Electronic copy available at: http://ssrn.com/abstract=2801064

QuantitativeMethodsforHumanRights:

FromStatisticsto“BigData”AntoineNouvetandFrédéricMégret

"Therearethreekindsoflies:Lies,damnedlies,andstatistics"-BenjaminDeisraeli,former

BritishPrimeMinister.I.TheUseofStatisticsinInternationalHumanRightsLaw.............................................................3IdentifyingGroupandIndirectDiscrimination................................................................................3EstablishingResponsibility.......................................................................................................................5TransitionalJustice.......................................................................................................................................6

II.ABigDataRevolution?................................................................................................................................7Detectingandtrackingsocietaltrends.................................................................................................8MappingSocialData..................................................................................................................................10ProducingEvidence...................................................................................................................................12

III.FromSmalltoBigData:PotentialandChallenges......................................................................13Openempowerment..................................................................................................................................13Accuracy,representativeness,andInterpretation.......................................................................15FromDetectiontoPrevention?.............................................................................................................19

Conclusion:ImplicationsforHumanRightsWork............................................................................20

Thefollowingpaperistheuneditedversionofachapterthatwilleventuallybepublishedinacollection.1Quantitativemethodsinhumanrightsrefertomethodsthatseektoharnessthepowerofnumbersandrelativelylargeamountsofdatatohighlightcertaintypesofhumanrightsviolations.Suchmethodsareobviouslynotexclusiveofotherapproaches(andinfact“somecombinationofquantitativeandqualitativemethodologiesprovidesadvantagesovereitheralone”)2butmayinsomecircumstancesprovideinsightsintohumanrightsviolationsthatfewothertoolscanapproximate.Theuseofquantitativemethodstoanalyzehumanrightsviolationsisaninterestingexampleofacontributionfromthesocialsciences—andfromtheboominhigh-technetworkedcommunications,morerecently—tothepracticeofhumanrights.Manyofthetoolsreliedonwerenotdevelopedspecificallywithhumanrightsworkinmind,andlongremainedonthemarginofitspractice.Thismaybebecauseofthetraditionalindividualismofrights,onewhichdidnotparticularlyrequirein-depthcomparativeorcross-societalanalysis.Itmayalsobebecauseofthedominationintheinternationalhumanrightslegalfieldofinterpretativeandnormativedebates,asopposedtotherelativelymurkierfactualworkofactuallydocumentingrightsviolations.Anditmaybebecauseofthedominationofabroad“qualitative”approachtodocumentingrightsviolations(e.g.:victiminterviews),onethatmayhaveshunnedfromtherelativelyvulgar1ResearchMethodologiesinLegalHumanRightsScholarship,(MartinScheinined.,forthcoming).2MollyK.Land,“DemocratizingHumanRightsFact-Finding”,inTheTransformationofHumanRightsFact-2MollyK.Land,“DemocratizingHumanRightsFact-Finding”,inTheTransformationofHumanRightsFact-Finding,406(PhilipAlstonandSarahKnuckeyeds.,2015).

Electronic copy available at: http://ssrn.com/abstract=2801064

actof“quantifying”theunquantifiable.Infact,socialscientiststhemselvesdidnotseemparticularlyinterestedinputtingsomeoftheirtoolstoworktostudythehumanrights“object,”perhapsbecausehumanrightsseemedtoraiseproblematicnormativeissuesthatwouldformapoorbasisforquantitativeanalysis.Nonetheless,onemayspeculatethatarangeoffactorshavemadelookingatrightsissueswithaquantitativelensincreasinglymoreappealing.First,thehumanrightsmovementisinfactnotconcernedonlywithindividualviolationsbutwitharangeoftrends,domesticbutalsoglobal,thatarehardtograspexceptthroughsomesortofquantitativeanalysis.Second,thegrowingimportanceofissuesofdiscriminationbetweengroupshasnecessitatedthedevelopmentofspecifictoolsthatcandetectandunderstandsocietalsourcesofrightsviolationswhichalsoarehardtograspwithoutunderlyingtrendsandpatterns.Third,thegrowingrecognitionofeconomicandsocialrightsmakesthedevelopmentofvariousquantitativeindicatorsanalmostinevitabledevelopment.Fourth,therecurrenceofmassivehumanrightsviolationsintheformnotablyofwar-timeatrocitiesandtheirprosecutionbeforeinternationalcriminaltribunalshasmadeatleastaccountingfornumbersofvictimsanurgentexercise.Fifth,“numbers”exerciseacertainfascinationandcanprovidepowerfulsignpoststotriggerinternationalactionandpolicychanges.3Asgoestheaphorism:What’sgetsmeasuredgetsdone.Finally,inthepastdecade,rapid(andstillemergent)developmentshaveaddedfurtherappealtotheuseofaquantitativelens.Increased“datafication”ofcommunicationsandmanyotherhumanactivitieshasmadetheuseofcomputationalmethods(aformofquantitativepractices)virtuallyinevitable.4Anddataitselfisbecomingmorereadilyavailable,tippingitsmarketbalancefromsupply-basedtodemand-based(thisalsodrivesexpectationsthatadequatelevelsofpolicyornormdevelopmentwillencompassquantitativedimensions).Thesevariousfactorsallappearandoverlapthroughoutthebelowpaper.Quantitativemethodsisanadmittedlyimmenseandvariedfield.Thischapterthereforeseekstopresentabasicandoverarchinginventoryofdifferentquantitativeapproachestohumanrightswork.Itdoesnotfocusexclusivelyonjudicialorevenstrictlyjuridicalmethodologies,butinsteadexaminesarangeofquantitativepracticesengagedinunderthehumanrightsbanner.Indoingso,thechapterexpandsