Connected lives in contemporary mobile societies
Abstract
As individuals continue to move, precipitating one of the largest migrations in history, understanding how they derive their social support, reconfigure their personal networks to stay connected, and attach to the new location is important if we want to gain insight into how lives are connected in contemporary mobile societies. Previous generations of migration were more likely to cut their roots when they moved. Today people move and stay in touch through new communications media. In this context, this study aimed to explore how mobile individuals¿ mobility patterns affect their social support, personal networks and community attachment, as well as the role of new media across these three notions. Specifically, we look at: (1) what kind of social support is derived by mobile individuals, where is it located and how is it sustained; (2) whether the type of mobility differ systematically in personal networks of mobile individuals; (3) and if community attachment is related to the type of social support and personal networks of mobile individuals. Ninety-five mobile individuals who had lived in Seville for a minimum of three months were selected from four distinct communities. The four communities, namely Erasmus students, Japanese Flamenco artists, musicians from the local symphonic orchestra and partners of researchers working at the Institute for Prospective Technological Studies, varied in the types of mobility they propelled and were similar in attracting skilled international migration towards Seville. Field data was collected through an electronic multiple name generator, a structured face-to-face interview and a network visualisation tool. These methods enabled us to gather data on the social support network of the respondents, their media usage, community attachment, personal networks, mobility and socio-demographics. Results showed that a significant proportion of social support is kept over a distance. In particular, a great deal of emotional support is derived from distant ties with whom respondents meet yearly. Respondents stayed in touch with these ties mostly through frequent communication with mobile phone and email, and also through SNS in the case of young respondents. Participants relied mostly on specialized support: social companionship by recent friends; emotional and co-presence support from old friends and family; and instrumental support from compatriots. We also found that friends are major sources of support and respondents travel more to meet up with friends than with family. In terms networks, patterns of mobility reflected in the personal networks of our respondents were observed. Respondents who had lived longer in Seville were more likely to have personal networks dominated by the exogroup (locals, alteri living in Seville, friends), just as those who were in Seville for a temporary period, knowing that a displacement to another location (be it country of origin or other) was either imminent or definite, were more linked to the endogroup (alteri living in country of origin, family, compatriots, etc). Temporary mobility was characterised by frequent contact with social ties residing in other locations, replacement of strong ties by a wider variety of weak ties through which company and socialization is derived, and frequent travel to sustain support from distant ties. When it comes to community attachment, respondents appeared to be susceptible to a weak sense of community but this was not reflected in respondents¿ discourse on how they connected to Seville. Respondents characterised by a settlement type of profile were more likely to score a higher sense of community. Despite scoring low on the sense of community index used (McMillan & Chavis, 1986), participants claimed to connect to Seville in a variety of ways, reflecting different notions of community attachment. High listing of Spanish alteri providing multiplex support and the respondents¿ expectation of living in the host location for a long period seemed to be the strongest predictors of a high place attachment in our study.
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2 FromtheLaboratoryofPersonalNetworksandCommunities DepartmentofSocialPsychology‐UniversityofSeville ConnectedLives inContemporaryMobileSocieties [Adissertationsubmittedinpartialsatisfactionoftherequirements forthedoctoraldegree(Ph.D.)inSocialPychology] by RominaCachia B.Comms(UniversityofMalta)2000 M.A.(UniversityofSussex)2003 Advisor:Dr.IsidroMaya‐Jariego Seville,2013
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5 Abstract Asindividualscontinuetomove,precipitatingoneofthelargest migrations in history,understandinghowtheyderivetheirsocialsupport,reconfigure their personalnetworkstostayconnected,andattachtothenewlocationisimportantif wewanttogaininsightintohowlivesareconnectedincontemporary mobile societies. Previous generations of migration were more likely to cut their roots whentheymoved.Todaypeoplemoveandstayintouchthroughnew communicationsmedia. Inthiscontext,thisstudyaimedtoexplorehowmobileindividuals’ mobility patternsaffecttheirsocialsupport,personalnetworksandcommunityattachment, aswellastheroleofnewmediaacrossthesethreenotions.Specifically,welookat: (1)whatkindofsocialsupportisderivedbymobileindividuals,whereisitlocated andhowisitsustained;(2)whetherthetypeofmobilitydiffersystematicallyin personalnetworksofmobileindividuals;(3)andifcommunityattachment is relatedtothetypeofsocialsupportandpersonalnetworksofmobileindividuals. Ninety‐fivemobileindividualswhohadlivedinSevilleforaminimum of three months were selected from four distinct communities. The four communities, namely Erasmus students, Japanese Flamenco artists, musicians from the local symphonic orchestra and partners of researchers working at the Institute for ProspectiveTechnologicalStudies,variedinthetypesofmobilitytheypropelled andweresimilarinattractingskilledinternationalmigrationtowardsSeville.Field datawascollectedthroughanelectronicmultiplenamegenerator,astructured face‐to‐faceinterviewandanetworkvisualisationtool.Thesemethodsenabledus togatherdataonthesocialsupportnetworkoftherespondents,theirmediausage, communityattachment,personalnetworks,mobilityandsocio‐demographics. Results showed that a significant proportion of social support is kept over a distance.Inparticular,agreatdealofemotionalsupportisderivedfromdistant tieswithwhomrespondentsmeetyearly.Respondentsstayedintouchwiththese tiesmostlythroughfrequentcommunicationwithmobilephoneand email, and alsothroughSNSinthecaseofyoungrespondents.Participantsreliedmostlyon
6 specialized support: social companionshipbyrecentfriends;emotional and copresence support from old friends and family; and instrumental support from compatriots. We also found that friends are major sources of support and respondentstravelmoretomeetupwithfriendsthanwithfamily. Intermsnetworks,patternsofmobilityreflectedinthepersonalnetworksofour respondentswereobserved.RespondentswhohadlivedlongerinSeville were morelikelytohavepersonalnetworksdominatedbytheexogroup(locals,alteri livinginSeville,friends),justasthosewhowereinSevilleforatemporaryperiod, knowingthatadisplacementtoanotherlocation(beitcountryoforiginorother) waseitherimminentordefinite,weremorelinkedtotheendogroup(alteriliving incountryoforigin,family,compatriots,etc).Temporarymobility was characterised by frequent contact with social ties residing in other locations, replacementofstrongtiesbyawidervarietyofweaktiesthroughwhichcompany andsocializationisderived,andfrequenttraveltosustainsupportfromdistant ties. Whenitcomestocommunityattachment,respondentsappearedtobesusceptible toaweaksenseofcommunitybutthiswasnotreflectedinrespondents’discourse onhowtheyconnectedtoSeville.Respondentscharacterisedbyasettlementtype ofprofileweremorelikelytoscoreahighersenseofcommunity.Despitescoring lowonthesenseofcommunityindexused(McMillan&Chavis,1986),participants claimedtoconnecttoSevilleinavarietyofways,reflectingdifferentnotionsof communityattachment.HighlistingofSpanishalteriprovidingmultiplexsupport andtherespondents’expectationoflivinginthehostlocationforalongperiod seemedtobethestrongestpredictorsofahighplaceattachmentinourstudy. Noteaboutthecover: Theimageusedinthecoverisoneofthefirstmapsrepresentingasystemofroutes.Itdatesbackto 10,000yearsagoandisengravedonastoneinValcamonicainnorthernItaly.Themaprepresents theplace,butalsothepeopleinactivity.Inaway,itisthefirstbasicmapofsocialrelations.
7 Acknowledgements WhilewritingaPhDisasolitaryprocess,Iwasluckyenoughtobesupportedbya greatnetworkofpeoplewhomadethisstudypossible. IthasbeenagreathonourtohaveasmyadvisorIsidroMaya‐Jariego, whose intellectual rigor, dedication, clarity and personal commitmentforacademic researchhavehighlyimprovedthiswork.Isidronotonlybelievedinmywork,but alsogavemetheopportunitytodevelopintellectually,pushedme to think different, offered flexibility towardsmyever‐changinglifecircumstances and provided me with all the support possible to make this project intriguing, gratifyingandenjoyable. IamalsodeeplyindebtedtoRev.Prof.SaviourChirchop,alifetimementor,and withwhomIinitiallystartedthisacademicjourney.Ialsowouldliketothankmy colleaguesattheUniversityofMaltafortheircontinuouscollaboration and for makingmyhomeuniversitysuchapleasantenvironment. TheInstitute forProspectiveTechnologicalStudies (IPTS)wasthehomeofthis project.IamgratefulforthesupportIgotfrommycolleaguesandforthevarious academicopportunitiesIwasofferedwhichallowedmetogrowasaresearcher. Besides providing an intellectually stimulating setting, IPTS offered the ideal settingtolearnaboutmobility.Ihadaverynicetimethanksto Pauline, Eleni, Valentina,Penelope,Boris,Norbert, Ruki,Sira,LucaandMarghe,amongstmany others. Iamalsoluckytoformpartofasupportiveresearchteamatthe Universityof Seville.ThankyouDaniel,NachoandFranforyourgenerosityandforbeingthere whenadvicewasneeded.IamalsothankfultoMariaJoseJuradoMolina,Stefan Anderer,LauraOrtizandFranciscoJoséDeJuanVázquezforhelpingmewiththe datacollection.Variouspeoplehavehelpedmewithlocatingrespondentsinthis work.Inparticular,IwouldliketothankGretchenTalbot,YukoOgiandSergio GomezyPalomafortheirhelpwithintheirrespectivecommunities.
8 ForhisgenerouscollaborationindevelopingnewversionsofVennmakerforthe purpose of this project and making my ideas come to reality, I am indebted to MichaelKronenwett.IalsowouldliketothankMarcusGamperforreceivingmein TrierandkindlyinstructingmehowtouseVennmaker. ThisthesiswouldhavebeenverydifferentifIhadnotcrossedpathswithJoseLuis Molina, who back in 2006 introduced me to my advisor and who also gave me valuable research advise during the INSNA conference in Trento. Christopher McCarty,JorgePalacio,CarlosContreras,AntoniaSáez,YvesPunie,DavidBroster, andAnuscaFerrarialsoofferedresearchadviceondifferentoccasions. ThankstoSharonSpiteriandNatashaFeithforreadingpartsofthisworkand makingitlegibleandJoseMuñozRubioforrevisingtheformat.Allmistakesinthis documentaremine. Special thanks to my network of friends who put up with me all these years – thanks for being there when it really mattered. You kept things in perspective, reminding me of thebeautiful things in life. In particular, I would liketo thank Ursula,JulianaandCristiano(friendsImetinSeville,whodespitetheirmobilityto otherlocationsremainpresentinmypersonalnetwork),Cikkaand Sharon for beingthebestcompatriotsIcaneverhaveandDaniela,Sharon,Elaine,Gabby,Aly andLisaforyourdistantsupport.Iamalsogratefulformyswimmingteam(Club NatacionSevillaMasters),beingmylocalcommunitythroughwhichIlearntmost aboutcommunityattachment. Thisworkwouldnothavebeenpossiblewithoutalltherespondentswhokindly participatedinthisstudy,notonlygivingmesomeoftheirprecioustimebutalso willinglyrevealingtheirpersonallives. Iamthankfultomyfamilyforprovidingtheirendlesssupport.Iwouldnotbewho Iamtodaywithoutmyfather,whotaughtmeearlyoninmylifetobecritical. Whereveryouare,Iamsureyouareoneveryproudfather.Also,thankstomy motherwhogavemewingstogooutandexperiencetheworld.Mybrothernot onlyprovidedtechnicalsupport,buttogetherwithhiswifeMariaandhissonLiam, theyaremymajorsourceofemotionalsupport.Also,Iwouldnothavebeenableto
9 finishwritingthisthesiswithouttheunconditionalhelpofmymother‐in‐law, MaleniSotoNaranjo,aswellasRocio,whotookcareofmyson,soIcouldfinish writing. Lastonthelistbutfirstinmyheartandatthecentreofmypersonalnetworkare twospecialpeople:mypartnerJuanluandmysonSamuel.Havingachildinthe middleofyourdoctorateismorelikelytobenegativelycorrelatedwithfinishing andsubmitting.Inmycase,althoughithasnotbeenaneasyjourney,thejoyof motherhoodhashelpedoffsetagreatdealofthedissertationpressures,aswellas mademydeadlinesmoreurgent.Samuel:youmademummylearnhowto prioritise,usetimeefficiently,andyougaveheralltheenergyandmotivationin theworldtofinish. Ihavebeengiftedinmylifewithagreatpartner.Juanlu,yourdailyunconditional love, understanding and encouragement is what kept me going. Yourthreatsof sendingthechaptersyourselfifIreadthemonemoretimekeptmeontrackwith mydeadlines.Thanksforbearingwithmethroughtheexhaustion,frustrationand joyofthisproject,foryourconstantsupportandforyourendlesslove.
16 Todaythemottoistocirculateandkeepintouch (Diminescu,2008) ariè,aFrenchstudentarrivedinSevilleinSeptember2011asan Erasmusstudent.IkomovedfromJapantoSevilleinSeptember,five yearsearliertostudyflamencodancing.Thatsameyear,Riet,a Belgian artist moved to Seville with her husband, after he obtainedaresearch granttoworkforaEuropeanInstitutionlocatedinSeville.Riet,aloverofclassical musicknewBorisinSeville:aBulgarianviolinistwiththeSevilleRoyalSymphony Orchestra.BorismovedtoSevilletoworkfortheorchestra20yearsagoandnow has dual citizenship. The four share the same city. Their move to Seville was optionalanddesired.Theirstoryisfairlytypicalintoday’scontemporarymobile societies. Theactofcrossingspace,althoughoriginallystemmedfromthenaturalnecessity tofindfoodandinformationrequiredforsurvival,hasevolvedintoanewpractice. Mobility,whetherforwork,study,relationship,leisureorotherpersonalreasonsis becoming more and more common, especially in Western societies.Human mobilityisamajorcharacteristicbutalsoaconcernofcontemporarysocieties.Itis anindicatorofqualityoflifeandstatusontheonehand(Hoete,2004),butalsoa detrimenttocommunitybelongingontheotherhand(Putnam,2000). Understandinghowmobileindividualsreconfiguretheirpersonalnetworkstostay connectedwithclosetiesthatarefaraway,fabricateanetworkoflocaltiesand combinelocalanddistanttiesinapersonalnetworkonwhichtheycanrelyfor differentkindsofsupportisimportant,ifwewanttogetabetterunderstandingof how lives are connected in contemporary mobile societies. Whereas previous generations of migration were more likely to cut their roots when they moved, todaypeoplemoveandstayintouch(Diminescu,2008).Thishasledtoanewera inthehistoryofmigration,whatDiminescucalls:“theageofthe connected migrant”(p.568). At the heartofallthis,is a basichumancondition to stayin touchwithotherpeoplefromwhomweseekapproval,support,affection, with whomwegossip,shareopinionsandfallinlove.Belongingandlovearemajor
17 needs,followingphysiologicalandsafetyneeds(Maslow,1943).Changesinthese basic interactions is what marks historical changes in community life (Fischer, 1982a) This project stemmed from my interest in exploring how mobile individuals sustaintheirsocialsupportnetworkonthego.Departingfrommyownstory,a foreigner residing in Seville originally for work purposes, we hypothesized that mobileindividualsarenotonlyhighlyconnectedbutrepletewithdifferentchoices onhowtosustainsocialrelations,socialsupportandpersonalcommunities.To studysocialrelations,andhowsocialsupportflowsthroughsuch relations, we figuredthattheexaminationofeachpersonalnetworkofourrespondentwasthe mostinterestingandinsightfulwaytoexaminesuchrelations. Forthispurpose,weinterviewedninety‐fivemobileindividualsfromfourdistinct communities who had lived in Sevilleforaminimumofsixmonths. People’s personalnetworksarepartoflargersocialnetwork,whichlinkedtogetherdefine our society (Fischer, 1982a). In the case of mobile individuals, their personal networksareembeddedindifferentpersonalcommunitieswhichrepresenttheir trajectories. While the role of large‐scale institutions, in particular corporations andstatesininitiatingandshapingmigrationflowshasbeenstudiedextensively (Castles, 2002), little attention has been devoted to the role of small relational communitieswhichareindispensableforthemobileindividual. In this study, we combine theories of social support, personal networks and communitytoprovideaunifyingframeworkofanalysis.Uniquetothisstudyare thefollowingmeasures:(1)intermsofcommunity,weproposestudyingrelational communitieswhichshapethetypeofmobilityofourrespondents,soastobetter understandhowthesesocialstructuresinfluencemobilitypatterns;(2)with respect to social support, we propose an alternative multiple name generator basedonpreviousworkbyotherresearchers(Barrera,1980;Marin&Hampton, 2007; Maya Jariego & Holgado, 2005), but also incorporating a new dimension uniquetoourstudy:thenotionofco‐presence(Larsen,Urry,&Axhaussen,2006); (3)inthecontextofpersonalnetworks,wesimultaneouslyanalyse two sets of data following similar measures used by McCarty (2002): data fromthe95
18 respondents and data from their 2,850 alteri.1We also utilize a relatively new software,Vennmaker(Schönhuth,Kronenwett,Gamper,&Stark,2012)todevelop thepersonalnetworkswiththerespondentsduringtheinterviewandtoproduce networkvisualisationsfortheanalyses. Thetopicofmobilityiswideanddependingonthefieldofstudiescanbestudied fromvariousaspects.ThisworkaddressesmobileindividualsinSeville,soasto explorehowsocialsupport,communityattachmentandpersonalnetworks are interrelated.Asmobilityisonlyasmallpartofthisworkandtherearealready severalexcellentreviewsofmigration,weonlyskimovermanyotherimportant factorswhichrelatetomobility,soastokeepwithinthescopeofthisstudy. 1.1DissertationOrganization This dissertation is organized around three sets of notions central to mobile individuals – socialsupport,personalnetworksandcommunitylife.The three notionsarefurtherlinkedthroughanotherdimensionwhichishavingasignificant impactonthelivesofmobileindividuals,theuseofnewcommunicationsmedia. Chapter 3 examines the social support networks of mobile individuals living in Seville.Differenttypologiesofsocialsupportelicitedfrommultiple name generatorsarestudiedagainstnetworkcomposition,mobilitypatterns and differentmodesofcommunication. Chapter 4 explores how different mobility patterns are reflected in the compositionandstructureofpersonalnetworks. Chapter5accountsforhowsenseofcommunity,socialsupportand personal networksofmobileindividualsareinterrelated,aswellasexplores how respondentsexperiencecommunityattachmentwiththehostlocation. Eacharticlefollowsasimilarstructure.Thetheoreticalframeworkispresentedat 1Eachrespondentinthisstudywasaskedtolist30alteri,fromwhichherpersonalnetworkwas developed.Byalteriwerefertothepeoplerespondentsrelyforsocialsupportintheirpersonal network.
19 the beginning, leading up to the definition of the research questions and the methodused.Thisisfollowedbyresultsandadiscussionoftheresults.Datafor thisstudywascollectedthroughstructuredface‐to‐faceinterviews, a multiple namegeneratorconductedthroughemailandnetworkvisualizations compiled during the interview through Vennmaker (Schönhuth et al., 2012). The major methods for analysis were personal network analysis,cluster analysis, sense of communityindex,casestudies,factoranalysisandcontentanalysis.Analysiswas conducted using the software SPSS (version 17 for Windows), Vennmaker (Schönhuthetal.,2012)andUcinet(Borgatti,Everett,&Freeman,2002). While each chapter stands on its own, for the purpose of the dissertation, the chaptersshouldbereadinchronologicalorder.Chapter3exploresindetailhow thesocialsupportnetworkwaselicited.Theanalysisofthepersonalnetworksof respondentsinChapter4isbasedonnetworkselicitedthroughthemultiplename generatorasoutlinedinChapter3.TheclusteranalysisreportedinChapter5is basedonfindingsfromChapter3andChapter4.Forthoseseekingmoredetailon thedatacollection,thetwoinstrumentsusedinthisstudyarefoundinAppendix2. Allthepersonalnetworkvisualisationsofeachrespondent,thatis,thefreehand drawingandtheVennmakerandUcinetmapsarepresentedinAppendix3. Ashortoverallconclusionispresentedattheendofthedissertation,summarizing themajorfindingsofthiswork,ourownreflectionontheresultsandimplications for future research. The next section of this introduction mapsoutthecentral theoreticalframeworkofthisstudy. 1.2Thecommunitydebate Mobility has become an integral part of Western societies. Withinthepastfew decades,therehasbeenagradualupturninmobilityflowsinEurope.Cheapand easytravel,urbanismandglobalisationandreal‐timeaccessofnewinformation technologieshaveallcontributedtosuchanincreaseinmobility.InEurope,the political decision to open up borders amongst countries pertaining to the European Union (EU) has also facilitated mobility across countries within the Union. However, while the achievementofaunitedEuropeancommunity is a
20 majorgoalforEurope,amajorconcernemergingfromsocialsciencesiswhether such an increase in mobility is leading to adverse results. Are people becoming moreisolatedandlosinginterestinthecollective? Mobilityhasprovokedawidearrayofdebatesontheroleofcommunity in contemporarysocieties.Westernindividualsroutinelyformsocialconnectionsand communicate with people who are far away, continuously participating in ephemeral configurations of togetherness in different spaces. Sincethe1950s, distancebetweenmembersofsocial,familialandwork‐relatednetworks have substantiallyincreasedandspreadout(Albrow,1997;Cass,Shove,&Urry,2005). People’s houses and activities are more spatially distanced than ever before, provoking long distance travel in order to meet face to face (Larsen,Urry,& Axhaussen,2006).Inthe1800s,atypicalAmerican citizenatmosttravelled50 metres.In2002,50kmtravelperdaybecamethenorm(Buchanan,2002).Such socialchangesaresaidtohavenegativeimplicationsonthewaypeopleparticipate incommunitylife.Putnam(2000)foundthatinAmericapeoplewere less connected,hadlessface‐to‐facetalkandshowedlittlelocalcivicengagement.The majorityofpeoplelivingincitiesspendatleastonehourcommutingtoandfrom work,andsomeevenspendtwohourseverydayintransit(Barley,2004).Time spentcommutingequalslessleisuretimespentwithfamilyandfriendsandless timededicatedtocommunitylife. Amajorpoolofstudiesaddressingnotionsofcommunityoriginatedfromthe20s and 30s from the Chicago school. These studies were based on the notion that humanbehaviorisdeterminedbysocialstructuresandphysicalenvironment,as opposed to genetic and personal characteristics. Within the span of 50 years (1860‐1910),Chicagogrewfromasmalltownwithapopulationof10,000toabig city, whereby the population exceeded two million. Taking Chicago as a city laboratory,researchersattemptedtodefinecommunityaroundadefiniteterritory, muchinfluencedbynotionsofthenation‐state(Albrow,1997),asawayoflooking forevidenceonhowurbanizationandsocialmobilitywerecausingcontemporary socialproblems(Wirth,1938).
21 Amajorproblemwithstudyingcommunityandlocalityasaunifiedunitisthefact thatcommunitiesaretreatedasisolatedstructuresandhence,it is difficult to capturetheflowofpeoplebetweencommunities.Thisbecameamajorconcernin someofthepioneeringworkofpersonalnetworkanalysiswhichoriginatedinthe Manchester School. Gluckman and Barne found that in order to study formal groupseffectively,theyhadtostudythepersonallinksbridging these organizations(McCarty&Molina,forthcoming).Intheirstudyontheimpactofa newhousingestateonanoldervillage,EliasandScotson(1965)alsofoundthat theycouldnotstudythetwolocations,withoutlookingintotherelationsbetween people.Intreatinggeographicalsocialmobilityasthemaincomponentofstudy, “communityitselfhadtobeseenasacontingentfeatureofsocialrelations,evenan ephemeralconfiguration”(Albrow,1997,p.42). Research in the 90s highlighted the need for new approaches forstudying communityandlocality(Appadurai,1990;Bhabha,1990;Hall,1992).Inthestudy based in the inner London borough of Wandsworth, Albrow (1997) found that whattheinhabitantsinthisareaexperienceisnothinglikethetraditionalconcept ofcommunitybasedonasharedlocalculture.Whiletheyallsharedthesame locality,theirmeaningfulsocialrelationswerealmostentirelyoutsideandacross theglobe:“ThesingleyuppiewithbusinessinBrusselsandholidaysinSeychelles canignoretheunemployedladnextdoorandisunconcernedbythelackofplay spaceoftheAsianfamilyinthenextstreet.They,inturn,mayhardlyknowoftheir neighbours’existencesincetheirpathsmayrarelycross”(p.53) Studieshaveshownthatthespreadingofsocialrelationsmakes connections weaker and more transient (Wellman, 1999b) and this has some negative implicationsonhowindividualsparticipateinlocalcommunitylife(Hunter,1978; Putnam,2000).ThecontroversyonthedeclineofcommunityintheUnitedStates becamemostlyprominentwiththepublishingoftheresultsfromtheGeneral SocialSurvey(GSS)in1985,whichincludedquestionsaboutthepersonal networksofrespondents.Researchersfoundthattheaveragenumberofclose‐ties with whom Americans discuss important matters was 2.94. A decade later, McPherson,Smith‐LovinandBrashears(2006)repeatedasimilarstudyandthe
22 resultscreatedmorealarm,asincomparisontothe1985GSSdata,theaverage number of core network structures in 2004 had decreased from 2.94 to 2.08. Moreover, the number of people claiming they had nobody with whom they discussedimportantmattershadtripled.2 ThepublicationofBowlingAlone:TheCollapseandRevivalofAmericanCommunity byPutnam(2000)heraldedtonewprominencethedebateonsocialisolationand decline of community. Echoing the work of de Tocqueville and his notions that participation in communities would help enhance democratic institutions and personalwell‐being,Putnamillustrateshowsocialcapital‐the quantifiable number and density of how individuals connect with civil society ‐ has been declining since the 1950s. Drawing evidence from 500,000 interviews, Putnam foundthatoverthelastquartercentury,citizensbelongedtofewerorganizations, knewlessneighbours,metfewerfriendsandsocialised lessoften withfamilies. MoreAmericanswereplayingbowling,buttheywerenotbowlingin leagues. Putnam attested such social changes to changes in work, family structure, age, suburban life, television, computersandwomen’srolesinsocieties, amongst others. Mobilityisoftenseenasadeviationtoplaceattachment,place‐basedcommunity, territoriality,identityandroots(Gustafson,2001).Politically,theideathatmobile individualsdonotbasetheiridentityandattachmentsolelytoaspecificlocationis apowerfulchallengetotraditionalideasofrigidnation‐statebelonging(Castles, 2002).InhisanalysisoftheGSSdata,Fischer(2011)foundthatmobilepeopledid nothavelesssocialtiesthannon‐mobileones,asisoftenassumed in the discussion on isolation in America. Increasing numbers of mobile individuals orienttheirlivesinmorethanonesociety,developingtheirsocialrelationswithin transnationalcommunities(Castles,2002).Althoughtimespentinonecommunity istimenotspentinanothercommunity(MayaJariego&Armitage,2007),relations 2TheresultsfoundbyMcPhersonetal.,(2006)ledtofurtheranalysisofthesamedatafollowing thecritiquebyFischer(2009),whoarguedthatthe2004resultscontainedseriousanomaliesand thatthedramaticincreaseinsocialisolationisnotasalarmingasreportedinthe2004study.
23 withindifferentcommunitiesindifferentlocationsmaybekeptsimultaneously.In someinstances,itcouldresultinmoreflexiblerelationswhereindividualscould “quickly plug in, pursue opportunities and build a wide range of relationships” (Florida, 2002, p. 220). Florida attests that youngish well‐educated people who tendtobemoremobileprefertolerantanddiversecommunitiesof weak‐ties, rather than tight‐knit small town communities, as such type of communities contributetocreativecapital. Associalconnectionsareincreasinglykeptatadistance(Albrow,1997;Fennell, 1997;Horrigan,2001;Licoppe,2004;Wellman,1996,2002),thosewhoarenear emotionallyare possibly geographicallyfar away. Such hybrid relations involve different mechanisms on how mobile individuals connect to different groups, communities, networks and other socialstructures.Theconceptof connectivity throughmobilitypresentedbyLarsen,etal.(2006),provideanalternativewayof lookingathowmobileindividualsareembeddedindifferentsocialstructures.As people move to live in other locations, their sense of community is not merely rooted in location based communities, but is increasingly shifted to relational communities(Bess,Fisher,Sonn,&Bishop,2002;Kayahara,2006).Thistransition from small groups to networked individualism suggests that communities are increasingly defined socially as opposed to spatially (Wellman, 2002). In this respect,ifwewanttostudyhowmobileindividualssustaintheirhybridrelations, we need to shiftto methods which capture suchrelations, for whichtheuseof personalnetworkswasdeemedpertinentforthepurposeofthisworktostudy socialsupport(Chapter3)andmobilitypatterns(Chapter4). Intryingtounderstandhowmobileindividualsspreadtheirnetworksandderive social support from their portable communities, we thought that examining whether they experience a collective belonging in the new host location isalso important.Existingresearchoftenignorestherelationshipwhichexistsbetween mobilityandterritorialbelonging,assumingthatmobilepeoplehaveaweaksense ofbelongingbydefault(Gustafson,2009). InthisstudyweusetheSenseofCommunityIndex(SCI)developedbyMcMillan& Chavis(1986)tomeasurebelongingandidentificationwiththehostlocation.The
24 psychologicalsenseofcommunity(PSOC)constructwhichoriginatesfromthework ofSarason(1974)wasdevelopedtodescribeacollectivebelongingindividualsfeel whentheyformpartofsocialgroups.TheSCIisbasedonfournotionsmeasured through specific items, namely: membership, feelings of emotional safety with a senseofbelongingandidentification;influence,exertionofone’sinfluenceonthe communitywithreciprocalinfluenceofthecommunityononeself;integrationand fulfilmentofneeds,physicalandpsychologicalneedsmettherebyreinforcingone tobehaveinamanneracceptabletothecommunity;andsharedemotional connection,positiveeffectrelatedtocommunitymembership. TheSCIhasbeenappliedandrevisedtostudyvarioustypesofcollectivegroups andcommunites,locational,aswellasrelational,asforinstance,neighbourhoods (Chavis&Wandersman,1990;Garcia,Giuliani,&Wiesenfeld,1999;Glynn,1986; Perkins,Florin,Rich,Wandersman,&Chavis,1990);migrants(Hombrados‐ Mendieta,Gomez‐Jacinto,&Dominguez‐Fuentes,2009;MayaJariego&Armitage, 2007;Sonn,2002);adolescents(Pretty,Conroy,Dugay,Fowler,&Williams,1996; Vieno, Perkins, Smith, & Santinello, 2005); fandom (Obst, Zinkiewicz, & Smith, 2002a, 2002b); multiple communities (Maya Jariego & Armitage, 2007); virtual communities (Blanchard & Markus, 2002, 2004; Forster, 2004; Previte, Pini, & Hearn,2003;Wang&Gloviczki,2008)andnetworks(Calvi,2008;Hughey&Speer, 2002)amongstotherareas. 1.3ElicitingtheSocialSupportNetwork Thesecondmajortheoreticalframeworkthatshapesouranalysisconcernsthe socialsupportofmobileindividuals.Socialsupportisdefinedas“theexistenceor theavailabilityofpeopleonwhomwecanrely,peoplewholetusknowthatthey careabout,valueandloveus(I.G.Sarason,Levine,Basham,&Sarason,1983).Itis anaturalresource,whosemeasurehasfascinatedmanycommunitypsychologists. Theincreasinginterestinsocialsupportcanbeseenfromthenumberofcitations overthepastdecades.From1978to1984,citationsofsocialsupportincreased from25to555,andalthoughstudieslevelledoffinthe90s,in1996therewerestill 707citations(Barrera,2000).
25 The focus on social support emerged in the 60s, as an alternative approach to studymentalhealth,shiftingthefocusfromtheindividualtothe community (Agneessens, Waege, & Lievens,2002; Levine & Perkins, 1997; Martinez Garcia, GarciaRamirez,&MayaJariego,2001).Scientificinterestinsocialsupportgrew morethoroughlyinthe70sasmoreresearchshowedthatpeoplefacingemotional problemsandinmomentofcrisisresortprimarilytotheirintimateties,rather than to professional mental health services (Caplan, 1974; Cassel, 1974; Cobb, 1976). The understanding of social support has evolved over theyearsfroma conceptusedtodescribeattachment,affiliationandsocialintegrationtotheidea thatsocialsupportisawayofhowindividualsfeelempoweredthrough the provisionofsocialrelations(Barrera,1980).Thepositiverelationbetweensocial support,individualwell‐beingandhealth(Cohen,Brissette,Skoner,&Doyle,1999; Cohen & Syme, 1985) is a major line of research where investigation pursues (Molina,Fernandez,Llopis,&McCarty,2008). Untilthe80s,researchonsocialsupportwaslimitedduetoalackofareliable, generalandconvenientindexofsocialsupport(Barrera,1980;I.G.Sarasonetal., 1983). This resulted in a wide array of studies developing new approaches to assesssocialsupport.Distinctmethodsofhowthelistofsocialsupportproviders may be elaborated have been developed (Agneessens et al., 2002;Bidart& Charbonneau,2011;Marin&Hampton,2007;McCallister&Fischer,1978;vander Poel,1993).Ingeneral,dataiscollectedthroughaskingrespondentstolistpeople whoprovidedifferentkindsofsupportortospecifytheavailabilityofdifferent kindsofsupportfromanexistinglistofsocialrelations.The former method is oftenusedtocreateanamegenerator,asinthecaseofthisstudy.Thisapproach reliesonspecificquestionsdesignedtoidentifythepersonswhogivespecifictype ofsupport. Recent research has sought to highlight different aspects of social support, promotingtheideathatdifferenttypesofrelationshipsmaybestowavarietyof socialsupport(Agneessensetal.,2002;Walker,Wasserman,&Wellman,1993). Althoughnostandardsocialsupportinstrumentexists,mostresearchers base their studies on three mayor types of support, namely:emotional, instrumental
32 networkssacrificeemotionalclosenesswiththeiralterswhencomparedwithegos withsmallernetworks(Robertsetal.,2009). Estimating the number of people an individual knows does not yield the same results as the identification of those people whom an individual considers important and actively maintain contact with (Hill & Dunbar, 2003). In a reanalysis of his data on people in Toronto, Wellman (1999c) found that the significanceoflocaltiesonlybecameapparentwhenthetypical measurement indicatorofcountingtieswasreplacedbyfrequencyofcontactegoshavewith theirties.Suchfindingswerekeptinmindwhendesigningthenamegeneratorof this study. For each of the alteri mentioned, respondents were asked how frequentlytheycommunicatedwiththemface‐to‐faceandthroughdifferentmedia, asawaytomeasurehowactivetheego‐alterrelationis. Fromrootstoroutes Althoughwehavecomealongwaywithnewmediatechnology,researchshows thatdistancestillmatters(Axhausen&Frei,2008).Thefrequencyofface‐to‐face contactandalsooftelephonecontacttendstodecreaseasdistancebetweenties increases.Interestingly,emailcontactandtheprovisionofsocialsupportdonot seemtobeaffected(exceptformaterialsupport)(Mok&Wellman, 2007;Mok, Wellman, & Carrasco, 2010). Licoppe (2004) found that while telephone conversationdecreased,thelengthoftimeonthephoneincreased,asifhavingthis typeofopenconversationwasasignofbonding(Goffman,1971)withtheabsent other. Paradoxically,althoughfarawayemotionaltieshaveneverbeensoclose,people travelmorethanever,spendingconsiderablyamountofmoneyandtimeonthe roadtomeetphysicallywiththeirfamilyandfriends.Thesignificantroleofthese face‐to‐face interactions manifested in attendance to significant events such as, weddings,familymeals,funeralsandbaptismstomentionbutafew,wasalready highlightedinthe70sbyGoffman(1971). Theneedtotravel,giventhewidearrayofopportunitiesofnewcommunications technologyforvirtualproximity,promptedanewlineofresearchfocusedonco
33 presence. A tie remains active through occasioned co‐presence(Larsen, Urry, & Axhaussen,2006)andmeetingness(Urry,2003).Thereisagapinliteraturefailing toexploretheprocessesbywhichco‐presenceandintimacyarebroughtaboutin travel, through which a sense of connection is sensed and maintained (Larsen, Urry,&Axhaussen,2006).Suchtypeoftravelisimportanttostudyforitssocial and emotional significance. This aspect of travel, which Larsen et al. term as tourismproximitylooksintoleisuretravelforreconnectingwithfriendsandfamily memberslivingelsewhere,ratherthanforseeingnewandinterestingplaces.This compulsiontoproximity (Larsen, Urry, & Axhaussen, 2006) so characteristic of mobilecontemporarysocietiesmadeusreflectsubstantiallyonhowpeopleonthe moverelyonsuchtripsasaformofsupport.Theactoftravel,itselfbecomesaway of feeling empowered. This reflection prompted us to explore how ties are sustained through the examination of copresenceasanothertypeofsocial support,forwhichwehavedevelopedamultiplenamegeneratorwhichtakesthis aspectintoaccount. 1.5ConceptualisingMobility Todaywelive,workandroaminaworldofperpetualmotion. Themobilityofpeople,goods,informationandservicesconfronts, permeatesandsaturatesoureverydayexistence. (Hoete,2004,p.9) Virtualbondsmakeiteasierthaneverbeforetostayintouchwithlovedonesona dailybasis.This“paradigmaticfigureoftheuprootedmigrant”makesreferenceto anothertypologyofmigrantfigurewhichisill‐definedincurrent literatureand research:amigrantfigureonthemovewhosimultaneouslyreliesontiesoutside his group of belonging, but also stay well connected with the social network at home,oranyotherplacethemigrantmighthavelivedinhismobile trajectory (Diminescu,2008, p.567).Diminescu, echoingtheworkofLarsenet al., (2006)
34 speculates the need for more appropriate measures to define the21 stcentury migrantbasedonmobilityandconnectivity. Overthepastfewyears,weobservethathumanmigrationisnotonlyonthe increase,butitisalsobecomingmorediverse(OECD,2001).Thegenericdivide andtraditionalcategoriesbetweenmigrant,foreigner,immigrant,nomadandeven sedentary is blurring (Diminescu, 2008). In our attempt to use a generic term which characterised all the respondentsinoursample,wefoundourselves grappling with terminology. Most migration research is focused on immigrants, defined“aspeoplewhomovefromonecountrytoanotherorfromoneregionto another,whichissufficientlyfarawayandforlongenoughtoinvolvelivinginand carryingouttheactivitiesofdailylifethere”(Hombrados‐Mendietaetal.,2009,p. 673).Thetermimmigrantisgenerallyusedforthosepeoplewhomovetoanother countrywiththeideaofbuildingabetterlife,soastoseeknew opportunities (Criado,2000). Incontrast,themigrantisusuallydefinedassomeoneintransit,“whocomesto work,travelsacrossourterritoriesandcities,andwhogoesbackhomeorleaves forsomewhereelse”(Diminescu,2008,p.566).Thetransitnatureofthemigrant posessomeambiguitybecauseinmigrationstudies,transitmigrationalsorefersto migrantswhohavetransitedor may transitsomewhere,passingthroughto anotherdestination,whichisoftentheEU(Collyer,Düvell,&deHaas,2012).These termsgroupsa“heterogeneousarrayofmigrationprocesses,migrants,potential migrantsandcountriesaroundalimitedseriesoflargelyundefinedcommonalities involvingillegality,highrisk,lackofcontrolandaboveallanassumeddesireto reachEuropeanterritory”(Collyeretal.,2012,p.411).Itreferstothestagebefore beingtransformedintoanimmigrant(Hess,2012). Anothertermcommonlyusedforpeoplewhomovetoanothercountryforashort periodoftimeistemporaryorcirculatorymobility.Bell&Ward (2000) define temporarymobilityas“anyformofterritorialmovementwhichdoesnotrepresent apermanent,orlasting,changeofusualresidence”(p.88).Incomparisonwith permanent migration and transit migration, temporary migration has received much less attention in academic research. While the significance of temporary
35 mobilityhasbeenrecognizedalreadyinthe70s(Zelinsky,1971),developmentof data,theoryandmethodfortemporarymigrationremainslimited(Bell&Ward, 2000). Insomecountriespeoplechangeresidencevarioustimesintheirlives,however, suchmovementisgenerallynotcapturedintraditionalmigrationmeasures,such asthecensus.Individualswhofrequentlychangelocationtendto dedicate less timetolocalcommunitiesandaremorelikelytomaintaincontact with distant closeties(Shklovski,2007).Studyingdatafromthe1996AustraliaCensus,Bell& Ward (2000) found that this type of migration is triggered by different circumstances. Permanent migration is more likely to be linked toasignificant eventinthelifecourse,suchasmarriage,familyformation,changeofemployment ormarriage.Incontrast,temporarymigrationismorelikelytobelinkedtothe intrinsicstateofthemover.Thepursuitofeducationorentryinthelabourmarket mayresultinmobilityinearlyadulthood,whilefreedomfromworkcommitments willleadtoretirementkindofmobilityduringlateadulthood.Intermsofdistance, theauthorscalculatedamedianmigrationdistanceforpermanentmigrantsof16.2 km,incomparisonto167.8kmfortemporarymovers. In deciding which term to use for our respondents, we realized that the terms abovewereuseful,butonlytodescribe different groups of oursample.As discussedbyHess(2012),migrationresearchishighlypolitical.Theactofnaming andcategorizingcross‐bordermovementofpeopleoftensurgesoutoftheneedto developpolitical objectivesandmigrationpolicies.Inordertoavoidfallinginto suchpoliticalpitfalls,wehaveoptedtoutilizethetermmobileindividuals,ageneric term which encompasses different kinds of mobilities by different type of foreignerspresentinoursample. AsdiscussedinChapter3andChapter4,mobileindividuals’networks and the typeofsocialsupporttendtobeshapedbyfactorsrelatedtothetypeofmobility. Apartfrom the time frame,mobilitypatternsare also shapedbythereasonfor mobility. Depending on the type of mobility, individuals optimizetheirsocial supportnetworkstosuittheirlifestyle.Astudentwhoisstudyingforafewmonths inaforeignlocationisunlikelytoshiftallhistiestothenewlocation.Generally,
36 thistypeofmobilitygeneratesapersonalnetworkwithhighdensityinthecountry of origin and more sparse groups in the country of residence.In Chapter3, we discusshowthetypeofmobilityhasaninfluenceonthetypeofsupportderived fromone`spersonalnetwork.Chapter4’sexaminationofthepersonalnetworksof ourrespondentsisrootedinthewaydifferentpersonalnetworksareconfigured dependingonone’stypeofmobility. Thedimensionofthesocialstructureweareinterestedtostudyinthisarticleis therelationalmobilitycommunity.Intheabsenceofabetterterminology,weuse thistermtorefertothetypeofcommunitywhichplaysamajorroleindefiningthe typeofmobilityundertakenbyourrespondents.Therelationalmobilitycommunity inourstudyimpliestoacertainextentacollectiveidentification amongst its members,whichproducecommonconcernsthroughwhichrelationsare constituted. Basedonpreviousresearchandinthecontextofthiswork,mobilitypatternsare examinedalongthreedimensions:timeplanningtostayinSeville,timespentin Sevilleandreasonformoving.Fortheanalysisofthiswork,weproposeacommon classificatoryframeworkwhichformsthebasisforatypologyofmobilitypatterns, asillustratedinFigure1.Theclassificatoryframeworkenables us to highlight majordifferencescharacteristictoourrespondents,intermsoftheirmobility. Figure1:CommonClassificatoryFramework
37 Asindividualscontinuetomove,precipitatingoneofthelargest migrations in history,thestudyofcommunityisbecomingmorecomplexthanever.Formany peoplelikeme,whowerebroughtupinonecountry,studiedinanother,workedin athirdandbuiltafamilyinafourth,itishardtospeakofdelineatedcommunities. As you move around, your personal network expands and ineach location you rediscovernewbearingsandfindwaysandmeansofconnectingmoretopeople and less to spaces. Mobility affords an opportunity to seek your own personal communities and your social support networks. While on the one hand, there seemstobeademiseofcommunity,ontheotherhand,mobilityaffords and provokes new types of community formations to which personal networks are attached.Althoughthethreenotionsofthiswork‐socialsupport, personal networksandcommunityattachment‐haveaffecteddifferenttypesofindividuals before,theincreasingdiversityofmobilityhasintroducedthesenotionstoanew academicterrain. Beforeturningtothemainanalysesofthiswork,wemustestablishthecontextof thisstudy.Chapter2setsthecontextofthisstudy:whoaretheparticipants,what aretheproceduresandthemethodsadoptedandthemeasureused.Subsequent chapterspresentthemainanalysisofthisstudywitheachchapter specifically lookingintosocialsupport,personalnetworksandcommunityattachment.
Chapter 02 The Setting
39 …Iacquiredveryearlythesenseofbeingloosedfromtimeasmuchasfrom space…Asapermanentalien,I’veneverbeeninapositiontovote,and,infact, I’veneverheldajobinthecountrywhereImoreorlesslive (Iyer,2000,p.384) Inthischapterwepresentthedesignofthestudy,themeasuresandmethodsused andhowwehaveanalysedthedata.Westartbydescribingtheparticipantsand communities selected, followed by the sampling procedure and finally, the researchdesign. 2.1Participants&Communities Tobetterunderstandthepersonalrelationsofmobileindividualsandhowthese relations are linked to a type of mobility, from January 2012 toApril 2012, we interviewed 95 foreigners living in Seville. We asked participants about their personalnetworks,communityattachment,socialsupportanduseofnewmedia technology.RespondentswereselectedacrossfourtypesofcommunitiesinSeville whichpooltogetherdifferenttypesofmobilities.ThecommunitieswereErasmus students, Japanese Flamenco artists, musicians from the symphonic orchestra (ROSS)andpartnersofresearchersworkingattheInstituteforProspective TechnologicalStudies(IPTS).Eachcommunitywillbebrieflypresentedinthenext paragraphs. ErasmusstudentsbelongtotheERASMUSProgramme,thelargestworldwide student exchange programme. Since its inception in 1987, almost3million studentsfrom33countrieshaveparticipated.3Eachyeararound230,000Erasmus studentsstudyabroad.4Thesestudentsareexemptedfrompayingfeesfortuition, registration, examination and access to library at the host institution. Their mobility is aimed to contribute towards personal development and acquiring a widerangeof competences andskills:languages,interculturalawareness, quick 3 The27EuropeanUnionmemberstates,Croatia,Iceland,Liechtenstein,Norway,Switzerlandand Turkey. 4http://ec.europa.eu/education/erasmus/doc/stat/erasmus1112_en.pdf
40 adaptability to changes and entrepreneurial mindset. Within theErasmus programme, Spain is the most popular destination (2011‐12: 39,300 students received)andtheUniversityofSevilleranksasoneofthetopreceivingSpanish universities. RespondentsselectedforthisstudywerestudyingattheUniversityofSevillefora year.Ingeneral,studentsplannedtogobacktotheircountryoforiginattheendof thescholasticyeartofinishtheirstudies.Inthecontextofthisstudy,theErasmus student community is interesting for various reasons. In general, students are easilyaccessible tostudy.Moreimportantly,theirmobilityisunique,givenitis temporalanddefinedbya specifictimeperiod.Their displacementto Sevilleis framedwithintheErasmusprogramme,whichfacilitatestemporarilysettlement inSevilleandmakesiteasierforthemtorelateandidentifywithotherErasmus students. The Japanese flamenco artists moved to Seville to pursue their training in flamenco.Whilethemajorityofrespondersaredancers,thesamplealsoincluded musiciansandsingers.Smallandpeculiar,thiscommunityoriginatesfromthe60s throughpioneerdancerswhotravelledtoSpaintolearnflamenco and consequentiallyopenedacademiesanddancecompaniesinJapan(Minder,2013). ThiscommunityisonlyasmallpartoftheJapaneseexpatcommunity in Spain whichmainlyconsistsofdirectorsandmanagersofmultinationals,entrepreneurs, investorsandqualifiedtechnicians,mainlylivinginMadridandBarcelona(Beltrán Antolin & Sáiz Lopez, 2002). Japanese students and artists also comprise an important part of the Japanese expat community, which in 2001 amounted to 3,259.5 Forthepurposeofourstudy,theJapaneseflamencoartists’community was interesting because it is highly unique, clearly defined and very little academic 5According to Beltrán Antolin & Sáiz Lopez (2002), the works published on Asian communities distinguishbetweencolonyandcommunity,wherebytheJapaneseinSpainarereferredtoasthe former.Theimplicationsofthistermisthatasopposedtocommunitylikeforinstancepeoplefrom Morocco,peopleareassumedtobemoreisolatedwithlittlecontactwiththehostsociety,tendto behighlyqualifiedwithhighlypaidjobsandareassumedtoberich.
41 researchhaslookedintothistypeofcommunity(moststudieshavefocusedonthe Japanese entrepreneurial community)(Cuesta Avila, 1997; Pelegrin Sole, 1996; Ramos Alonso & Ruiz Ruiz, 1996; Rocafort Nicolau, 1990; Villa Cellino, 1987)). Theseartists,althoughhighlydistinctiveintheirappearance,language,cultureetc, shareaspecializedpassionwithlocals.Thestrongsenseofcommunitytheyhave withintheFlamencocommunityinSevillewasforinstance,epitomizedintheway localflamencoartistsinSevillemobilisedresourcestohelptheirfollowJapanese colleaguesfollowingtheFukushimaearthquakein2012.67 In general, Japanese flamenco artists come to Seville as students and work to financetheirflamencoclasses.Theirmobilityisnottemporallydefined.Somego backtoJapanormovetootherlocations,whileothersstay:“Istartedflamencoasa hobby,butitalsomademethinkaboutwhetherIcouldeverbehappystayingin Japanandworking14hoursaday.”(Minder,2013).Movingtoanewlocationfora passiondefinesaveryspecifictypeofmobility.Weassumedthatparticipantsin thiscommunitycometoSevillewithalreadyaverystrongsenseofbelongingto theFlamencocommunity.Ingeneral,theflamencocommunityseemstobeanopen typeofculture,however,wehavelearntfromvariousflamencodancers,thatwhile astrongsenseofunitydefinesthecommunityingeneral,atthesame,itisnoteasy tobeintegratewiththecorenetwork,whichmostlyconsistsoflocalartists.This suggests that while belonging is high, membership is gained through respect acquiredfromthecorenetwork. OurthirdcommunityconsistsofpartnersofemployeesworkingfortheInstitute forProspectiveTechnologicalStudies(IPTS),oneofthesevenscientificinstitutes oftheEuropeanCommission’sJointResearchCentre(JRC).Thisresearchinstitute, which is in operation in Seville since 1994, employs around 200 people out of which a high majority consists of foreigners. From this group of foreigners, we selectedpeoplewhoprimarilyhadapartner,andsecondly,thatthepartnerhad movedtoSeville. 6http://www.flamenco‐world.com/magazine/about/flamencos_por_japon/ejapo04042011.htm 7http://blog‐flamenco‐world.blogspot.com.es/2011/03/el‐flamenco‐frente‐al‐terremoto‐de.html
48 Anotherissuewiththisprocedureofsamplingisthehugeeffortrequiredtokeep theprocessofrecruitmentflowing.Mostparticipantswerecontactedbyemail,as themajorityofparticipantsfeltmorecomfortablegivinganemailaddressoftheir friendratherthanamobilephone.Forthemajorityofourrespondents,anemail addressseemedlessprivatethanamobilephone.Ingeneral,olderrespondents were more willing to give us the phone number of their friends, sometimes in additiontotheemailaddress. Correspondencebyemailistimeconsumingandcouldalsobeareasonwhythe responseratewaslow.Formostinterviews,anaverageofsixemails was exchanged before the actual interview. In addition, as the first part of the data collectionwasconductedthroughadocumenttheparticipantsreceivedbyemail, thiscreatedafurtherdelayinthesettingupoftheinterview. Despitethelimitationsofthesample,itisimportanttomentionthattheselection ofthesamplewasbasedontheoreticalfoundationswhichallowedustoexamine patternsofmobility,ratherthanprovidegeneralizations.Foreachrespondent,a widearrayofquantitativeandqualitativedatawascollectedthroughwhicharich andsystematicanalysisanddetaileddescriptioncouldbeprovided. 2.3ResearchDesign Dataforthisstudywascollectedintwophasesthroughtwomodes of data collection: email and face‐to‐face interviews. The first phase of data collection consistedofamultiplenamegeneratorcollectedthroughadocument sent by email.Throughthisdocument,weaimedatelicitingthesupportnetworkofthe respondentsandfivenameinterpreters,namely,thefrequencyofcommunication oftheegowithaltersacrossdifferentmediaandthenationality of the alters. Respondentswereaskedspecificallytosendthedocumenttotheresearcherprior totheinterview. Thesecondphaseconsistedofastructuredface‐to‐faceinterview,duringwhich data about five specific areas, namely: media usage, community attachment, personalnetworks,mobilityandsocio‐demographics,wascollected.Thisallowed
49 ustogatherdataabouttwodistincttypesofdyadicrelationships,namelyego‐alter andalter‐alter.Datacollectionduringtheinterviewalsoincludedvisualisationof therespondent’spersonalnetworkthroughVennmaker,amajorreasonwhythe secondphasewasconductedthroughface‐to‐faceinterviews.Vennmaker also facilitatedthecollectionofanothergroupofnameinterpretersofthealteri(place ofresidence,gender,age,relationwithegoandthedurationofthetie).Inthenext twosections,wepresentindetailthemeasuresusedineachandeverysectionof ourdatacollection. 2.3.1Firstphaseofdatacollection Thefirstphaseofdatacollectionconsistedofadocumentwhichwassentbyemail toalltheparticipants.Inthisdocument,participantsweregivenclearinstructions onhowtocompleteamultiplenamegeneratorandwerelaterledtolistavariety ofattributesonthealteritheylisted(seeInstrumentAppendix2). DrawingupthePersonalNetwork Literature from networks theory shows that when defined broadly, a personal networkiscomposedofalltieswithwhomalterhassomesocialcontact.However, whendefinedmorenarrowly,apersonalnetworkcanrefertosubsetofties(Marin &Hampton,2007).Limitingthenumberofpersonalnetworkstoasubsetofalters isatrade‐offbetweenwhatisthemostefficientandachievingthemostaccurate representationofrespondents’personalnetwork,inthiscasetheirsocialsupport network (Bidart & Charbonneau, 2011). The appropriate number ofsubjectsto studypersonalnetworksisamajorconcerninPNA.AsFu(2005)illustratesthere is no clear boundary delineating personal networks except the objective of the studyinquestion.Personalnetworksmayvaryfrom250alters(Killworth1984)to 5000 alters (Killworth, Johnsen, Bernard, Ann Shelley, & McCarty, 1990; Pool & Kochen,1978).Inthisstudy,anetworksizeof30alteriwasselected. Thechoiceof30alterswasbasedonpreviousfindingsandsubsequentdecisions relatedtothedatacollectionandtheanalysis.Primarily,wewantedtodelineatea personalnetworkwhichislargeenoughforstructuralnetworkanalysis. In his articleonthevalidityofapplyingstructuralnetworkanalysis to personal
50 networks,McCarty(2002)illustrateshow30istheoptimalnumberinidentifying clusters,givenresultsfrom60alterididnotdiffersignificantlyincomparisonand theproceduretolist30memberscutsthelengthbymorethanhalf,asegoshaveto compileanadjacencymatrixof435pairsasopposedto1,770pairs.Secondly,we wereinterestedinelicitingthepersonalnetworkwhichprovidessocialsupport. Generally,suchnetworksaremorelikelytobesmaller,ratherthanlarge.Wellman (2007)atteststhatpersonalnetworksstudyingalteristronglyconnectedwithego tend to vary between 2‐30 alteri. Similar approximate number oftiesare presented in the work of Roberts, Dunbar, Pollet & Kuppens (2009) where personal networks are seen as a combination of the inner most layer of the network, also known as supportcliquewhichaveragesaboutfivemembers (Milardo, 1992) and the next layers known as sympathygroupwhich averages around 12‐15 members (Dunbar & Spoors, 1995). Thirdly, we wanted to administer a variety of name interpreters for each of the 30 alteri(11intotal whichequalsto330detailsperrespondent)inafeasibletime.Finally,30alteri seemedtobethelimitinproducinganetworkvisualisationwhichremainslegible andinstructiveduringtheinterview.Toomuchinformationtendstoheavilytire therespondentsbecausefullconcentrationisneededtorememberallthevisual cuestypicallypresentinanetworkvisualisation. The 30 names were elicited through an eight‐item social support instrument, developed and adapted based on theworkbyvariousacademics(Burt, 1984; Fischer, 1982a; Marin & Hampton, 2007; van der Poel, 1993; Wellman, 1979; Wellman&Wortley,1990).Thedifferentnamegeneratorsweregroupedintofive major types of social support, namely emotionalsupport, instrumentalsupport, socialcompanionship, copresenceandother(seeFigure2).Giventhisstudyis about mobility, a specific name generator was added to identifywhichalteri provoketravelfromourrespondents.Asfoundbypreviousscholars,theuseof multiple name generators ensured that the research gathered data about a multidimensional definition of support, hence, obtaining a more accurate representationofthetotalsocialsupportnetwork(Marin&Hampton,2007;van derPoel,1993).
51 Figure2:Socialsupportcategoriesbasedontheeightnamegenerators The alteri were listed according to perceived social support, that is, on the potentialsupportivecontentof a relationasopposed totheactuallysupportive content.Whilethisapproachhasbeencriticisedonthebasisthatunlessaperson neededsupportinthepast,theywouldnotknowpreciselywhopertainstotheir supportive network, as discussed by van der Poel (1993), researchinthisarea demonstratedthatpeoplewithnoexperienceofanykindofsupport still knew whotheycouldturntowhentheyneededsupport.Inhisstudyon students, Barrera(1980)foundthattheuseofareliableprocedureforidentifyingmembers of a very specific social network led to similar network size between what respondentsmentionedasperceivednetworksizeandactualnetworksize. Respondents were instructed to list the names vertically accordingtothefive socialsupportcategoriesmentionedaboveuntiltheyarrivedat30names.Taking intoaccountthatsocialsupportismultiplex,meaningthatonepersoncanprovide emotional support as well as social companionship, we devised our name generatorinawaytocapturesuchmultiplicity.Peopleprovidingmorethanone typeofsupportcouldbelistedhorizontallyinmorethanonesocial support category.Respondentscarriedoutthistaskpriortotheinterviewatthecomfortof theirhome.Anelectronicdocumentwasusedtocollectthenamesofthealteri.As this document was compiled in the absence of the researcher, very precise instructionsonhowtofillthelistofaltersandalsoanexample(seeFigure3)were given.Theinstructionsweretestedwithfivepeopleofdifferentnationalitiesfor
52 whom English was not the first language prior to starting the interviews and changesweremadeaccordingly. Figure3:Namegeneratorexample Followingthelistingofalteri,respondentswereaskedtoprovidespecificdataon six name interpreters, namely, nationality and the frequency ofhowthey communicatedwiththealteriface‐to‐face,bymobile,byemail,bysocialnetwork sites(SNS)andbyVoiceoverInternetProtocol(VoIP).Nameinterpreters are importantinpersonalnetworksastheysupplyadditionalinformationonthealters andtheirrelationwiththerespondent(Burt,1984;McCallister&Fischer,1978). Oncethisdocumentwasreceivedbytheresearcher,generallybyemail,the interviewwassetup.Onaveragedatacollectionfromthetwomodes was separatedbyaweek. Onaverage,18peoplewerementionedmorethanonceineachsocial support network.Participantsfromtheorchestraweretheonesmostlikely to mention socialsupportmultiplexalteri,whileJapaneseflamencoartists were the least likelytomentionsuchalteri. 2.3.2Thesecondphaseofthedatacollection Themainsourceofdataforthisstudywascollectedthroughastructuredface‐to‐ faceinterview.Measuresusedinthisphaseofthedatacollectionaredescribed below:
53 (1) TheInterview:MediaUsage Thesectionontheuseofnewmediaincludedgeneralquestionsonhowmuchtime respondentsspend ondifferentmedia,which typeofmedia theyusedandhow theyusedit. (2) TheInterview:CommunityAttachment Inthesecondsection,wesoughtdataonhowrespondentsexperiencecommunity attachmentwithSeville.Twodistinctmeasureswereused: CommunityAttachment. The following open question was posed to all respondents during the interview: Everybodyfeelsconnectedonewayor anothertothecity.HowwouldyousayyouareconnectedtoSeville?On purpose,wechosenottousethewordcommunity,soastoevaluate whether respondents would mention notions related to community attachment.Resultsfromthisquestionwereexaminedthroughaqualitative contentanalysis,dependingonthefrequencyofcommontermsusedbythe respondents. In terms of order, this question was asked towardsthe beginningoftheinterview,sothatrespondentsarenotinfluencedintheir answersbytheSCI,whichwasconductedlater. SenseofCommunityIndex.Theoriginal12itemSCIdevelopedbyMcMillan andChavis(1986)wasusedasaproxytomeasurebelonginginthehost location through membership, influence, meeting needs and shared emotionalconnection.ThetotalinternalconsistencyoftheSCIinthisstudy isrelativelylow,=.54.ThelowCronbachisdiscussedinChapter 5, wherebyPlaceAttachmentasanalternativemeasurewithahigherinternal consistencyisproposedandusedforouranalysis.Theoverallresultsofthe SCIarepresentedinTable3.
54 Table 3.Psychological SenseofcommunitywithSeville ( N =95) M SD IthinkSevilleisagoodplaceformetolive 1.68 0.62 PeopleinSevilledonotsharethesamevalues* 2.57 0.74 PeopleinSevilleandIwantthesamethingsfromthecit y 2.48 0.58 Icanrecognizemostthepeoplewholiveinmy 2.38 0.90 IfeelathomeinSeville 1.96 0.73 Veryfewpeopleinmyneighbourhoodknowme* 2.57 0.83 Icarewhatmyneighboursandcityresidentsthinkofmy 2.73 0.75 IhavenoinfluenceoverwhatSevilleislike* 2.56 0.76 IfthereisaprobleminSevillepeoplewholiveherecangetit 2.24 0.62 Itisveryimportantformetoliveinmyneighbourhoodin 2.260.76 Peopleinthiscitygenerallydon’tgetalongwitheachother* 2.05 0.77 IexpecttoliveinSevilleforalongtime 2.4 0.9 Allmeasuredona4‐pointscalewhere1=StronglyAgreeand4=StronglyDisagree *Itemswerereverselyscoredbeforeanalysis (3)Interview:PersonalNetworks Thefollowingmeasureswereusedinthenetworksectionoftheinterview: FreehandPersonalNetworkVisualisations: Respondents were asked to represent visuallytheirrelationswiththe30peopletheyhadmentionedpreviouslyinanA4 paperthroughafreestyledrawing/visualisation. Groups:Respondentswereaskedtoidentifythegroupsthatemergedinthevisual representationandtospecifywhethertherespondentsineachgroupresidedin Seville,countryoforiginoranotherlocation. PersonalNetworkMatrix:Inordertobeabletomeasurethestructureof each respondent’snetwork(McCarty,2002),participantswereaskedtoreportonthe relationshiponallpairsofalters.Atiewaspresentifthealterskneweachother, meaning if they would salute each other independent if the respondent was presentornot.Intotal,respondentshadtolist435relations.Thecollectionand analysisofpersonalnetworkstructuraldatahasbeendifficultinthepastbecause usingapaperinstrumenttolistdowntherelationsbetweenthe alters in an adjacencymatrixusingonesandzerosistediousandtimeconsumingandhardly any network programmes were devotedforthispurpose(McCarty,Molina, Aguilera,&Rota,2007).
55 The use of Vennmaker in this study has facilitated the development of the adjacency matrix through a visual map (Figure 4). Visual representation of personal networks to elicit data from respondents is a relativelynewmethod which is still being explored (Cachia & Maya Jariego, 2010; Carrasco, Hogan, Wellman, & Miller, 2006; Hogan, Carrasco, & Wellman, 2007; MayaJariego& Holgado,2005;McCarty,2002;McCartyetal.,2007).TheuseofVennmaker,not onlyallowedustogathermoredatainashortertimeperiod,butalsoprovidedan interactive tool to keep respondents interested, as well as facilitated the identificationoferrors.Attheendofthedatacollection,thevisualisationcanbe exportedintoanadjacencymatrix,whichcanthenbeusedforfurther network analysis. Figure4:ScreenshotfromVennmaker EgoalterCharacteristics: For each alteri, respondents were asked to specify the followingmeasures: Frequencyofcontact: The frequency with which they communicated with alteriintermsofface‐to‐face,mobile,email,SNSandVoIP.Responsescould bemadeinfivecategories:daily,weekly,monthly,yearly/veryrarelyand
56 never. At the aggregate (i.e. network) level, frequentfacetoface communication/mobile/email/SNSandVOIPsumsupthenumberofalteri with whom ego communicated daily and weekly using the respective medium. Typeofrelation.Foreachalter,respondentswereaskedthetypeofrelation theyhavewiththisperson.Responsescouldbemadeinsixcategories: partner/spouse, family, friend, colleague, neighbour and other. At the aggregate level, the variables numberofpartner/familymembers/ friends/colleague/neighbour/otherindicatethenumberofalterilistedper eachcategory. DurationofTie.Lengthoftherelationshipwithalteriwasmeasuredthrough fivecategories.Attheaggregatelevel,thenumberofalteriknowninthepast year/pastfiveyears/tenyears/twentyyears/over20years sums up the numberofalterilistedineachcategory. Location:Respondentswereaskedtospecifytheresidinglocationoftheir alteri.Attheaggregatelevel,thenumberofalteriinSeville/countryof origin/othersumsupthenumberofalterimentionedperlocation. Nationality:ThisvariablemeasuresthenumberofalteriwhoareSpanish, fromcountryoforiginandothernationalities.Attheaggregate level,the numberofSpanish/compatriots/otherssums up the number of alteri mentionedpernationality. Thegenericresultsoftheego‐altercharacteristicsarepresentedinTable4and Table5.
57 Table 4.Sociodemographiccharacteristicsofalteri ( N =2,850) f% TypeofRelation Partner 55 1.9 Family 527 18.1 Friend 1866 64.1 Colleague 193 6.6 Neighbour 59 2 Other 150 5.2 Durationofrelation Inthepastyear 644 22.1 Inthepast5years 711 24.4 Inthepast10years 521 17.9 Inthepast20years 430 14.8 Allmylife/Over20years 544 18.7 Location Seville 1206 41.4 CountryofOrigin 1072 36.8 Other 482 16.6 Nationality Spanish 693 23.8 Compatriot 1483 51 Other 644 22.1 Inouranalysis,wedistinguishbetweensixtypesofpersonalnetworkmembers: thosewholiveinSeville(locals),thosewhoSpanish,thosewholiveincountryof origin,thosewhosharethesamenationalityofrespondents(compatriots),those wholiveinalocationwhichisnotSevilleandneithercountryoforiginandthose wholiveinSevillebutareneitherSpanishnorfromthesamecountry as the respondent(transnationals). Table 5. FrequencyofContactwithAlteri ( N =2850) M SD Range Face‐to‐Face 2.9 1.9 1‐5 Mobile 3.4 1.2 1‐5 Email 3.9 1.1 1‐5 SNS 3.8 1 1.5 VOIP 4.4 1 1.5 All measured on a 5‐point scale where 1= daily, 2=weekly, 3=monthly, 4=yearly/veryrarely,5=never
64 Wortley,1990).Inthecontextofmobility,theseinstrumentshardlyevertakeinto accounttheaspectoftravel,theneedforco‐presenceasawayofsustaindistant support. This chapter examines the type of perceived support listed by our population (N=95)andwhichtypeofcontactisusedtosustainthedifferentsourcesofsocial support. We also explore the role of travel as another form ofcontact, through whichrespondentsstayintouchwithsocialties.Basedonthepotentialsourcesof support (N=2,850), a social support taxonomy is created classifying alteri into specialized,intermediateorpolyvalentsupportproviders.Towardstheend, the study also utilizes a typology derived in a unique clustering procedure through whichfourtypesofsocialsupporttypesareidentified:(1)Diversified Social Companionship,(2)RecentSocialisingties,(3)Polyvalentsupportbyoldfriends, and(4)Co‐presencesupport.Bothcategorizationsareusedtoexaminehowthe typeofsocialsupportisrelatedtonetworkcharacteristicsandthetypeofmobility. 3.2.1Definingandmeasuringsocialsupport Inpsychology thefocus onsocialsupportemergedinthe60s,asan alternative approachtostudymentalhealth,shiftingthefocusfromtheindividual to the community(Agneessensetal.,2002;Levine&Perkins,1997;MartinezGarciaetal., 2001). Scientific interest in social support grew more thoroughly in the 70s as moreresearchshowedthatpeoplefacingemotionalproblemsandinmomentof crisis resort primarily to their intimate ties, rather than to professional mental health services (Caplan, 1974; Cassel, 1974; Cobb, 1976; Martinez Garcia et al., 2001).Hitherto,researchonsocialsupportwaslimitedduetoalackofareliable, generalandconvenientindexofsocialsupport(Barrera,1980;I.G.Sarasonetal., 1983). This resulted in a wide array of studies focused on developing new approachestoassesssocialsupportnetworks. Duringthepastdecades,differentsocialsupportinstrumentshavebeendeveloped tomeasuresocialsupport.Findingsfromrecentstudiesshowthatstudyingsocial supportasaone‐dimensionalphenomenonhasvariouslimitations.Differenttypes ofrelationshipsmaybestowavarietyofsocialsupport(Agneessensetal.,2002;
65 Walker et al., 1993). In studying how alteri characteristics influenced social support,researchersfoundthattheego‐alterrelationhadaninfluenceonthetype ofsocialsupportprovided(Schweizer,Schnegg,&Berzborn,1998). Kin were mainlyprovidersofemotionalandeconomicsupport,friendsactmoreassocial companions and neighbours were less significant but lend instrumental help. SimilarfindingswerefoundbyFischer(1982a)inhisanalysisonhowpersonal communitiesarelinkedtotheresidentialcommunities.Friendsweremorelikely toprovidecompanionship,relativesandneighboursprovidedpracticalhelpand immediaterelativesandfriendsgavecounseling. Studiesonsocialsupporthavealsolookedintohowthesamepersoncanprovide morethanonetypeofsupport,whatintheliteratureisreferredtoasmultiplixity. Tiesinapersonalnetworktendtobeamixtureofspecialized–providersofone typeofsupport–ormultiplex–providersofdifferenttypesofsupport(Hennig, 2007). Therearedistinctmethodsofhowthelistofsocialsupportproviders may be elaborated (Agneessens et al., 2002; Bidart & Charbonneau, 2011; Marin & Hampton, 2007; McCallister & Fischer, 1978; van der Poel, 1993). In social sciences, social support is often studied through an ego‐centered perspective, where respondents (ego) are asked about the availability of different kinds of supportfromalistofpeople(alteri).Anamegenerator,supplemented by additionalattributesofthealteri,asforinstance,thetypeofrelationthey have withego,isoneofthemostusedtoolstocreatealistofsocialsupportproviders. Tieevaluation,consistinginidentifyingwhetheraspecificrelationexistsbetween thealteri,asforinstance,whetheralteriknoweachother,enablesresearchersto study,notonlythecompositionbutalsothestructureofthenetwork, using networkanalysis. Inresponsetocritiquesuggestingthatthesocialsupportwasnot a reliable measure,aconceptualframeworkthatspecifiedwhyanalteriqualified as a networkmemberbasedonaseriesofspecificquestionwasdeveloped(Barrera,
66 1980; Jones & Fischer, 1978). The major issue at stake at present is that researcherscontinuetolookformoreprecisequestionstomeasuresocialsupport andwhichprovidedatawhichcouldbecomparedacrossdifferentstudies. 3.2.2Mobilityandsocialsupport Internationaldisplacementhasimportantrepercussionsonthestructureofsocial supportnetworks.Mobilitymeanschange,adisruptiontoone´spersonalnetwork (Sonn,2002)andthedevelopmentofnewdemandsforsupportinanunfamiliar environment(Litwin,1995).Aresidentialmovecanleadtostressfulsituationsand asfoundbyvariousstudiesbasedonthebufferingmodel,social support can protectapersonfromhealthrelatedproblems,suchasloweringoftheimmune system. The simple knowledge that you have a social support network at your disposalwasfoundtobepositivelyrelatedtobolsterone’sperceived ability to copewithstressfulsituations(Cohen&Wills,1985). Therelationshipbetweensocialsupportandtheprocessofmigratoryintegration hasbeenexploredinvariousstudies(Aroian,1992;Berry,1997;Clarke&Jensen, 1997; Leslie, 1992; Lubbers et al., 2010; Lynam, 1985; Martinez Garcia et al., 2001).InastudyaboutPolishimmigrantsinAmerica,Aroian(1992)foundthat compatriotswereamajorsourceofsupportparticularlyduringearlyresettlement. Adecreaseinthesizeofthesupportnetworkinthefirstfewmonthsofresidence following international displacement is likely to be observed. Research with AfricanandLatin‐AmericanimmigrantsinSpainhighlightedtwobasicstrategies undertaken by respondentsin rebuilding the personal networks, namely family reunificationandtheincorporationofhostindividuals,bothofwhichhaveclear consequencesonthesupportnetwork(MayaJariego,2006).Inasurveywith710 ChinesemigrantsinSingapore,Chen&Choi(2011)observedthatrecentlyarrived migrantsaremorelikelytorelyoncomputer‐mediatedsocialsupport to supplementthelackofofflinesocialsupport.However,astimepassesandtheir localnetworksgrow,onlinesupportismorelikelytobeinformational. Mobility has an ambivalent nature: on the one hand, spatial dispersion from friendsandfamilyisseenasanobstacletothenurturingofsocialties,butonthe
67 other hand, mobility to another space also brings about opportunities for establishingnewsocialtiesandjoiningnewgroupsoutsideone’slocalcommunity (Viry,2012).Increasingly,inhabitantsofurbancitiessustainmeaningfulactiveties outsidetheirimmediatelocalityashasbeendemonstratedbythestudiescarried out in East York, Ontario (Wellman, Carrington, & Hall, 1988) and in London (Albrow,1997).Whenspecificresourcesarenotavailable,especiallyinperiodsof social change, as demonstrated by the Media System Dependency theory (Ball‐ Rokeach&DeFleur,1976),peoplewillturntomediasystemstogetthem(Chen& Choi,2011).Arecentlyarrivedmigrantisunlikelytohaveasufficientextensive network,forinstance,tolookforaplacetorent.Consequently,theinternet becomesanalternativesourceofsocialsupport.Naturally,tangibleassistanceor physical companionship is limited through new media, however, tangibleitems whichcanbeprovidedintheformofsoftwareorcompanionshipthroughplaying anonlinegame,forinstance,werealsofoundtobepresentinthestudybyChen& Choi(2011). Newformsofportabilityandconnectivity,haveenablednewwaysofhowpeople reconfiguresocialnetworks,bydisconnectingandreconnectingthemincomplex ways(Larsen,Urry,&Axhaussen,2006).Peopletravel,relocateandmigrateand stillremainclosetoemotionalties(Walkeretal.,1993).Thismarksashiftfrom traditional groups in one location (little boxes) where membership to different social groups was strong to overlapping person‐to‐person connectivity (networkedindividualism),wheretiesarespatiallydispersedand do not necessarilyoverlap(Wellman,2002).Inhisseminalworkinthe80sonpersonal networksin towns and cities, Fischerforewarned thattheessentialconcernfor studentsofcommunityshouldbesocialrelations:“whatkindsofsocialrelations peoplehave,withwhatconsequences”(1982a,p.2). Networksofmobileindividualstendtobemoreindividualized,lessoverlapping and more sparse, in comparison to personal networks of non‐mobile people (Larsen,Urry,&Axhaussen,2006;Urry,2003;Wellman,1999a;Wellman,Tanabe, van den Besselaar, & Ishida, 2002; Wittel, 2001). Recent literature show an emerging interest in examining geographical mobility through informal and
68 smaller‐scale transnational networks between mobile individualsbasedon interpersonal connections, often as expressed through personal networks (Carrascoetal.,2008;Kennedy,2004;Larsen,Urry,&Axhaussen,2006;Lubberset al.,2010;Lubbersetal.,2007;MartinezGarciaetal.,2001;MayaJariego,2006; Mok& Wellman,2007;Molina, Fernandez,&Llopis,2007). Theuseofpersonal networkstostudysocialsupportisusefulasitallowsresearcherstoidentifysocial support,notmerelybasedonproximity,butalsoondistantties(Castells,2000; Hampton et al., 2009; Hoete, 2004; Larsen, Urry, & Axhausen, 2006; Wellman, 1996). Paradoxically,althoughfarawayemotionaltieshaveneverbeensoclose,people travelmorethanever,spendingconsiderablyamountofmoneyandtimeonthe roadtomeetphysicallywiththeirfamilyandfriends.Recentresearchshowsthat despiteadvancedcommunicationstechnology,distancestillmatters,(Axhausen& Frei,2008).Atieremainsactivethroughoccasionedcopresence(Larsen,Urry,& Axhaussen,2006)andmeetingness(Urry,2003)anditseemssuchpresencecannot besupplantedbyvirtualpresenceorcommunicationasyet. InherstudyonmigrantsofPakistanioriginlivingintheNorthofEngland,Mason (2004)foundthatalltherespondentsclaimedtotraveltoPakistanatleastoncea year.Auniversalassumptionthatvisitswouldorshouldbearegularoccurrence wasobserved.Thiscompulsiontoproximity(Larsen,Urry,&Axhaussen,2006)is importantformobilityresearchduetothesocialandemotionalsignificance.While awidearrayofliteraturehasfocusedonthenotionofthenetworkedindividualism (Wellmanetal.,2002),lessresearchhastakenintoaccounttheroleoftraveland howitinfluencestheproductionandstabilizationofsocialsupportnetworks. Inthisarticle,weexaminethesocialsupportnetworksofmobileindividualsliving inSeville.Weexploredifferenttypologiesofsocialsupportfrommultiplename generators,throughwhichwestudynetworkcomposition,mobilitypatternsand differentmodesofcommunication.Specifically,westudydistincttypesofsupport; howtheyarekeptatadistance;whatsortsofrelationsprovidedthem;and different profiles of mobile individuals. Given the mobile nature of our
69 respondents,wewerealsointerestedinexploringhowtheroleoftraveltosustain farawaytieswasembeddedinthesocialsupportstructureofourrespondents. 3.3Method 3.3.1Participants ThetargetpopulationofthisstudywasmobileindividualslivinginSeville,fora minimumperiodofsixmonths.Respondentswereselectedthroughasnow‐ball sampling,utilisingfourcommunitiesasthesamplingframe.Thefourcommunities were Japanese Flamenco artists, Erasmus students, partners of researchers working for the Institute for Prospective Technological Studies(IPTS),an internationalofficepartoftheEuropeanCommissionandmusicians from the Symphonic Orchestra of Seville (ROSS). A detailed descriptive analysis of the participantsandthesamplingusedinthisstudyispresentedinChapter2. 3.3.2Procedure Aseriesofquestionsdesignedtoelicitthesocialsupportnetworkofrespondents wasused.Departingfromthepremisethatsocialsupportisnotauni‐dimensional construct,thetechniqueweusedisanadoptionofafivenamegeneratorbasedon previous work in this area (Barrera, 1980; Fischer, 1982b; Marin & Hampton, 2007;vanderPoel,1993).Thegeneratorswereamendedaccordingtothescopeof thiswork,soastoensurethatthequestionnaireiskeptshort,tothepointandto facilitate understanding. The decision to use a broad, multidimensional view of social support is based on the findings by Marin & Hampton (2007), which demonstrates that multiple generators are more reliable than single generators when measuring size, density and measures of network compositions. This has enabledustoobtainmorespecificdatawhichwouldnothavebeenpossible,ifwe wereutilisingonesocialsupportnamegenerator.Thenamegeneratorwehave adopted consists of four dimensions, namelyemotional,instrumental,socialising and copresenceand other,asafifthcategory,wherebyrespondentswere
70 instructedtomentionotherimportantpeoplewhotheymayhavenotmentioned yet,iftheyhavenotreached30names,30beingthecut‐offnumberrequested.10 Alteriwhoprovidedmorethanonetypeofsupportcouldbelisted in different typesofsupport.Multiplexitywasusedinthisstudytogaugethestrengthofthe relationbetweenegoandalteri. Giventhisworkisaboutpeoplelivingabroad,anewdimensionwasaddedwhich webelieveisimportantwhenstudyingsocialsupportofindividuals with such profile.Asdiscussedalreadyrecentstudieshaveshowninavarietyofwaysthat socialsupportisnotnecessarilyembeddedinthelocationwhereyoulive.Thisled ustobelievethatpeoplewhoarealsosourcesofsocialsupportbutlivefaraway fromtherespondentsarealsoimportanttoincludeinthesocialsupportnetwork. Notonlydothesepeopleprovidedistant socialsupport,buttheyalso trigger a greatproportionofthemobilitywithinourpopulation.Althoughwithinexisting socialsupportanalysisframework,distanttiesalsotendtobe identified (especially,ifalteriattributes,suchas,frequencyofcontactandlocationareused), wewereinterestedtofindwhetherthereareanyalteriwhoaresosignificantin one’s network, that although they might not provide frequent emotional, instrumental or socializing support, they propel participants to travel to meet thesealteri.Accordingly,wehaveaddedanewsocialsupportcategory,whichwe termcopresence,basedontheworkofLarsenetal.(2006). Respondentswerealsoaskedtoevaluatethetiesbetweenallthemembersandto listanumberofattributesrelatedtothealteri.Thepersonalnetworkselicitedin this work are produced by self‐reporting methods and should be regarded as perceivedsocialsupportnetwork,ratherthanactualsupportnetwork. Inthisarticle,twosimultaneousanalyseswerecarriedout.Inthefirstsectionwe reportresultsfromthe95respondents.Inthesecondsection,wereportresults fromtherespondents’alteriwhichamountedtoatotalof2,850alteri. 10Thequestionsusedinthemultiple‐namegeneratorandthemajorreasonswhyweoptedfor30 participantsaredescribedinChapter2.
71 Thevariableschosentorepresentthesocialsupportnetworkcompositionreflect the factors identified in previous research as key components of personal networksingeneral(typeanddurationofrelationwithalteri)andthoseofmobile individuals (location and nationality of alteri listed). Mobility patterns variables include the type of community respondents belong to, duration of residence, employmentstatus,timeplannedtostayinlocationofresidence. Mode of communicationwasmeasuredalongthetypeofmediausedandthefrequency. 3.4Results 3.4.1CrossSectionAnalysisofdifferenttypesofSocialSupport Thefirstpartoftheanalysisprovidesadescriptiveanalysisofthefourtypesof socialsupportaslistedbyparticipants.InFigure5,wecanseethenamegenerator ofafictionalrespondent.Forthispartoftheanalysis,Maria,Paul(B),Martinand Alexwereexaminedasalteriprovidingemotionalsupport;Karen,Almudenaand Natashaasinstrumentalsupportproviders;andMartin,SimonandPaul(T),Alex andSoniaasthealteriprovidingsocialisingsupport.MartinandAlexwerealso studiedasmultiplexsocialsupportalteri. Figure5:ExampleoftheInstrument Incomparingthetypeofsocialsupportalterilistedbyrespondentsanumberof trendsappearTable7.
72 Table 7: TypeofSupportacrossNetworkCharacteristics(N=2,850) Emotional Instrumental Social Companionship Copresence Other f % f % f % f % f % Location ofAlteri Seville 364 35,7 326 45,0 887 52,6 110 13,7 104 39,2 CountryofOrigin 478 46,9 284 39,2 514 30,5 502 62,5 105 39,6 Other 178 17,5 114 15,7 286 17,0 191 23,8 56 21,1 Total 1020 100 724 100 1687 100 803 100 265 100 Nationalit y Spanish 210 20,1 198 26,4 455 26,3 100 12,3 89 33,3 Compatriot 647 61,9 399 53,3 823 47,6 585 72,2 120 44,9 Other 189 18,1 152 20,3 452 26,1 125 15,4 58 21,7 Total 1046 100 749 100 1730 100 810 100 267 100 TypeofRelation Partner 50 4.7 37 4.9 47 2.7 11 1.3 0 0 Family 270 25.6 205 26.9 166 9.5 292 35.7 40 15 Friend 688 65.3 433 56.9 1343 76.6 450 55.1 139 52.1 Colleague 30 2.8 36 4.7 111 6.3 38 4.7 28 10.5 Neighbour ‐ ‐ 20 2.6 27 1.5 6 0.7 14 5.2 Other 15 1.4 30 3.9 60 3.4 20 2.4 46 17.2 DurationofTie Inthepastyear 124 11,8 109 14,3 483 27,5 76 9,3 48 18,0 Inthepast5years 223 22,1 188 24,7 471 26,9 139 17,0 78 29,2 Inthepast10years 201 19,1 147 19,3 359 20,5 135 16,5 46 17,2 Inthepast20years 222 21,1 132 17,3 273 15,6 160 19,6 40 15,0 Allmylife/Over20years 274 26,0 185 24,3 168 9,6 307 37,6 55 20,6 EmotionalSupport:Almosthalfofthealterilistedaspotentialprovidersof emotional support live in country of origin. Face‐to‐face interaction with these alteritakesplaceonayearlybasis.Face‐to‐facecommunication tends to be strongly related to short distances (Mok et al., 2010). Distance is overcome by substitutingface‐to‐facecommunicationwithothermodalitiesofcommunication. Respondents communicate frequently with alteri providing emotional support mainly through mobile, followed by SNS. The majority of alteri providing emotionalsupportwerefriends.Familymemberswerealsomentionedassources ofemotionalsupportbuttooursurpriseonamuchlowerdegree.Providersof emotional support tend to be alteri respondents have known for a longer time.
73 Interestingly,participantswhohadchildrentendedtolistlessemotionalsupport providers Instrumentalsupport:Respondentsderiveinstrumentalsupportfrompeopleliving inSevilleandincountryoforiginandfromalteritheyhavegottoknowrather recently,mainlyinthepastyearorinthepastfiveyears.Themajoritytendtobe compatriots. Frequent communication with these alteri providing instrumental supportwasmainlyface‐to‐faceorbymobile.Inthisstudy,neighboursseemtobe mainlyprovidersofinstrumentalsupport. Socialcompanionshipsupport:Localalteriwerelistedasthemajorprovidersof socialcompanionship(53%).Respondentsderivedsocialcompanionshipsupport mainlyfromcompatriots,friendsandsocialtiestheyhavegotto know rather recently. Frequent contact with these alteri was mostly through face‐to‐face communication. CopresenceSupport: Respondents claimed to visit mostly friends, followed by family.Ahighproportionlivedincountryoftheoriginoftherespondent,were compatriotsandarepeopletheyhaveknownformorethan20yearsoralltheir lives. Therelationbetweentheprovisionofdifferenttypesofsupportissummarisedin Figure9,atwo‐modenetworksbasedonalter‐by‐typeofsupportmatrix,inwhich xij=1iftheithalterprovidedthejthsupport,andxlj=0otherwise.Hence,thevalue maybeinterpretedasanindexofmultiplesupportprovidedbythesamealter. A good proportion of alteri providing emotional support were also listed as potential providers of social companionship, instrumental and co‐presence support.Thestrongestrelationisbetweenalteriprovidingemotionalsupportand alteri providing social companionship. Of particular interest to our study is the strongrelationbetweenalteriprovidingemotionalsupportandalterilistedinthe co‐presence support. Seemingly, the population in this study relies on a good proportionofemotionalsupportatadistance.
80 providingsolelysocialsupport(M=8.92);co‐presencesupport(M=3.15)anda combinationofemotionalandsocialsupport(M=2.52)(Table10). Table10:Meanrankingofthe15typesofsupport TypeofSupportAlteri M SocialCompanionship 8.92 Copresence 3.15 EmotionalandSocial 2.52 Emotional 1.95 Emotional,InstrumentalandSocial 1.89 Instrumental&Social 1.47 Emot,Instr,SocialandTravel 1.47 Instrumental 1.35 Animportantissuewithregardstoclusteranalysisisthedecisionregardinghow manyclusters theresearchshouldelicit fromthedata(Mooi&Sarstedt, 2011). Giveninourdata,wedidnotknowtheexactnumberofclusters, we have consideredcarefullythetrade‐offbetweenrequestingfewclustersbutatthesame time, enough clusters which will allow us to identify different social support profilesoftherespondents.Thetechniquegenerallyadoptedinvariablyinvolves experimentingwithdifferentclustersolutionsuntilthegroupsderivedrepresent socialsupportnetworktheory(Litwin,1997).Forthiswork,four clusterswere deemedthemostaptindefiningdifferenttypologiesofsocialsupport. Table11presentstheclustersderivedbasedonthethreemaintypesofsupport,as listedabove.Thefiguresshowninthetablearethefinalclustercentres,oneach criterionvariableforeachofthederivedclusters.Eachcluster represents a differenttypeofrespondentbasedonthedifferenttypesofalterilistedpereach typeofsupport.Thefirstclusterincludes50cases(53%ofoursample),thesecond 21cases(22%),thethird9cases(10%)andthefourth15cases(16%).
81 Table 11: ClustercentresforTypeofSupport ( N =95) Cluster1 (n=50) Cluster2 (n=21) Cluster3 (n=9) Cluster4 (n=15) TypeofSupport Socialcompanionship 8 16 1 5 Co‐presence 2 2 0 10 Emotional&SocialCompanionship 2 2 7 2 A descriptive analysis of the different clusters in relation tothenetwork composition variables is presented in Table 12. Frequencies and analysis of varianceofsocio‐demographicvariables(TableA2),mobilityvariables(TableA3), and the type and frequency of communication usedto communicatewithalteri (TableA4)arepresentedinAppendix1.Thetableslistthemeanvariablescorefor eachclusterandtheinterclusterdifferencesand theirsignificance.All variables usedweretestedfornormality.One‐wayAnova(Schefféintergroupmeans)was usedfornormallydistributedvariables(Fscores)andtheKruskal‐Wallistest(H scores)wasusedforthenon‐parametricvariables.Forthenon‐parametric variables,follow‐upteststoevaluatepairwisedifferencesamongthefourclusters controlling for Type I error across tests by using the Bonferroni approach was used.AdescriptionofeachclusterispresentedinTable13. Cluster 1 (53%) is mainly characterized by social companionship support. Copresenceandcombinedsupport(alteriprovidingbothemotionaland social companionship) are also available but moderate. We refer to this cluster as DiversifiedSocialCompanionship.Respondentsinthisclusterweremorelikelyto mention an intermediate number of Spanish alteri and family members. The durationofrelationbetweenrespondentsandalteriinthisclusterisdiversified, withaslightlyhighermeanofalteriknowninrecentyears.Participantsweremore likelytolistahighnumberofalteriwithwhomtheycommunicateface‐to‐faceona weeklybasis. Cluster2(22%)issimilartosomedegreetothepreviouscluster,inthatitreflects a high social companionship and minimal levels of co‐presence and combined emotionalandsocialcompanionshipssupport.However,itisdifferentandunique inthatitcontainsthehighestfrequencyofsocialcompanionshipbyasubstantial
82 Table 12: Means,OnewayANOVA&KruskalWallisvarianceofnetworkcomposition characteristicspercluster(N=95) Cluster1Cluster2Cluster3Cluster4FH M SD M SD M SD M SD N ofalteriper Seville 13,2 6,16 12,1 7,31 12,2 6,70 14,5 5,0 .450 Countryof 10,8 5,99 13,6 5,60 13,6 6,70 12,0 4,81 1,416 Other 6,0 5,67 4,4 4,87 4,2 4,24 3,47 2,75 1,59 N ofalteriby Spanish 7,8 6,19 4,6 5,52 7,8 6,94 9,9 4,48 48,33**** Compatriot 15 7,18 17,8 7,82 16,8 7,86 14,5 4,19 1,001 Other 7,0 4,07 7,6 5,78 5,4 4,93 5,6 3,81 2,86* N ofalteriper Inthepastyear 6,5 5,80 10,7 7,73 3,2 3,563 3,4 3,94 46,753**** inthepastfive 8 4,58 7,3 4,92 6,7 5,70 6,6 5,71 1.77 Inthepastten 5,7 4,03 4,1 3,40 7,2 3,15 5,6 4,45 9,437* Inthepast 4,4 4,30 3,1 3,65 8,2 6,40 4,93 4,85 36,864*** Allmylife/More 5,4 3,17 4,4 4,98 4,7 1,94 9,4 5,17 14.90*** N ofalteriper Partner 0,5 ,51 0,6 ,51 0,4 ,53 0,9 ,26 16,141*** Noof 5,8 2,82 4,2 2,84 4,1 2,47 7,9 4,41 12.19** Noof 19,8 4,76 20,6 5,87 22,3 3,91 16,1 5,47 9.16* No.ofalters 2,0 3,45 2,3 2,76 1,3 3,04 2,5 2,33 9,390* No.ofalters 0,4 1,05 ,8 1,67 ,3 0,50 1,4 2,23 10,085* Noofalters 1,5 2,65 1,3 3,17 1,4 1,81 1,9 1,80 11,920** *p<0,05;**p<0,01;***p<0,005;****p<0,001 difference, the highest number of alteri from other nationalitiesandthelowest number of Spanish alteri. Two‐thirds (76%) of respondents in this cluster have livedinSevilleforlessthanayear.TheproportionofSpanishalteriinthesupport networkispositivelyrelatedwiththelengthofresidenceoftherespondents,χ2(8, N=95) = 49.64, p=.00.Respondents(100%)whohadlivedlessthanayearin SevillehadlessthaneightSpanishalteriintheirnetwork. Participantswiththisprofileweremorelikelytomentionalteritheyhavegotto knowinthepastyear,reflectingasupportnetworkbasedonrelatively Recent SocialisingTiesprovidingsocialcompanionship.Thisclusteralsodiffersbythelow
83 numberoffamilymembersandthehighnumberoffriends.Intermsofrelational mobilecommunity, this cluster is dominated by a high presence of Erasmus students. When it comes to communication, respondents in this cluster differed significantly from other clusters mainly in frequent face‐to‐face communication andcommunicationbySNS.Participantswiththisprofilelistedthehighestnumber ofalteriwithwhomtheymeetface‐to‐faceweekly(M=7.3,SD=4.78) and the highest number of alteri with whom they communicated through SNS (M=8.0, SD=6.30)alsoonaweeklybasis. Cluster3(10%)isasmallclustermainlyconsistingofrespondentswithmultiplex supportalteri.Theserespondentsdidnotmentionanyco‐presencesupportalteri andhavefewalteriprovidingsolelysocialcompanionship.ListingofSpanishalteri was intermediate, while the number of other foreigners in thesepersonal networkswasthelowest.Alteriprovidingthistypeofsupportweremorelikelyto haveknowntherespondentsforthepast10and20years.Asacluster it is characterisedbyPolyvalentSupportbyOldFriends.Thisclusteralsostandsoutfor thelowestrankingoffamilymembersandthehighestrankingof friends. Colleaguesandneighbourswerealsoattheirminimal.Thisclusterisdominatedby orchestramusicians.Whenitcomestomedia,weobserveastatisticallysignificant difference in the high number ofalteri mentioned with whom respondents met rarelyface‐to‐face. Cluster 4 (16%) is mainly characterized by the high frequency of Copresence Support.Thisprofileisuniqueinbeingtheclusterwiththehighestnumberofties forwhichrespondentstraveltomeet.Thesesocialsupportnetworkstendtohave astrongbaseinthelocationwheretheylive,ascanbeobservedbythehighest listing of Spanish alteri, and yet, travel to meet with specificpeoplewhoare important.Respondentswiththisprofilelistedmorefamilymembersandtiesthey haveknownforalongtime.TheyweremorelikelytofromtheFlamencoandthe IPTScommunity.
84 Table 13. CharacteristicsoftheSocialSupportProfiles Description NetworkComposition,MobilityPatternsand Communication Diversified Social Companionship Mainlycharacterized bysocial companionship support. Lowprovisionofcopresenceanda combinationof emotionalandsocial companionship IntermediatenumberofSpanishalteri. Relationbetweenrespondentandalteriis diversified,withaslightlyhighermeanofalteriin recentyears. Mediumnumberoffamilymembers Highnumberofalterilistedinweeklyface‐to‐face communication Recent SocialisingTies Highestfrequencyof socialcompanionship Lowlevelsofcopresenceand emotionalandsocial companionship support. LowestnumberofSpanishalteri Highestmentioningofalterifromother nationalities Supportismainlyderivedfromrecentlyknown alteri Lowmentioningoffamilymembers Majorityofrespondentsinthisclusterhavelived inSevilleforalessthanayearandtendtobe Erasmusstudents Highestlistingofalteriwithwhomtheymet frequentlyface‐to‐faceandcommunicated throughSNS Polyvalent supportbyold friends Highestmentioning ofcombined emotionalandsocial companionship support. Noco‐presence supportalteri Lowpresenceof alterisolelyproviding social companionship. RelativehighnumberofSpanishalteri Haveknowntherespondentsforalongperiodof time Lowestrankingoffamilymembers,neighbours andcolleagues Highestrankingoffriends. Majoritybelongtotheorchestracommunity Listedthesamenumber(anaverageof5)with whomtheycommunicateonaweeklybasisface‐ to‐faceandthroughSNS Copresence Support Mainlycharacterized bydiversifiedsocial supportalteri. Highestmentioning ofco‐presence supportalteri HighestnumberofSpanishalteri Lowlistingofalterilivinginotherlocations Supportismainlyderivedfromalteriwhothe respondentshaveknownforover20yearsorall theirlives. Highestproportionoffamilymembers,partner, neighbours,colleaguesandothers. Highestmentioningofalteriwithwhom respondentrarelycommunicatedbymobileand lowestnumberofalteriwithwhomrespondents communicatedbySNSonaweeklybasis.
85 However,statisticaldifferencewiththeotherclusterswasmainlyaresultoflow presenceofErasmusstudents.Ingeneral,theserespondentsweregenerallythe oneswhocommunicatetheleastfrequentlyacrossallthedifferentmedia. Weobservethatthefourclustersseemtobeassociatedwithdifferenttypesof mobilityinherenttothefourrelationalmobilitycommunities.IfwelookatFigure8, wecanobservethattheclustersdominatedbysocialcompanionshipsupport,that isCluster1andCluster2arecharacterisedbyrespondentswhoareinSevillefora shortstay(Erasmus)or intransit toanotherlocationinthenearfuture(IPTS). Multiplexsupportseemstobeassociatedwithrespondentswhoaremorelikelyto be settled in Seville (orchestra). And co‐presence support is more typical of respondentswhohavelivedinSevilleforamediumperiod,inwhichtheyhave eithersettledinthepastfewyearsortheywillbeenhereforacoupleofyearsand aremorelikelytoleavesoon(IPTSandFlamenco)andwhereshortmobilityof comingandgoingishighlypresent. Figure8:SocialSupportClusters 3.5Discussion Thisarticleexploredprimarilythetypeofsocialsupportparticipantsofthisstudy relyonandsoughttounderstandhowthetypeofsupportisrelatedtonetwork composition of alteri, communication with alteri and mobility patterns of the respondents.Italsoexamineddifferenttechniquesforconstructingtypologiesof
86 social support from multiple name generators. Results from the three distinct typologiesshowthatwhilesomefindingsweregeneral,otherswerespecifictothe typeoftypologyextracted. Thethesisthatmobilityishavinganegativeimpactonsocialrelationshasbeen explored. Across the three types of typologies we found that a significant proportion of our respondents’ social support is kept at a distance. This is congruentwithvariousstudieswhichhavealsochallengedtheabove thesis showingthattheprovisionofsupportisnotlocationbound,onthecontraryitmay wellbekeptatdistance(Albrow,1997;Fennell,1997;Horrigan,2001;Licoppe, 2004;Mok&Wellman,2007;Moketal.,2010;Wellman,1996,2002).. AsdiscussedbyFischer(1982a),thereisnothingmysticalaboutproximity:nearby tiesareindispensibleinprovidingimmediatesupport,whiledistanttiesprovide support when proximity is less critical, often in situation involving the most intimacy,sacrificeandfaith.Perhaps,thedifferencewenoteinthisstudyisthat distanttiesarenotalllatent,asobservedbyFischerinhisstudy.Thefrequent communication by mobile and SNS, especially with emotional distant ties is an evidenceof such activerelations.Itispossiblethat theseemotionaldistantties beforethemobilitytookplaceprovidedavarietyofsocialsupportandnowdueto distanceremainimportantinthepersonalnetworkintermsofthetypeofsupport (emotional)ratherthanintermsofstrength(multiplexsupport). The low frequency of face‐to‐face communication across our respondents is anotherindicationthatwithinourpopulationsocialsupportiswidespreadonnot locationbound.Whilemeetingface‐to‐faceisimportant,aswehaveobservedby thehighnumberofalterilistedunderco‐presencesupport,thefrequencyofwhen face‐to‐facecommunicationtakesplaceseemstotakealowerpriority. New communicationsmedia,notonlyproducesacontinuumoftherelationtypicalof oldermedia,wherebythehighcostoflongdistancephonecall,forinstanceonly allowedpeopletoexchangequicknews,butalsoallowspausedtype of communication,inwhicheverydayfeelingsandimmediateemotionscanbetalked aboutinreal‐time(Licoppe,2004).
87 As people are more likely to live away from their family, friendships constitute importantsocialbondspreviousassociatedwiththefamily(Bellotti,2008;Pahl, 2001).Friendscomprisedmorethanhalfofthepersonalnetworkofrespondents, confirmingsimilarresultsinpreviousstudies(Fischer,1982a;Wellman&Frank, 2001).Fischer(2011)attributesapartialdecreaseofrelativestolatemarriages, lessmarriagesanddivorce.Whencomparingresultsfrom1970sto2000s,Fischer (2011)foundthatfamiliesweresmallerduetomoresingle‐parentfamiliesand moreelderlylivingindependently.Itwasalsointerestingthatrespondentsinthis studyclaimedtotravelmosttovisitfriends,followedbyfamily.Keepingfriendsat adistance,requireaneffortwhichisnotnecessaryforstayingintouchwithfamily. Previousresearchhasdemonstratedthatqualifiedpeoplearemorelikelytorely onfriends,asopposedtoloweducatedpeoplewhoaremorelikely to obtain support from family (Kennedy, 2004). The highly skilled nature of respondents couldbeoneofthereasonswhyfriendsplaysuchanimportantrole in our respondents’socialsupportnetworks. Acrossthethreetypeofanalysiswehavealsolearntthatthetypeofmobilityhas aninfluenceonthecompositionofthesocialsupportnetwork.Fromthecrosssection analysis, we observe that settled respondents seem to rely more on emotionaltieswithwhomtheycanmeetface‐to‐face.Incontrast,transittypeof respondentsweremorelikelytolistsocialtieswithwhomtheycommunicateon thegothroughnewcommunicationsmedia.Inthetypologyonthestrengthon socialsupportwefoundthatrespondentswhoweremorelikelytobesettledin Seville for a longer period, such as the orchestra musicians tended to mention moremultiplexsupportalteri.Thosemorecharacterizedbytemporary displacement, such as IPTS and Erasmus listed mostly alteri providing intermediatesupport.Flamencostoodoutinmentioningthemostalteriproviding specializedsupport. Similarlyfromtheclusteranalysis,weobservedthattheclustersencompassing socialisingsupportnetworksweremoretypicalofrespondentscharacterizedby temporary displacement (Erasmus and IPTS). Respondents who had most multiplex alteri in their personalnetworkswerethosewhoseemtobemore
88 settled in Seville (orchestra). Respondents whose personal networks were dominated by alteri listed in co‐presence seem to be those who are neither in immediatetransitnorcompletelysettled. Fromthedifferenttypologieswehavealsonotethatourpopulationreliesmostly onspecializedsupport:socialcompanionshipbyrecentfriends;distantsupport fromoldfriendsandfamily;instrumentalsupportfromcompatriotsandemotional supportfromoldfriendsandrelatives.Examinationoftheclusters’profilesshow theimportanceofsocialcompanionshipforimmigrants.Twoclusters,whichmake threequartersofoursamplearemainlydefinedbysocialcompanionshipsupport. Acrossthefourclusters,networkcompositionwasamajordimension which differedacrossclusters.Thetypeofsupportprofilehadaninfluenceonthelisting ofSpanishalteri,typeofrelationanddurationofrelation. Intermsoftheinstrumentusedforthiswork,wehavelearntthatcollectingdatain twophasesmakesdatacollectioneasierandallowpersonalnetworksresearchers tocollectavarietyofalteriattributes,otherwiseimpossibletocollect.Thelisting ofthe30alteripriortotheinterviewwasalsousefulinsavinguptimeduringthe interview.Whileintermsofnetworkanalysis,30alteriisalmosttheminimumto studystructureofnetworks,whenitcomestonetworkvisualisations,wefound that30alteriisthemaximumnumberofalterionecanmanageduring an interviewwhenusingvisualmapstoelicittheadjacencymatrix. Thehighlistingofsocialtiesintheco‐presencecategorysuggests that future studiesaddressingsocialsupportofmobileindividualsshouldtakeintoaccount thisaspect.Asthefindingsinthisstudydemonstrates,despitesophisticatednew communicationsmedia,distancestillmatters(Axhausen&Frei,2008),andpeople willinglygooutoftheirwaytospendqualitytimewithsignificantpeopleintheir lives.Interestingly,respondentswholistedthemostalteriinco‐presencesupport weremostlyeitherthosewhohadlivedforaveryshorttime(lessthanayear)or those who had lived for a substantial amount of time (over ten years). Understandably,whenpeoplearriveinanewcity,theyarestillhighlylinkedto alterilivingabroad.Astimegoesby,itseemsthatthelinkwith these alteri is fortifiedagain.
89 Inconclusion,themajorresultsofthisstudyconcernedtherelationshipbetween socialsupport,networkcomposition,typeofmobilityandusageofmedia.First,we foundthatahighproportionofthesocialsupportofourpopulation is kept at distance.Secondly,ourresultsstrengthenthenecessityofexploringmoreindetail theuseofdifferentmediabymobileindividualsandtheinfluenceithasonthe socialsupportnetwork.Thirdly,wehaveunderstoodthatmajordifferencesinthe typeofsocialsupportnetworksseemtoberelatedtomobilitypatternsinherentof thefourrelationalmobilitycommunity. Although it was not the scope ofthestudytoextendtheresultstothegeneral populationofforeignerslivinginSeville,weareawarethatthecontributiontothe literatureonsocialsupportwouldhavebeensounderifwehadtheopportunityto interview more representative respondents. Moreover, utilising an electronic documenttoelicitthesocialsupportnetworkofrespondentsalsohassome disadvantages.Notalltherespondentsunderstoodperfectlywhattheyhadtodoin thefirstpartofthedatacollection,whichwasdoneathome,andhence,theyeither emailed the researcher or waited for the interview to discuss their doubts. Moreover, a number of respondents had to be followed up more than once to ensurethatthedocumentwasfilledandtheinterviewcouldbesetup. Despitetheabovelimitations,therearefewstudiesthatlookedintosimultaneous analysis of 95 respondents and their 30 alteri (2,850 social support providers). Thewidevarietyofdataonthesocialsupportnetworkofeachand every respondentprovidesdatawhichlendsitselftovarioustypesofanalysis,someof whichwehaveexploredinthisstudy.
96 support.Thisapproachshiftedtheattentionfromtheindividual,wherebysocial supportisconsideredapsychologicalcharacteristic,toanoutcome of being embedded in different networks made up of friends, family and other support (Luke,2005).Inthecontextofmobility,personalnetworksenableexplorationof differentnotionsofadaptabilitybeyondthelevelofinstitutionsandorganizations. Theroleofnetworkcontacts,strengthofties,diversityofcontactandstructural holes,tomentionbutafew,playapivotalroleinunderstandingthesocialsupport networkofmobileindividualswhosepersonalnetworksareofgreaterriskfor changesinmembership. Forinstance,theroleofthealteriinrelationtonetworkcompositionwasstudied byWellman&Wortley(1990).Intheirstudy,theyfoundthatspecificsocialties providedifferenttypesofsupport,“respondentsshopforsupportatspecialized interpersonalboutiquesratherthanatgeneralstores.Whiletherespondentsget allfivedimensionsofsupportfromsomewhereintheirnetworks,theyusuallyget different types of support from different network members. Not only different relationships,butdifferenttypesofrelationships,oftenprovide companionship, emotionalaid,services,andfinancialaid”(p.583). Mobility Theuseofnetworkanalysistostudymobilitycanbeseeninavarietyofstudies (Carrasco et al., 2006; Larsen, Urry, & Axhaussen, 2006; Lubbers et al., 2010; Lubbersetal.,2007;Moketal.,2010;Viry,2012).Majorconcernsinthesestudies havebeenthechangeinnetworksizeandstructureandcompositionofpersonal networks as people move to another location. Research seems to suggest that mobileindividualsarecondemnedtosparseindividualisednetworks and face difficulties in bringing their distinct social circles together.Atthesame,these fragmentednetworksprovideopportunitiestotakeadvantageofdifferentsocial circlesandtheirintersections(Kadushin,1966;Simmel,1910‐11). Variousstudieshaveusedpersonalnetworkstostudyvariousfacetsofmigration processes, as for instance, the socialsupportstructure(Martinez Garcia et al., 2001;MayaJariego,2006),theevolutionofthepersonalnetworksofimmigrants (Lubbersetal.,2010),theroleofhostindividuals(deMiguelLuken&Tranmer,
97 2010;Domínguez&Maya‐Jariego,2008),ethnicself‐identification(Lubbersetal., 2007)andsenseofcommunity(MayaJariego&Armitage,2007),amongstother topics. Inthecontextofthiswork,wewereparticularlyinterestedin previous studies whichinsomewayoranotherhaveinvestigatedhowdifferentmobilitypatterns arereflectedinthepersonalnetworksofindividuals.Utilisingapersonalnetwork approachtostudyacommunityinsouthernCalifornia,Schweizer et al., (1998) found that Anglos and Hispanics living in the same area had different types of personalnetworks.Astrikingdifferencewasobservedinthepresenceofkinand familyinthepersonalnetwork.WhileforAnglos,kinandfriendswereofequal importance,forHispanicstiestorelativesweremorenumerous.Overall,theyalso found that although southern Californians are considered highly mobile, their personalnetworkswerenotasgeographicallywidespreadandlocalswerefound toplayamajorrole. In investigating how ethnic self‐identification was reflected in the network structureandcompositionofmigrants,Lubbers,etal.(2007),identifiedfivetypes ofnetworkprofiles,namely:Scarce,Dense,MultipleSubgroups,TwoWorlds ConnectedandEmbedded,whichwerefoundtoberelatedtothedifferentways respondentsidentifiedthemselves.Differencesinnetworkpropertiesasaresultof thetimespentinaresidinglocationwasalsofoundbyDomínguez&Maya‐Jariego (2008).Recentandtemporaltypesofmobilityresultedinpersonalnetworkswith thelowestaveragecentrality.Incontrast,longertypesofmobilitywerereflected in the high average centrality of the personal networks. Similar findings were obtained in the study on residential mobility by Viry (2012), where early residentialmobilitywasreflectedinmoretransitiveandlesscentralizedsupport networks. 4.2.3VisualisationsofPersonalNetworks Theuseofvisualrepresentationtoelicitdataonpersonalnetworksisrelatively recent(Carrascoetal.,2006;Hoganetal.,2007;MayaJariego&Holgado,2005; McCartyetal.,2007).Visualisationsareusefulinthefieldofpersonalnetworks
98 becausetheyshowvisuallythestructureofthenetwork,inwhichgroupingsand the bridges between the groups can be identified with little effort, as well as allowing for exploration of the relations (McCarty et al., 2007).Amajor disadvantageisthatthevisualisationshavetobeexaminedonebyone(McCarty& Molina,forthcoming) Moststudiesutilisingvisualrepresentationsofnetworkshaveusedpaper‐based methods. In such studies, the respondent is requested to draw their network freehand.Inothers,anetworkmapisprovidedandtherespondentisrequestedto placethealteri,sometimesusingpost‐itnotes,accordingtosomeformofrelation withtheego,asforinstance,emotionalcloseness(Gamper,Schanhuth, & Kronenwett, 2012) or through the use of concentric circles depicting different relations(Carrascoetal.,2006). In their Connected Lives study, Hogan, et al. (2007) discuss how the use of sociograms,whichinthatstudywerepaper‐based,enabledresearcherstowork closelywithrespondentssoastoidentifythestrengthofrelationship and efficiently capture ties between alteri. The study conducted bytheJoseph RowntreeFoundationonhowresidentsintraditionallywhiteestatesunderstand theircommunitieshaveusedcommunitymap‐makingtoaccessdifferenttypesof informationfromresidentsandagencyworkers(Pearce&Milne,2010).Theuseof mapstocollectdatahasalsobeenusedmorecreativelyinstudiesliketheoneby denBesten(2010),wherebyhanddrawnmapswerefoundtobeusefulinstudying immigrantchildren'slocalbelongingwiththeirneighbourhoods.Inthisstudy,the maps were found to be appropriate to gather data from children with diverse ethnicbackgrounds,especiallysincemanyofthemdidnotspeak,readorwritethe languageofthehostlocation. Development of new technology has also resulted in a small variety of programmes, such as EgoNet,13Visone14and Vennmaker, which are designed to visualise personal networks. The advantages of using computer based network 13http://egonet.softpedia.com 14http://visone.info/
99 visualisation in the data collection are numerous. A depiction of complex structures is easily made comprehensible, helping both respondent and interviewer (Gamper et al., 2012). Moreover, using pen and a paper to list relations between alteri is tedious, time consuming and does not give the researchermuchpossibilitytofixpotentialerrors.Throughnetworkvisualisations itismucheasierfortheintervieweetoidentifyerrorsintheirnetwork. The effectiveness of computer‐based personal network visualisations against freestylemethodshasbeeninvestigatedbyMcCartyetal.,(2007)intheirstudyin Barcelona. Computer‐based network visualisations rendered important details that were different from respondents’ perceptions of what they had originally drawn,forexample,allowingrespondentstocompartmentalisealteriofdifferent ethnicities.Inasimilarcomparisonusedtoinvestigatewhichtechniquewasmost useful in identifying cliques, groups and communities, freehandvisualisations werefoundtobesimplisticincomparisontocomputerbasedmaps (Cachia & MayaJariego,2010).Ontheotherhand,ascanbeobservedinFigure9,wherewe identifiedsixstyles,thepaper‐basedmethodsallowrespondentsmorecreativity inhowtheydifferentiatepersonalrelationspresentintheirnetworks. Figure9:FreehandVisualisationsofPersonalNetworks15 New media technologies, in particular SNS which are fundamentallybasedon networks have also explored various technological designs to conduct visual exploration for the end‐user. Vizster, is one of them. An ethnographic study conductedusingthisapplicationhasshownthatusersfoundthisapplicationuseful 15Thesefreehanddrawingswereobtainedinthepreliminarystudyconductedforthisdissertation.
100 and enjoyable to explore their personal online networks (Heer & Boyd, 2005). NetGen an application developed to be used through the Facebook API, allows Facebookuserstocreatetheirownnetworkvisualisationsandshareitwiththeir contacts(Hogan,2010).Inthepastfewyears,networkvisualisationsofdifferent onlinedatahavedevelopedintoafieldofstudyonitsown. 16 Network visualisationshavealsobeenusedindifferentstudiesasavisualanalytictoolto discussaparticulartopic.Inastudyontherelationnetworksamongimmigrants, MayaJariego(2006)utilizesnetworkvisualisationsasanillustrationofimmigrant networkvariations.Inastudyonundergraduatestudents,MayaJariego&Holgado (2005) utilize two distinct network visualisations to examine how respondents interpretedtheirstrongtiesandmultiplicityofdifferenttypesofsupport.Inthis chapter, network visualisations extracted from Vennmaker are used as illustrationsindifferentcasestudiestodiscussmobilitypatterns.InAppendix3, we also present the three types of network visualisations collected from respondentsinthisstudy. 4.3Method 4.3.1Procedure Data on personal networks was elicited in this study by asking respondents to namethepeoplewhowouldprovidethemwithvariouskindsofsupport.Ofthe variouskindsofsupportonecouldreceive,wehaveaskedspecifically about emotional, instrumental, socialising and co‐presence support. Foreachtypeof support,welistedtwoquestions. Intotal,respondentswereaskedtoname30alteri. 17During the interview, respondents were presented with the 30 names they had listed and using 16Two excellent repositories of how online network visualisations are being used by designers, statisticians and computer scientists to understand different typesofdataareFlowingData (http://flowingdata.com/) by Nathan Yau and Visual Complexity (http://www.visualcomplexity.com/vc/)byManuelLima. 17Similartootherstudies(McCarty&Molina,forthcoming),somerespondentsemailedustoask whethertheycouldorshouldincludealterithatdidnotliveinthehostlocation.Somerespondents
101 Vennmaker,theywereaskedtocreatetheirownpersonalnetworkbydraggingthe namesintoawhitespaceonthecomputeranddrawingalinebetweenthealteri whokneweachotherFigure10.Asdiscussedalreadybypreviousresearchers,the holisticviewofthenetwork,asopposedtousinga0and1matrix,madeitmuch easiertoremembertherelationbetweenthealteriandhence,indirectlyreduces error(Gamperetal.,2012).Inthisinteractivemanner,respondentscreatedtheir ownmatrixthroughavisualmap. Figure10:ScreenshotofnetworkvisualisationsthroughVennmaker Through Vennmaker, we were able to gather a variety of attributes more effectivelythanthroughthenormalquestionsgenerallyusedinpersonalnetworks study.Forinstance,weutilisedapiechartvisualisationtocollectdataaboutthe locationofthealteriFigure11.Insteadofaskingtherespondentstolistthelocation ofeachandeveryalteri,weaskedrespondentstodragalteriinthecorresponding location.Attheendofinterview,thisdatacouldbeexportedandusedforanalysis. Such mechanisms helped in making the interview more interactive, allowing us to gatheravarietyofdataaboutthealterimoreeffectively. toldusthatafterwardswhentheysawthatwewereaskingforthenationalityofeachalteri,they kindoffiguredoutthatanyalteri,irrelevantofthelocationcouldbementioned.Awayofavoiding specifically telling the respondents to include alteri from alllocationsistoaskrespondentsto specifythelocationofthealteriimmediatelyafterthenamegeneratorisconducted.
102 Figure11:ScreenshotofnetworkvisualisationthroughVennmaker 4.3.2Measures For the analysis of this article, the measures listed below were used. Network characteristicswereexaminedbasedontwomeasures:networkcompositionand network structure. Networkcompositionwasmeasuredthroughfourvariables: locationofalteri,nationalityofalteri,ego‐alterrelationandthedurationofthetie (see Chapter 2). Networkstructurewascalculatedthroughfourcentrality measuresasdescribedbyWassermanandFaust(1994): AverageDegreecentrality:Thisreferstotheperceivedalter‐to‐alterrelation,which istheproportionofpairsofalterswhotherespondentsbelieveknoweachother andwouldgreeteachotherwhens/hewasnotpresent.Foreachrespondent,an aggregatemeasurehasbeenusedwhichcalculatesthedegreecentralityofevery alteri. This measure specifies the degree of connectivity in the network, often describedasnetworkdensity. AverageClosenessCentrality:Thismeasurealsoreferstotheperceivedalter‐to‐ alterrelation,butitisfocusedonthepathanalterihastofollowtobeconnected throughintermediaries.Analteriishighlycloseifs/heisconnectedbytheshortest pathtodifferentalteri.
103 AverageBetweenessCentrality:Ameasureofthenumberoftimesanodeactsa bridgealongtheshortestpathbetweentwoothernodes. AverageEigenvectorCentrality: This refers to the influence of a node in the network. Egohasbeeneliminatedfromallthesemeasures.Bydefinitionegoisconnectedto eachandeveryalter,henceitspresencecanstronglybiasstructuralmeasures,in particular centrality measures (Degenne & Lebeaux, 2005; McCarty & Wutich, 2005). Thetypeofmobilitywasmeasuredthoughthefollowingvariables: reason for moving;durationofresidenceinSeville;howlongtherespondentplannedtostay inSevilleandwithwhomtherespondentlived. In terms of media the aggregate measure frequentfacetoface communication/mobile/email/SNSandVOIPwitheachalteriwasused.18 4.4Results 4.4.1CaseStudies Inthefirstsection,weexaminethepersonalnetworksoffourrespondents,soasto illustratenetworkvariationsintermsofmobilitypatternsdefinedbytherelational mobilitycommunity.Typologiesofnetworksisanefficientmethodforclassifying immigrantsaccordingtotheirprogressinthenewlocation(MayaJariego,2006), orasinourcase,thetypeofmobility.Eachrespondentrepresent relational mobilitycommunityinageneralway.Thedescriptionofthepersonalnetworksis based on the structure and composition of the personal networksofthe respondents. For each case, we usetwovisualisations:thepersonal network visualizationthattherespondentscreatedduringtheinterviewusingVennmaker, and a network visualization that we created post‐interview as awayof summarizingthepersonalnetworkintermsofnetworkcomposition(nationality 18ThegenericmeasuresaredescribedinmoredetailinChapter2.
104 ofalteri,locationandego‐alterrelation)andthetypeofsupportprovidedbyalteri. Eachgraphincludes: The 30 alteri mentioned by the respondent. The respondent is excludedfromthesociogram. Thetiesbetweenthenodesindicatethatthealteriknoweachother andwouldgreeteachotherintheabsenceoftherespondent. Thecolourofthenodesindicatesthenationalityofthealteri:redfor Spanish;blueforcompatriotsandbrownforothernationalities. The size of the node reflects the type of support provided by the alteri. Social support was presented across five categories: emotional, instrumental, socialising, co‐presence and other, with emotional displayed as the largest node and other as the smallest node(seeChapter3formoredetails). Thethreesectionsdefinedbythepiechartindicatethelocationof residence of the alteri during the time of the interview. The pink representsSeville, the light blue representscountry of originand theyellow,otherlocations. Case1:Yoko,flamencoDancer Yokoisa35‐year‐oldJapanesedancerwhomovedtoSevilleovertenyearsagoto pursuehertraininginFlamencodancing.ShelivesinSevillewithherpartnerwho isSpanish.ShefeelsconnectedtoSevillemainlythroughFlamenco.Shetrainsfor severalhoursduringthedayandworksintheevenings. The composition of Yoko’s network is a combination of Spanish and Japanese. Typical of other flamenco respondents, Yoko has a high proportion of Spanish peopleinherpersonalnetwork.Thefactthatemotionalsupportalteriaremainly SpanishandliveinSevillestandout.Similarly,thelackofJapanesealteriinSeville isalsounique,ascompatriotslivinginSevilleseemtobeindispensableforother mobile individuals in this study, especially for instrumental support. Notwithstanding the long duration in Seville, we also observe that a high proportionofherpersonalnetworkisbasedinJapan,hercountryoforigin.The
105 majority of these alteri were listed as alteri Yoko travels to visit for important events. Yoko'snetworkstructureisclearlydefinedintwolocations,SevilleandJapan,but thereislittlecontactbetweenthetwolocations.Fewalterilivinginotherlocations werelisted.Yoko’spartnerplaysanimportantroleinhernetworkbecauseheis connectedtothethreemainlocations. Figure12:Yoko´sPersonalNetworkinUcinetandVennmaker Ifwelookatthevisualisationontheleft,weobservethatthenetworkisdispersed showing various subgroups with little contact between one and another. When asked to divide the network into different groups, Yoko came up with eight categories,namely:family,neighbours,partner'sfriend,partner'sfamily,Japanese friends, Japanese flamenco mentors, flamenco friends in Sevilleandfriendsin Seville.Yoko'snetworkshowsahighaveragebetweeness. Case2:Margot,Erasmusstudent. MargotisaPolishstudent,whomovedtoSevilleasanErasmusstudent.Shehas livedinSevillefor6monthsandwillgobacktoPolandattheendofthescholastic year.Sheis22yearsoldandliveswithherflatmates.ShefeelsconnectedtoSeville throughherbestfriend,salsaandthegoodfeelfactorofthecity. Margot’spersonalnetworkismainlymadeupofcompatriots,who live in her country of origin. Her alteri in Seville are mainly other foreigners, followed by compatriotsandSpanish.Emotionalsupportis mainlylocatedinhercountryof origin,whileinstrumentalandsocialisingsupportarebasedinSeville.Margotsees
112 alterilivinginSevilleandthehighestproportionofSpanishintheirnetwork.In contrast,partnersofIPTSemployeesandErasmusmentionedthehighestnumber ofalteriincountryoforiginandthehighestnumberofcompatriots. Whenitcomestostructure,respondentsfromIPTS,followedbythosefromthe orchestrahadthehighestclosenessnetworks.Averageclosenesscentralizationis theextenttowhichthenetworkstructureisdominatedbyasinglealterintermsof closeness. In contrast, respondents from Erasmus and Flamenco differed significantlyinhavingpersonalnetworkswithlowclosenesscentrality. In terms of media used to communicate with alteri providing different kinds of support,majordifferencescanbeobservedinthefrequentuseofSNSandVOIP Clearly,newcommunicationstechnologiesplayamajorroleinthewayErasmus studentscommunicatewiththeiralteri.TheserespondentsusedSNS to communicatewithhalfoftheiralteriandlistedthehighestnumberofalteriacross the four communities with whom they communicated frequently using VOIP. Email,whichseemstobedisplacedbySNSinthecaseofErasmus students, is mainlyusedbyIPTSrespondents. Musiciansfromtheorchestra(M=13.06,SD=4.68)andflamencoartists(M=11.05, SD=5.60)weremorelikelytolistalteriwithwhomtheymeetfrequentlyface‐to‐ face. Respondents from the orchestra also communicated frequently with their alterithroughmobile(M=9.17, SD=3.50).Japaneserespondentsweretheleast technological across all the communities, mentioning the least number of alteri withwhomtheycommunicatedbymobilephone(M=4.11,SD=3.70),SNS(M=2.63, SD=2.77)andVOIP(M=0.79,SD=1.27). Lookingattheresultsofbothsectionsabove,weobservesimilarities in the findings. A relation exists between both network composition and network structure and the type of mobility that frames our respondents.Thetypeof mobilityundertakenbyourrespondentsisreflectedintheirnetworkcomposition. Musicians and Flamenco artists not only had a high proportion of emotional supportinSevillebutalsolistedthehighestnumberofSpanish alteri. Those respondentswhohavelivedinSevilleforover10yearsweremore likely to
113 mention between 8–16 (71%) and between 17‐26 (21%) Spanish alteri. The maximum number of Spanish alteri mentioned was 26. Musicians from the orchestra were characterised by their long mobility in Seville,whilethehigh mentioningofSpanishalterifromtheJapaneseartistsmightbemorerelatedtothe fact that through the flamenco communitytheseartistshaveadirect access to Spanishalteri(Figure17).Wealsoobservethatthetwocommunitiesthatlistedthe mostSpanishalteriandalterilivinginSeville,thatis,musiciansfromtheorchestra andflamencoartistswerealsotheoneswholistedthehighestnumberofalteri with whom they communicated face‐to‐face. In both these communities, respondentsseemedtobemoresettledinSeville. Incontrast,respondentswhohaveeithermovedrecentlyorwhohavemovedfora shortperiod,asinthecaseformostErasmusstudentsandIPTSpartnertendedto remainhighlylinkedtoalteriincountryoforiginandcompatriots. Emotional supportwasalsomainlyincountryoforigin.Respondentsfromthesecommunities listed the lowest number of Spanish alteri and alteri living in Seville. Their mobilitiesarecharacterisedbyatransitnature,andhence,thereislittleeffortput towardsdevelopingone’spersonalnetworkswithsocialtiesthatinfewmonthsor yearstimewillbeoutofone'spersonalnetwork.Inbothcommunities,thelinkto compatriots and other nationals is much easier than with the Spanish.In particular,themajorityofIPTS’partnersnotonlyliveontheperipheryofcitylife, giventhatIPTSisnotlinkedinanywaytoSevilleortoSpain, but also face languageproblems.InthecaseofErasmus,linkswithtransnationals is much easierandintheshortperiodofresidencetheyareunlikelytobeconnectwitha highnumberoflocals.
114 Figure17:MobilityPatternsbyNetworkComposition Intermsofnetworkstructure,wealsoobservesomepatternsthatcouldalso signifyarelationtothetypeofmobilityofourrespondentsFigure18.Asobserved bythecasestudies,Boris’(orchestra) network is the most denseandcohesive; Celia(IPTS)alsohasadensenetwork,butwealsoobservesubgroupsrelatedto herrecentmovethatarelessconnectedtoherdensenetwork.Following the patternofhernetwork,itislikelythatinamatteroftime,someofthesetieswill get to know each other. Moreover, respondents from these communities also coincidedinhavingthehighestclosenessnetworksacrossourpopulation. Figure18:MobilityPatternsbyNetworkStructure Somecommonalitiesbetweenthesetwotypesofrespondentsare:size of community,formalstructureofthecommunityandeducation.Respondentsfrom IPTSandtheorchestrahavemovedtoSevilleforemploymentpurposes. The
115 relationalmobilitycommunitiesto which they pertain are small cohesive communities,whereitiseasiertoconnecttootherpeopleandmakefriends.While wehavegatherednodataonthestandardoflivingofourrespondents,duringthe interviews,someofwhichtookplaceatrespondents’houses,itwasevidentthat respondents from the orchestra and the IPTS had a higher standard of living, possiblyasaresultofbelongingtothesamerelationalmobilitycommunity. In termsofeducation,wefoundnopositiverelationbetweenthehigheducationof these respondents (more than 60% in both communities have a post‐graduate degree)andthelevelofclosenessoftheirnetworks. In contrast, Yoko’s (flamenco) personal network is the sparsest with different subgroups clearly separated fromeachother.SimilarlyMargot’s(Erasmus) networkisalsomadeupofdifferentgroups,whicharenotnecessarilyconnected witheachother.Theirlowcohesionwasalsoreflectedinthelow closeness centrality.RespondentswithinthesecommunitiesmovedtoSevillethroughlarge, dispersedrelationalcommunities,which,whileprovidingaframeworkforone’s community,wouldpossiblynotplayamajorroleinone'ssettlementinalocation asasmallcohesivecommunitydoes,asinthecaseofIPTSandtheorchestra. 4.4.3NetworkProfiles Inthissection,aquickclusteringprocedureisusedtoexplorewhetherdifferent typologiesofnetworkprofilesreflectsimilarpatternsofmobilityasdefinedbythe relationalmobilitycommunity. The objective of the typology construction is to discoversystematiccovarianceamonggroupingsofthenetworkcharacteristics.In thissectionthedistinguishingfeaturesofthenetworkprofilesaredescribed,while therelationwithothermobilitycharacteristicsofourrespondentsispresentedin thefollowingsections. ThenetworkclusterswerederivedthroughakmeansclusteranalysisusingSPSS. Theclusterswerebasedonfourcriterionvariables,onecharacteristicforeachof the four network variables: location, nationality, centrality, relation. The characteristics used were: the number of alteri living in country of origin, the number of Spanish alteri, degree centrality and the proportion offamilyinthe
116 personalnetworksofourparticipants.Thedurationofrelationwasleftout,given theclustersdifferedminimallywhetherornotthischaracteristicwasincludedor not.Fivecaseswereexcludedonthebasisofbeingoutliersononeofthevariables. Aftercarefulconsideration between differentnumbersofclusters,weoptedfor four clusters from which we could distinguish four types of network profiles alreadypresentinthecasestudies.Thetermsusedtorefertotheclustersarefor descriptive purposes given they only refer to one distinctive property of the clusters.TheclustercentresofeachvariablearepresentedinTable15. Dense network (N=13):highaveragecentralitynetworksandmedium numberofalterilivingincountryoforigin,numberoffriendsandnumber ofSpanishalteri; Table 15. ClusterCentresforNetworkProperties ( N =90) Networkprofiles(Clusters) Dense (n=13) Host (n=21) Distant (n=34) Far‐Flung Sparse (n=22) Averagecentrality 51.1 26.4 31.0 18.4 Nalterilivingincountryoforigin 12 6 14 14 Nfriends 19 17 22 19 NSpanishalteri 8 15 4 7 Hostnetwork(N=21): personal networks that consists of high Spanish alteriandlowproportionofalterilivingincountryoforiginandfriends; Distant Network (N=34):largestcluster,mainlymadeupofpersonal networksmadeupoffriends,ahighnumberofalterilivingincountryof originandlownumberofSpanishalteri; Far‐FlungSparsenetwork(N=22):personalnetworksmainlycharacterized bylowaveragecentralityandhighnumberofalterilivingincountry of origin.
117 Thenetworkprofileoftherespondentswaspositivelyrelatedto the relational mobilitycommunity,χ 2 (9,N=90)=37.91,p=.00.Japaneseflamencorespondents weremorelikelytohavesparsenetworksandlesslikelytohavedistantnetworks. AhighmajorityofErasmusstudentshadadistantnetworkprofile,butwealsosee asmallportionofstudentswithFar‐flungSparsenetworkprofile.PartnersofIPTS weremorelikelytohaveDistantandSparsenetworksprofile.Musiciansfromthe orchestraweremorelikelytohaveHosttypeofnetworkprofile,followedbyDense networktypology(Figure19). Figure19:ThefourclustersbytypeofRelationalMobilityCommunity Networkprofilesdifferedsignificantlyintermsofthetypeofmobility:thereason formovingtoSeville;thedurationofstayinSeville;howlongtheyplannedtostay inSeville;andwithwhomtheylivedinSeville(Table16). Whencomparedwithindividualcharacteristics,theclustersdifferedintermsof age,χ 2 (9, N = 90) = 34.46, p=.00;legalstatus,χ 2 (12, N = 90) = 27.22, p = .01; education,χ 2 (9,N=90)=17.45,p=.04;andworkstatus,χ 2 (9,N=90)=31.83,p= .00.Intermsoffrequencyofdifferentmodesofcommunication,weonlyobservea significantdifferencebetweencommunicationthroughSNS,χ 2 (3,N=90)=12,24, p=.01.AdescriptivesummaryofthemainfindingsispresentedinTable17.The natureofeachnetworkprofileispresentedinthenextparagraphs. TheDenseNetwork profileis mainly characterized by respondents with dense networks.Respondentswithhigh centrality networksweremorelikely to list a highnumberofalterilivingintheircountryoforiginandanintermediatenumber 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Flamenco Erasmus IPTS Orchestra Sparse Distant Host Dense
118 Table 16. FrequenciesandAnalysisofVarianceofMobilityVariables ( N =95) Cluster1 Cluster2 Cluster3 Cluster4 N % N % N % N % X2 ReasonforMoving Work 5 38.5 9 42.9 5 14.7 2 9.1 23.28* Relationship 0 0 4 19 5 14.7 4 18.2 Famil y 1 7.7 2 9.5 6 17.6 2 9.1 Studying 5 38.5 5 23.8 18 52.9 14 63.6 Wantedachange inlifestyle 2 15.4 1 4.8 0 0 0 0 Howlonghaveyou livedinSeville Lessthanayear 5 38.5 0 0 22 64.7 10 45.5 34.79**** 1–5years 1 7.7 7 33.3 10 29.4 7 31.8 6–10years 1 7.7 2 9.5 1 2.9 0 0 Over10years 6 46.2 12 57.1 1 2.9 5 22.7 Howlongdoyou plantostayin Seville? Idonotknow 2 15.4 5 23.8 6 17.6 4 18.2 31.16**** Fewmoremonths 5 38.5 1 4.8 20 58.8 9 40.9 1‐5years 1 7.7 3 14.3 6 17.6 7 31.8 Indefinitel y 5 38.5 12 57.1 2 5.9 2 9.1 Withwhomdoyou live? Alone 0 0 4 19 1 2.9 3 13.6 24.42*** Partner 3 23.1 8 38.1 6 17.6 8 36.4 Family 4 30.8 9 42.9 8 23.5 2 9.1 Flatmates 6 46.2 0 0 19 55.9 9 40.9 *p<0,05; ** p<0,01; ***p<0,005; **** p<0,001 ofalterilivinginSeville.Respondentswiththisprofileweremainlybetweenages 41‐60 (46%), followed closely by ages 21‐40 (39%). The mobilityofthese respondentsismainlycharacterizedbyaneedtochangetheirlifestyle. RespondentswithaHostNetworkprofilelistedahighnumberofSpanishalteri and a low number of alteri living in the country of origin. These respondents tendedtobemiddle‐aged,hadhighereducation(withamajorityhavingapostgraduate degree) and were more likely to be married. This cluster is clearly differentiatedbyhavingrespondentswhoplantoliveinSevilleindefinitely.Most oftheserespondentshavemovedtoSevillebecauseofwork,andthemajorityis employed. Cluster3isthebiggestclusterandischaracterisedbyDistantNetworkprofiles, wherebyrespondentslistedahighnumberofalterilivinginthecountryoforigin and consequently, few Spanish alteri. Participants with this profile were more likelytohavelivedinSevilleforlessthanayearandhardlyanyrespondents plannedtoliveinSevilleindefinitely.Themajoritywerestudentsagedbetween ages21‐40claimingtocommunicateweeklywiththeiralterimostlythroughSNS.
119 Table17.CharacteristicsoftheNetworkProfiles(N=95) Description TypeofMobility,IndividualCharacteristics andCommunication Profile1: Dense Network Highaveragecentrality Intermediatenumberofalteri livingincountryoforigin, listingoffriendsandlistingof Spanishalteri Youngestofalltherespondents MovedtoSevilleforachangeinlifestyle. Profile2: Host Networks Highest frequency of Spanish alteri Lowestnumberofalteriliving in country of origin and listing offriends Middle‐agedrespondents Higheducation PlantoliveinSevilleindefinitely MovedtoSevillecauseofworkandthemajority areemployed. Profile3: Distant Network Highestlistingoffriendsand alterilivingincountryoforigin LowpresenceofSpanishalteri LivedinSevilleforlessthanayear HardlyanyrespondentsplannedtoliveinSeville indefinitely. Morelikelytobestudents Highlistingofalteriwithwhomthey communicatethroughSNS Profile4: FarFlung Sparse Networks Mainly characterized by the lowestaveragecentrality Highestmentioningofalteri livingincountryoforigin Morelikelytobedivorcedorseparated. Theyweremorelikelytobestudying Plantomoveeitherinthenextfewmonthsorin thenext1‐5years. TheFarFlungSparseNetworkprofileischaracterizedbyrespondentswithlow centrality networks and a high proportion of alteri living in country of origin. Respondentswithsparsenetworksfallinthemiddlerangeofallthemobilityand backgroundvariablesandarenoteasilycharacterizedbymobility and demographics variables. These respondentswere more likely to be divorced or separatedandthemajoritywasbetweenages21‐40,althoughseveralwerealso betweenages41‐60.Respondentswiththisprofilewereplanningtomoveeither inthenextfewmonthsorinthenext1‐5years.Respondentswithinthisnetwork weremorelikelytobestudying.
120 4.5Discussion The major question in this chapter is whether personal networksofmobile individualsdiffersystematicallydependingonthetypeofmobilitydefinedbythe relationalmobilitycommunity.Network visualisations and analysis of network compositionandstructureacrossthefourcommunitiesrevealedaheterogeneous foreignpopulation,inwhichpersonalnetworksdovaryaccording to specific aspectsofmobility. Whilesomedifferencescanbeexplainedbypersonalcharacteristics,similartothe findings by Fischer (1982a), we observe that the role of the relationalmobility communityhasacertaintypeofinfluenceinthemobilityundertaken.Communities stimulatedwhatFischertermsasselectivemigration.Peopleundergochangesand altertofitinsomecommunities,whilecommunitiesattractcertaintypesofpeople, whichbringwiththemcertainkindsoflivesandnetworks.TheJapaneseflamenco dancerisbynatureaverydifferenttypeofmobileindividualthanthemusician fromtheorchestra.Bothhaveoptedtogoabroadtopursuetheirpassionforart, however,thecontextinwhichtheydidsodiffered. Resultsinthisstudyinferthatpatternsofmobilitymaybereflectedinthepersonal networks of mobile individuals. We have observed that network composition variesdependingonthetypeofmobility.Mobileindividualswithasettledprofile weremorelikelytohavepersonalnetworksdominatedbytheexogroup(e.g.the Spanish, alteri living in Seville, friends). Respondents who wereinSevillefora temporaryperiod,knowingthatadisplacementtoanotherlocation(beitcountry oforiginorotherlocation)waseitherimminentordefiniteweremorelinkedto theendogroup(alterilivingincountryoforigin,family,compatriots,etc). Intermsofnetworkcomposition,respondentswithdensepersonalnetworkswere more likely to be linked to small cohesive relationalmobilitycommunities.In contrast,thosewithsparsenetworkshavemovedtoSevillethroughlargesparse relationalmobilitycommunities. Thenetworkprofilesidentifiedbytheclusteranalysisarecloselyrelatedtothe distinct mobility determined by the relationalmobilitycommunity.While some
121 overlapcanbeobserved,overallSparseNetworkprofilesweretypicalofJapanese flamenco artists, Distant Network profile of Erasmus students and partners of IPTS,andHostNetworkprofileoforchestramusicians. Theprocedureandtoolsusedincollectingdataforthisstudy,inparticulartheuse ofVennmakertodevelopthepersonalnetworksduringthedatacollection, allowedustoconductmoreefficientinterviewswithfewerburdensonboththe respondent and the interviewer. In our view, these methods are not only preferableinmanywaysincomparisontotraditionalwaysofcollectingpersonal networkdata,butalso morereliable andmoreprecise.Respondents responded verypositivelytothevisualisationsoftheirpersonalnetworks and they often commentedonthemandcomparedthemtothefreehanddrawingoftheirpersonal network.Thisaddedvaluetotheinterview,aswefeelrespondentsalsobenefited fromtheinterview. Amajorweaknessofthisstudyisthemethodusedtoelicitthename‐generator. While eliciting the name generator through an online document allowed us to collectmoredataduringtheface‐to‐faceinterview,asyet,wecannotensurethat allrespondentsdidthenamegenerationinthesamemanner.Peoplecanreferto differentdevices(email,contactsonmobile,etc)toretrievethenames.Thiscould createabiasinthedatatowardsparticulartypeofrelations(McCarty&Molina, forthcoming).Moreover,ego‐reportingtechniquesarerifewithpotentialforerror, given ego may provide erroneous data about her alteri, as well asaboutthe relationthatexistsbetweenthem,andtheperceptionofthetiemightnotalways bereciprocatedbythealteri.
128 describedbyHughey&Speer(2002),wheretheydescribehowbridgestodense networks,forinstance,increasethediversityofavailableresources.Althoughreal value is accrued to those who are embedded in cohesive networks, cohesive networksmaynotbeenoughtosustainwell‐beingorchangeanoppressive network.Networkanalysismaybeusefulinidentifyingthoseweaktieswhichare indispensable in the provision of bridgingsocialcapital (Granovetter, 1973; Putnam,2000). Literatureandresearchoncommunitysuggestthatincontemporary societies, senseofcommunityislesstiedtoalocationandmoretosocialrelations.Theshift from locational(spatially‐defined communities) to more relational(relationallydefinedcommunity)communities(Bessetal.,2002;Kayahara,2006;Rheingold, 1993)raisesomeimportantquestion on howcommunityattachmentshouldbe researched. Mutually supportive networks of relationships are now possible amongstpeoplewhodonotnecessarilysharethesamegeographical neighbourhood experience (Wellman, 1996; Wellman et al., 1988).Social connectionsmayalsobekeptatadistance(Albrow,1997;Fennell,1997;Horrigan, 2001;Licoppe,2004;Wellman,1996,2002). The relation between notions of community and network structurehasbeen studiedfromvarious aspects (Cowman et al.,2004;Domínguez&Maya‐Jariego, 2008; Fischer, 1982a; Maya Jariego & Armitage, 2007). Castles (2002) explores whether a relation exists between community attachment and a community's socialnetworkstructureforresidentsfromsixcommunitiesinWashing State. Findings suggest that a community’s network structure does not significantly affectcommunityattachment,butitaffectone'sevaluationofcommunity. Residents of cohesive communities were more likely to provide positive evaluationsofthecommunity'ssocialandphysicalenvironment. Analysisofcommunityattachmentandsocialsupportcannotunderminetheuseof new communications technology. In response to the study by McPherson et al. (2006),whoclaimedthatsocialtiessupportedbynewtechnologiesareweakand geographically dispersed, the Pew Internet Personal Networks and Community survey found that Americans are not as isolated as previously reported, mainly
129 becausetheuseofthemobilephoneandtheinternetwasfoundtobeassociated with larger and more diverse discussion networks (Hampton et al., 2009). Portabilityofnetworkshasledtoeasyaccesstoawidearrayofsocialties,through which various kinds of social support is sustained. In their study of an online newsgroupcalledMultipleSportsNetwork,Blanchard&Markus(2002)foundthat members experienced a different kind of sense of community thanthat experiencedthroughface‐to‐faceinteraction.Senseofcommunityamongstonline memberswasmaintainedthroughsocialprocessesofexchangingsupport,creating identitiesandmakingidentificationsandtheproductionoftrust. Givensocialtiesaremorelikelytobeextendedspatiallyformobileindividualsand hence,theirpersonalnetworkandsocialsupportisfarthanconcentratedintheir residinglocation,wewereinterestedtoinvestigatetheroleoftheresidinglocation forcommunityattachment.Inthenextsectionwepresentthemethodsusedinthis study,followedbytheresultsandadiscussiononthefindings. 5.3Method In this chapter, we use the data of the 95 respondents from the four distinct communities, namely: Japanese Flamenco artists, Erasmus students, partners of employeesworkingattheIPTSand musiciansfrom thesymphonic orchestrain Seville.Theanalysisisbasedontwosetsdata.Thefirstdatasetisbasedonour respondents were N=95.Theseconddataisbasedonalteriattributeswere N=2,850. Measuresusedinthisstudywerethefollowing: SenseofCommunityIndex(SCI).Theoriginal12itemSCI(McMillan&Chavis,1986) wasusedasaproxytomeasurethelevelofconnectionrespondentsfeltwiththe hostlocationasacommunity.Fouritems(4,5,6&9)outofthe12wereadjustedto refer to neighbourhood. In our understanding, these items were moreaptin relationtoneighbourhood,ratherthantoSeville.The12itemswerepresentedon aLikertScalerangingfrom1(stronglyagree)to4(stronglydisagree).Thescales contained both positive and negatively worded questions, which were reverse
130 scoredbeforeanalysis.TheinterviewswereconductedinEnglish.Clarifications,in particularinconductingtheSCIweremadeinSpanishwhennecessary. Recently the SCI instrument has been revised. The Sense of Community Index version2(SCI‐2)is nowcomposedofa 24items (Chavis,Lee,&Acosta,2008). While the latter instrument would have been more appropriate for our study, givenitismoreadequateasacrossculturalmeasure,thelengthofourinterview didnotpermita24iteminstrument.Although,thisisalimitationtoourstudy,itis atrade‐offwehadtochoose.However,wedidconducttheSCIthroughaLikertlike scaleasproposedinSCI‐2insteadoftheTrue‐Formatformatproposedoriginally. InordertoevaluatetheinternalconsistencyoftheSCI,Cronbachalphareliability wascalculatedforthefoursubscalespercommunity. 19Giventhetotalinternal consistencyoftheSCIinthisstudywasmoderate=.59,some items withlow consistency were removed.Principal components factor analysis with varimax rotationrevealedfivetypesofrelationsofthewayrespondentsconnecttothecity, ascanbeobservedinTable18.Forthisanalysis,thefirstfactorwillbeused.We havelabeledthisgroupoffiveitemsasPlaceAttachment.TheCronbach'salpha reliabilityestimatesforthisfactorwasmoderatelyhigh=.70. TypeofSocialSupport:The type of social support was measured across two indicators: - StrengthofSocialSupport:The15typesofsupport(Table9)providedby 2,580alteri weregroupedintothreegroupsaccordingtothe strengthof socialsupport,namely:specializedanduniquetypeofsupport,intermediate typesupportandmultiplexsupport(seeChapter3). 19 TheinternalconsistencyforthefourcommunitieswashigherwithintheIPTS(=.71),andlower withintheotherthree:ROSS(=.59),Erasmus(=.58)andFlamenco(=.45).Webelievethatthe lowinternalconsistencyfortheFlamencocommunityisrelatedtopossiblydifferentunderstanding byJapaneserespondentsonnotionsofcommunityincomparisonwithWesternparticipants.As ourownresultsdemonstrate,despitebeingacollectivesociety,thereseemstobelesssignificance givenbetween relationsbetween people. RemovingtheFlamencoparticipantsfromSCIanalysis onlyimprovedtheconsistencymarginally(=.60).Forthisreason,wehaveoptedtoconductthe analysis,includingtheJapaneserespondentsandinstead,removingsomeoftheitems.
131 Table18.FactorAnalysisoftheSCI Factors 1 2 345 Factor1:PlaceAttachment IexpecttoliveinSevilleforalongtime ,789 ‐,162 ,089 ,104 ‐,055 IfeelathomeinSeville ,741 ,321 ‐,043 ‐,137 ‐,123 Veryfewpeopleinmyneighbourhoodknowme* ,605 ,099 ,148 ‐,197 ,204 IhavenoinfluenceoverwhatSevilleislike* ,604 ‐,223 ‐,296 ,127 ,385 IthinkSevilleisagoodplaceformetolive ,539 ,410 ,126 ,324 ,047 Factor2:SharedValue s PeopleinSevilledonotsharethesamevalues* ,041 ,785 ‐,069 ‐,137 ,022 PeopleinSevilleandIwantthesamethingsfromthecity ‐,005 ,762 ,065 ,353 ‐,138 Factor3:Neighbourhoo d Itisveryimportantformetoliveinmyneighbourhoodin Seville ,034 ,093 ,842 ,049 ,201 Icanrecognisemostofthepeoplewholiveinmy neighbourhood ,449 ‐,185 ,526 ‐,290 ,002 Factor4:Perceptionoflocalhost s IfthereisaprobleminSevillepeoplewholiveherecan getitsolved ,011 ,162 ‐,130 ,772 ,097 Peopleinthiscitygenerallydon’tgetalongwitheach other* ,108 ,272 ‐,472 ‐,615 ,197 Factor5:Action s Icarewhatmyneighboursthinkofmyactions ,037 ‐,050 ,175 ,011 ,919 Eigenvalue2,41 1,70 1,40 1,39 1,16 Varianceexplained20,08 14,16 11,67 11,61 9,70 Cronbach´s .70 .53 .48 .53 *Allitemshavebeenreverselyscored - TypeofSocialSupport: Four social support typologies were used for this analysis.20These were (1) Diversified Social Companionship, (2) Recent SocializingTies(3)Polyvalentsupportbyoldfriendsand(4)Co‐presence support(seeChapter3fordetails). NetworkCharacteristics. Two measures were used as network characteristics: networkcompositionandnetworkstructure.Networkcompositionwasmeasured 20ProfileswerederivedthroughakmeansclusteranalysisusingSPSSasreportedinChapter3. The clusters were based on three criterion variables: social companionship; co‐presence; and emotional&socialcompanionship.
132 through five variables: location of alteri, nationality of alteri, ego‐alteri relation, duration of the tie and the age of the alteri. Networkstructurewas calculated throughfourcentralitymeasuresasdescribedbyWassermanandFaust(1994), namely average degree centrality, average degree centrality, average closeness centralityandaveragebetweenesscentrality(seeChapter4).Withrespecttothe lattermeasure,inthisarticleweonlyuseaveragedegreecentrality. NetworkProfiles:Fournetworkprofileswereusedforthisanalysis.21Thesewere (1) Dense networks, (2) Host networks, (3) Distant networks and(4)Far‐flung sparsenetworks(seeChapter4formoredetails). Communication.Foreachalter,respondentswereaskedhowfrequentlythey communicated through different media, namely face‐to‐face, mobile, email, SNS andVoIP.Forthisanalysis,onlyfrequentcommunicationwasutilized,whichwas measured according to the number of alteri mentioned in daily and weekly communicationforeachtypeofmedium.Respondentswerealsoaskedhowoften theyusedeachtypeofmediumperday. Mobility.Thetypeofmobilitywasmeasuredthoughthefollowingvariables:reason formoving;durationofresidenceinSeville;howlongtherespondentplannedto stayinSevilleandwithwhomtherespondentlived.Thetypeofrelationalmobility communitywasalsostudiedaspartofthemobilityconstruct. VariablesweretestedfornormalityusingtheShapiro‐Wilktest.One‐wayAnova (Schefféintergroupmeans)wasusedfornormallydistributedvariables(Fscores) andtheKruskal‐Wallistest(Hscores)wasusedforthenon‐parametricvariables. Forthenon‐parametricvariables,follow‐upteststoevaluatepairwisedifferences amongthefourcommunitiescontrollingforTypeIerroracrosstestsbyusingthe Bonferroniapproachwasused.Adescriptionoftheresultsispresented in the followingsection. 21ProfileswerederivedthroughakmeansclusteranalysisusingSPSSasreportedinChapter4. Theclusterswerebasedonfourcriterionvariables:alterilivingincountryoforigin,numberof Spanishalteri,averagedegreecentralityandtheproportionoffamilyinthepersonalnetworksof ourparticipants.
133 5.4Results Resultsarepresentedinthreesections.Section5.4.1outlinestheoverallsenseof community experienced by respondents using both quantitative and qualitative measures. The second section explores how different typologies of our respondentsarerelatedtoplaceattachment.Thefinalsectionpresentsresultsofa cluster analysis derived from measures based on the three majorareasofthis study, namely personal networks characteristics, social supportandplace attachment. 5.4.1Overallsenseofcommunity ToassessthesenseofcommunityrespondentsexperiencewithSeville,theSCIwas conducted.Themeanscorewas2.32(SD=0.32),whereascoreofoneindicatedthe highestpossiblescoreofsenseofcommunity,and4indicatedtheweakest.This mean suggests that participants in this study showed a relativelylowsenseof communitywithSeville. Table19presentsthemeansandstandarddeviationsforeachscale for each relationalmobilitycommunity and the variance between communities. Although, wefoundnosignificantdifferencebetweenthefourcommunities,wecanobserve thatFlamencoartistsandorchestramusiciansshowedahigherscoreofsenseof communitythanErasmusstudentsandIPTSpartner. Ifwelookatthefourscalesseparately,weobservesignificantdifferenceacrossthe fourcommunitieswhenitcomestomembershipandreinforcementof needs. Musicians from the orchestra showed the highest membership. Thetwoitems which caused the intercommunity variation in the Membership scale were neighbourhoodrelated.Almostalltherespondentsfromtheorchestraagreedthat they could recognize and be recognized by their neighbours. Erasmus students registeredthelowestmembership.
134 Table 19. MeansandKruskalWallisVarianceoftheSCIacrosscommunities FlamencoErasmus IPTS Orchestra M SD M SD M SD M SD F H Membership 2.16 0.53 2.60 0.53 2.21 0.60 2.04 0.52 14.325*** Influence 2.48 0.45 2.48 0.40 2.65 0.57 2.41 0.35 2.505 Reinforcement ofneeds 2.39 0.37 2.10 0.46 2.19 0.50 2.43 0.47 8.427* Shared Emotional Connection 2.07 0.40 2.40 0.49 2.24 0.49 2.19 0.29 7.127 TotalMeanSCI 2.26 0.24 2.39 0.31 2.32 0.39 2.27 0.29 0.908 Allmeasuredona4‐pointscalewhere1=StronglyAgreeand4=StronglyDisagree *p<0,05;**p<0,01;***p<0,005 Note.SCI=SenseofCommunityIndex(Chavisetal.,1986) Incontrast,Erasmusstudentsweretheonestomostlyagreethattheirneedsare reinforcedinthehostlocation.Theitemwhichcausedthemajordifferenceinthis scalebetweenrespondentsispeopleinSevilleandIwantthesamethingsfromthe city.Interestingly,musiciansfromtheorchestraweretheleast tofeelthattheir needsarereinforcedinthecity. In general, participants responded slightly more positive to place attachment, althoughthescoreremainsrelativelylow.Themeanscorewas2.24 (SD=0.52). Musicians from the orchestra scored the highest place attachment, followed by Flamencoartists.PartnersofIPTSemployeesweretheonlyonestoscorealower placeattachmentthansenseofcommunity.22Thelowstandarddeviationssuggest that there was little difference in the way participants withineachcommunity respondedtoplaceattachment(Table20). ROSSmusiciansdifferedsignificantlyintermsofplaceattachmentfromErasmus students. The item which caused the most difference in the total score is respondents’expectationtoliveinSevilleforalongtime.Bothmusiciansfromthe 22Erasmusstudentsshowedonlyaminordifferencebetweenthetwoscales.Orchestramusicians and Flamenco artists registered the highest difference between the two scales, scoring more positiveinplaceattachment.
135 orchestra and flamenco artists expected to live in Seville the longest. Erasmus studentsweretheleasttoagreetoexpecttoliveinSevilleforalongtime. Table 20. MeansandKruskalWallisVarianceofPlaceAttachmentacrosscommunities FlamencoErasmusIPTSOrchestra MSDMSDMSDMSDH IthinkSevilleisagoodplacefor metolive 1.84 0.60 1.55 0.67 1.64 0.57 1.83 0.62 4.556 IfeelathomeinSeville 2.00 0.67 2.00 0.75 2.00 0.76 1.78 0.73 1.321 Peopleinmyneighbourhoodknow me 2.32 1.00 2.94 0.66 2.52 0.87 2.22 0.65 12.120** IhaveinfluenceoverwhatSeville islike 2.39 0.70 2.48 0.71 3.04 0.74 2.22 0.65 13.885*** IexpecttoliveinSevilleforalong time 1.89 0.66 2.88 0.86 2.60 0.93 2.00 0.77 20.519**** TotalMean 2.090.452.370.472.360.552.010.538.994* Allmeasuredona4‐pointscalewhere1=StronglyAgreeand4=StronglyDisagree *p<0,05;**p<0,01;***p<0,005;*******p<0,001 Ingeneral,respondentsfromIPTSweremorelikelytodisagreewithexpectingto liveinSevilleforalongtime.Thisseemstosuggestthatrespondentswhoarein transit,asincasewithErasmusstudentsandIPTSaremoresusceptibletoalower senseofcommunityandplaceattachmentwiththecitywherethey are living. Respondentswhoweremorelikelytobeintransitalsoclaimedtobetheleast knownintheirneighbourhoodsacrossourpopulation. Musiciansfromtheorchestradifferedsignificantlyinthewaytheyfelttheycould influence what Seville is like. During the interviews, musicians mentioned that throughtheirmusictheyfelttheycontributedtowardsthecultureofthecityand hence, positively influence the city. For example, a musician from the orchestra toldus: Ihaveaplaceinthissocietycauseofmywork.IthasavalueandI'm recognizedforthat. In contrast, people from IPTS, were the least likely to feel that they have an influenceoverwhatSevilleislike.ThefactthatErasmusstudentweremorelikely tofeeltheyhaveaninfluenceoverwhatSevilleislikethanIPTSpartnersis an unexpectedfinding.Influenceseemstobetheconstructinwhich respondents
136 fromthefourcommunitiesdiffereddependingmoreontheroleofthecommunity withinthelocation,ratherthanthetypeofmobility(durationofstay,time expectedtoliveinSeville,etc). HowwouldyousayyouareconnectedtoSeville? AlbeitthelowsenseofcommunitymeasuredbytheSCI,participants provided quitepositivedescriptionsofhowtheyconnectedtoSeville.Althoughinthisopen question,weavoidedpurposelyaskingrespondentsaboutnotionsofcommunity, as can be observed in the four diagrams presented below, various aspects of community life were mentioned by respondents. As reported by anErasmus student: Asoneofover2500ErasmusstudentsIamsortofpartofthecity.Ireally enjoyspendingtimewonderingthroughoutthecityduetoitsarchitecture andvividpubliclife” Various references related to integration were made by the respondents. “Our habitshavechanged:SpanishfoodatSpanishtime,bicycleinthecityandweare moreoutside”(IPTSpartner).Ascanbeobservedfromthediagrams,wordslike goingout,friends,family,streetlife,sociallifeandmarketareamongthefrequent termsusedacrossthefourcommunitiestorefertovariousaspectofcommunity lifeperceivedandexperiencedineverydaylife. Figure20:TagcloudofcommontermsusedbyFlamencoartists
137 Neighbours were also mentioned frequentlyasoneaspectofhowrespondents connectedtoSeville: NetworkisgettingbiggerasIliveherelonger,friendsoffriends…In my neighbourhood,there´sasenseofcommunity,butIdon’tknowaboutother neigbourhoods…whenitcomestoFlamenco,Iknowalotofthecommunity (Flamencoartist). Whenwelookatthetermsusedpercommunity,wecanobservedifferentwaysof howrespondentsfromthefourcommunitiesconnecttothecity.Flamencoartists seem to connect to the city mostly through affective ties: partner, friends of friends,professor,Spanishhostfamilyandchildren: People in Seville are very interesting, sociable and very open.Youcan minglewiththemeasily. TheyalsoclaimedtoconnecttoSevillethroughlocals.Indescribing locals, Flamencoartistsexpressedawidearrayofpositiveexpressions: Peoplehelpmealot.Igotoschoolbybike.Ihadaproblemwithmybike andpeoplehelpedmewiththebike.IfIdropsomething,peoplearereally helpful.Peopleareverykindandsweet. Erasmusstudentsseemtoderivetheirconnectiontothecitymorethroughtheir friends.Theyalsomadevariouscomparisonswiththeircountryoforigin,asaway ofspeakingpositiveaboutthelifeinSeville: Inthenorth,peoplehavetobeuseful.Here,Ifeelthesocietyislivingfor eachother.Thisfeelsbetterforme.Peoplearenotrushing. The short residence of students in Seville is reflected in how they felt they connected to Seville: monuments, history, architecture, streets,culture,artand music.Itseemsthattheshortstaymakesoneexperiencethecitymorefroma tourist’sperspectiveandcomparisonswithcountryoforiginarenatural.
144 relyingonPolyvalentsupportbyoldfriendsresembledthoseprofileswithSparse networks,withtheexceptionofthetimetheyhaveknowntherespondents. One profile clearly differed from the rest in terms of network composition: the Host type of profile. These respondents had the highest proportion of Spanish alteriandthelowestnumberofalteriincountryoforiginintheir personal networks, typical of respondentswhoaremoreintegratedinthe new location. This is further confirmed by the high place attachment score across all the differenttypologies.Thistypologywasdistinguishedbyrespondentswithahigh education and who are middle‐age and employment. They were morelikelyto havemovedtoSevillebecauseofwork.Butperhapsamajordistinguishingfactor isthattheyplannedtoliveinSevilleindefinitely. Figure27:SocialSupportTypologiesandNetworkProfilesaspernumberofAlteri 2 4 6 8 10 12 14 16 Spanish Countryof Origin Famil y Inthepast year SocialCompanionship NewSocialisingPals Polyvalentsupportby oldfriends Co‐presenceSupport DenseNetwork HostNetwork DistantNetwork SparseNetwork
145 5.4.3Ofpersonalnetworks,socialsupportandplaceattachment: AClusterAnalysis Utilisingmeasuresfrompreviousanalysisinthisdissertation,thefinalsectionof thisworkinvestigatestherelationbetweensocialsupport,personalnetworksand placeattachmentformobileindividuals(Figure28).Fourmeasureswereclusteranalysedusingthek‐method,namelynetworkstructureofpersonalnetworks, forwhichweexaminetheaveragedegreecentrality;networkcompositionof personalnetworks,wherebyweselectedthenumberofalterimentioned who reside in Seville;26 placeattachment to local community attachment;27 and intermediatesupport,asameasureofsocialsupport. 28Four different clusters wererevealedasthebestapproximationofthedistributionofourrespondents. Figure28:FrameworkofAnalysis The figures shown in Table 21 are the final cluster centres, on each criterion variableforeachofthederivedcluster.Eachclusterrepresentsatypeofmobile respondentbasedondataderivedfromherpersonalnetworkcomposition and structure,typeofsocialsupportderivedfromalteriandthelevel of place attachmentexperiencedwithSeville. 26 See Chapter 3 for more details on both network measures 27 As described above in this chapter 28 see Chapter 3 for detailed explanation of social support measures
146 Thefirstcluster(37%)istypicalofPeripheralSettlersrespondents.Thisprofileis characterstisedbylowplaceattachment,lowdensitynetworks,ahighnumberof alterilivinginSevilleandlowintermediatesupport.Transitparticipants(24%)are characterizedbythelowestscoreofplaceattachment,lowestnumber of alteri livinginSevilleintheirnetwork,amediumdensenetworkandalownumberof alteriprovidingintermediatesocialsupport. Table 21: ClusterCentresforNetworkCharacteristics,SCIandSocialSupport ( N =90) Peripheral Settlers (n=33) Transit (n=22) Rooted (n=23) Cohesive Settlers (n=12) Network Characteristics Structure:Average DegreeCentrality 19.86 32.21 30.59 51.55 Composition:No.ofalteri livinginSeville 14 7 17 16 SCI PlaceAttachment* 2.27 2.52 1.98 2.12 StrengthofSocial Support IntermediateSupport 5.48 5.59 9.48 7.08 *Measuredona4‐pointscalewhere1=StronglyAgreeand4=StronglyDisagree TheRootedrespondents(26%)haveahighlevelofplaceattachment,thehighest numberofalterilivinginSeville,mediumdensenetworksandahighnumberof alteriprovidingintermediatesupport.TheCohesiveSettlersparticipants(13%)are characterizedbytheirmediumscoreofplaceattachment,highlydensenetworks, high number of alteri mentioned living in Seville and medium number of alteri providingintermediatesupport. Themostfrequenttypeofmobileindividualsinourpopulationarethosewiththe PeripheralSettlerstypeprofile,followedbyTransitandRootedtypeprofiles,who arebothcharacterizedbymediumdensenetworks.Theleastfrequentwasthe Cohesive type profile. Subsequent analysis investigates how these four profiles differed in terms of network characteristics, frequent use of media with alteri, mobilitypatternsandsocio‐demographicvariables.
147 AswecanobserveinFigure29,Transittypeofrespondentsclearlydifferentiated themostfromtheotherclusterprofilesacrossallnetworkcompositionvariables Figure29:Networkcharacteristicsbyclustertype Locationofalteri.Locationofthealteridifferentiatedsignificantlythefourtypesof clusters,inthenumberofalterimentionedresidingincountryoforigin,χ2(3, N=90)=11.35,p=.01andinthenumberofalterimentionedresidinginanother location,χ2(3,N=90)=10.74,p=.01.ParticipantswithaTransitprofilementioned thehighestnumberofalterilivingincountryoforigin(M=15.05,SD=5.25)and thehighestnumberofalterilivinginotherlocationwhencomparedwiththeother profiles(M=8.05,SD=6.34). Nationalityofalteri.Thefourprofilesalsodifferedsignificantlyinthenumberof Spanish,χ2(3,N=90)=10.05,p=.01andcompatriotsχ2(3,N=90)=10.74,p=.01 mentioned.RootedprofileparticipantslistedthehighestnumberofSpanishalteri (M=9.26,SD=6.84)andthelowestnumberofcompatriots(M=4.23,SD=3.94). Conversely,Transitparticipantsmentionedthehighestnumberofcompatriots(M =19.36,SD=6.74)andthelowestnumberofSpanishalteri(M=13.39,SD=5.43). Ageofalteri.Two agebracketsdifferentiated the four clusters:number ofalteri listedwhoarebetween21‐30yearsχ2(3,N=90)=12.93,p=.01andnumberof alteri listed who are over 51 years χ2(3,N=90) = 19.14, p= .00. Transit participantsweremorelikelytolistyoungalteri(M=17.14,SD=1.77)andthe least likely to mention older alteri (M= 1.77, SD= 3.94). Cohesive respondents listedthehighestnumberofolderalteri(M=8.08,SD=5.84). 0 5 10 15 20 Countryof origin Other Spanish Compatriots 21‐30yrs Over51yrs Location Nationality Age Peripheral Transit Rooted Cohesive
148 Relationwithalteri: We found no significant difference between clusters in the numberoffamilyandfriendsmentionedastheiralteri.Cohesiveparticipantshada slightlyhighernumberoffamilymembersandTransitparticipantsahigher numberoffriends.Asmallsignificantdifferencewasobservedwithneighbours,χ2 (3,N=90)=8.11,p=.04,duetothelackofneighboursinTransitparticipants. Frequentcommunication.Transitparticipantsalsodifferedsignificantlyinfrequent face‐to‐facecommunicationwiththealteri,χ2(3,N=90)=11.96,p=.01.Cohesive respondents claimed to meet frequently face‐to‐face with almosthalfoftheir personalnetwork(M=14.33,SD=4.74)andRootedrespondentsmeetwithmore thanonethirdoftheirrespondent(M= 12.22, SD= 5.13). In contrast, Transit respondentsonlymetface‐to‐faceoftenwithonefourthoftheirpersonalnetwork (M= 8.77, SD= 5.46) and listed the highest numberofalteriwithwhomthey communicatesfrequentlythroughSNSalteri(M=10.14,SD=7.10),χ2(3,N=90)= 9.20,p=.03(Figure30). Figure30:Clustertypesbyfrequentcommunicationwithalterithroughdifferentmedia It is quite interesting that across the four clusters, SNS seemtobecomemore popularinfrequentcommunicationthanemail.Reflectingthemediadisplacement theory,itseemsSNSaretakingoveremailusageespeciallybyyoungrespondents. UsageofnewmediaisparticularlyseenbyTransitusers.Ontheonehandfrequent communication by SNS superseded face‐to‐face communication with their alteri 0 2 4 6 8 10 12 14 16 F2F Mobile Email SNS VOIP Peripheral Transit Rooted Cohesive
149 anddailyusageofIMconsistsofthreeormorehours.29.Inherresearchonusage ofSNSbyteenagers,boyd(2008)foundthatemailuseisindeclineamongstyoung usersbutinstantmessagingisontheincrease.Whileprivatemessagesthrough SNSarestructurallysimilartoemail,immediacyinfriendsseeingmessagesand replyinginstantlyhaspromptedyounguserstoshiftusagefromemailtoSNS. Whileemailseemtobetheall‐purposetoolforadults,youngusers useitfora muchnarrowersetofpurposes,mostlytocommunicatewithadults.Mostofthe young respondents in our study confessedhavingSNSopenallthe time their computerisswitchedon,nottomentionits24/7usethroughthemobilephone. Mobility. The relational community in the host location differentiated the four profiles, χ2(9,N=90) = 31.73, p=.01. Once again major difference was mainly caused by Transit participants, who were more likely to be Erasmus students (59%).Wealsoobserveaslightmajority,althoughlesssignificant, of orchestra musicians in the Cohesive profile (42%) and Flamenco artists inthePeripheral Settlersprofile(33%)(TableA6inAppendix1). Thefourclustersdifferedsignificantlyintermsofresidencelength,χ2(9,N=90)= 22.66,p=.01andtimeplannedtostayinSevilleχ2(9,N=90)=17.20,p=.05.Transit participants were more likely to have lived in Seville for less than a year and planningtostayinSevilleforashorttime.Cohesiveparticipantsdifferedinbeing dominatedbyrespondentstohavelivedinSevilleformorethan10yearsandfor moving to Seville for a change in lifestyle,χ 2 (12, N=90) = 22.13, p=.04. The majorityofPeripheralSettlersplannedtostayforafewmonths(36%),butalsoa goodproportionclaimedtostaybetweenoneandfiveyears(24%) and indefinitely (24%). Across the four clusters, studying was a major reason for movingtoSevilleforawiderangeofourrespondents.Workisalsopresentacross thefourclusters,butonamuchlesserdegreeinparticipantswithaTransitprofile. 29Transitrespondents’dailyuseofIMmadethemdiffersignificantlyfromtheotherclusters,χ2(12, N=90)=25.04,p=.02
150 SenseofCommunity.30Transitprofilesweretheleastlikelytorecognizepeople wholivedintheirneighbourhoodandtheleastlikelytoexpecttoliveinSevillefor alongtime.Transitprofilesalsoscoredthelowestinthemembershipconstruct andintheoverallsenseofcommunity.Incontrast,Rootedrespondentshadthe strongestmembershipandsenseofcommunityandwerethemostwhoclaimedto recognizemostofthepeopleintheirneighbourhoodandexpecttoliveinSeville foralongtime(TableA7inAppendix1). Demographics.Significantdifferencewasobservedintermsofageχ2(15,N=90)= 25.27,p=.05,legalstatusχ2(12,N=90)=21.39,p=.05andwhetherrespondents hadchildrenχ2(3,N=90)=12.68,p=.01.Transitrespondentsweremorelikelyto beyoung(21‐30years),whileCohesiverespondentsweremorelikelytobeolder (51‐60years).Rootedrespondents,whoscoredthestrongestsenseofcommunity, weremorelikelytobemarriedandhavechildrenconfirmingresultsbyprevious studies. An overall descriptive analysis of the different profiles derived is presented in Table21. 5.5Discussion Inthecontextofthecommunitylostthesis,thischaptersetouttoexamine the senseofcommunityexperiencedbymobileindividualsinSevilleandwhetherany relation could be identified in terms of their respective relationalmobility community. Our simultaneous analysis of community attachment, utilising two distinctmethods,showthatdependingonthemethodused,differentresultson senseofcommunitymaybeobtained. 30Two items from the SCI, the membership construct and the totalsenseofcommunity differentiatedtherespondents
151 Table 22. CharacteristicsoftheTypologies Description Networkcharacteristics,mobility, communicationanddemographics Peripheral Settlers Lowdensitynetwork Lowplaceattachment Lowintermediatesupport HighnalterilivinginSeville Mediumnofalterilivingincountryoforigin&other RelativelyhighnumberofSpanishalteri Lownumberofcompatriots Highnumberofolderalteri Morelikelytouseemailtocommunicatewithalteri Majority,residedinSevilleeitherfewyearsorover 10years Mostlyhavemovedforstudying SlightmajorityofFlamencoartists Transit Lowplaceattachment LownalterilivinginSeville Lowintermediatesupport Mediumdensenetworks Highestnalteriresidingincountryoforigin Highestnalteriresidinginlocationother Highestncompatriots LowestnSpanishalteri Listedmoreyoungalteri High nof alteri with whom they communicate throughSNS Frequentuseofnewmediawithalteri MostresidedinSevilleforlessthanayear PlanningtostayinSevilleforashorttime Mostlyhavemovedforstudying LowestSCI,membership MorelikelytobeErasmusstudentsandyoung Rooted HighnalterilivinginSeville Highintermediatesupport Highplaceattachment Mediumdensenetworks Leastnalterilivingincountryoforigin HighestnSpanishalteri Lowestncompatriots Differedinusageofblogs DiversifiedinthelengthofresidenceinSeville StrongestSCIandmembership HighestexpectationtoliveinSevilleforalongtime Recognisepeoplewholiveintheirneighbourhood Morelikelytobemarriedandhavechildren Cohesive settlement Highdensenetworks HighnalterilivinginSeville Medium intermediate support Mediumplaceattachment Leastnofalterilivinginlocationother Listedmoreolderalteri Higher nofalteriwithwhomtheycommunicate face‐to‐face Lowusageofemailwithalteri MajorityresidedinSevilleformorethan10years, but also a good proportion (33%) for less than a year MajorityplanningtostayindefinitelyinSeville,but 33%claimedtobestayingforfewmoremonths Morelikelytobebetween51‐60years Slightmajorityoforchestramusicians
152 The experience of sense of communitywhichemergedfromthequalitative analysis is remarkably different from the results derived from the SCI. Respondentsappeartobesusceptibletoalowsenseofcommunitythroughthe SCI,however,suchlowsenseofcommunityisnotreflectedinrespondents’ discourseonhowtheyconnectedtoSeville.Fromthequalitativeanalysis,welearn thatrespondentsinthisstudyexperienceawidearrayofcommunityattachment, whichsomehowisnotaccuratelycapturedbytheSCI,confirming findings by Mannarini&Fedi(2009)wherebythedifficultiesofreducingcomplexnarratives touni‐dimensionalmodelarediscussed. Thefrequentmentioningoftherelationalmobilitycommunitybyeachrespective groupandthelistingofothertypesofcommunitieswhichrespondentsfeltwere importantinconnectingthemwithSevillesuggestthatourparticipants,despite their mobile status, connected to a variety of communities in the host location. Moroever,throughthisanalysiswealsolearntthesignificantroleoftherelational communityinshapingthetypeof mobility experienced by our respondents. MusiciansfromtheorchestraandFlamencoartists,whoweremorelikelytohave livedlongerinSeville,scoredastrongerplaceattachmentthanErasmusstudents and IPTS respondents. For musicians fromthe orchestra, place attachment was based on their perception of having an influence over what Seville is like and recognitionintheirneighbourhoods.Thestrongplaceattachmentregisteredby FlamencoartistshadtodomorewiththeirhighexpectationtoliveinSevillefora longtime. Incomparingthesocialsupporttypologiesandthenetworkprofiles elicited in previous sections of this dissertation, the Host Network profile clearly differed fromtheothertaxonomiesacrossthefourmajornetworkcharacteristics measures.Respondentsinthisprofilewerecharacterizedbyahighproportionof Spanishalteri,lownumberofalterilivingincountryoforigin,higheducation,their mobilitywasworkrelatedandtheyplannedtoliveinSevilleforalongtime.This participantsscorednotonlythehighestplaceattachment,butalsotheywerethe onlyoneswhoingeneralagreedtheyfeltaplaceattachmentwithSeville.
153 Thesefindingssupportpreviousstudieswhichclaimapositiverelationbetween integrationofhostsinone’spersonnetworkandahighersenseofattachmentto thelocation.Fromthecomparativereviewbetweenthesocialsupporttypologies andpersonalnetworkprofiles,wefoundthatthehighnumberofSpanishalteri and the time planned in staying in the host location seem to be positively associatedwithahigherplaceattachment. Thisstudyalsosoughttofindatechniquetoclassifyasampleofmobileindividuals basedonthreemajor notionspresent incommunitypsychology:social support, place attachment and personal networks. The typologies derived,namely, PeripheralSettlers,Transit,RootedandCohesiveSettlersseemtoreflectdiffering degreesofmobilitypatterns. Rootedmobileindividualsweretheoneswhohadthestrongestplaceattachment and the strongest sense of community. These respondents had a high multiplex support,highnumberofalterilivinginSeville,highestnumberofSpanishalteri andweretheonestomostlyagreedinexpectingtoliveinSevilleforalongtime. Lowplaceattachmentwasreflectedintwotypesofclusters,PeripheralSettlersand Transit.TheTransittypesofmobileindividualweremorelikelytohavemovedto SevilleforadefinedshortperiodandweretheleasttoexpecttoliveinSevillefora longtime,hence,thelowplaceattachmentislogical.Thelowattachmentofthe PeripheralSettlers’ profiles is intriguing. Irrespective of the high number of Spanish alteri, they still scored low in place attachment. In this profile, only a quarterclaimedtostayindefinitelyinSevilleandmultiplexsupportwaslow. Respondents with Cohesive Settlers profile were few in our study,buttheyare interesting because they are also unique in various aspects. These mobile individualshavedensenetworks,highproportionofalterilivinginSevilleandyet place attachment is medium. While the majority has lived in Sevilleforalong period,thereisalsoaproportionthathaslivedforashortperiod. Fromthefourtypologieselicited from data based on personal networks, social supportandplaceattachment,theTransittypeofparticipantsstood out for differing substantially across various measures. With a personal network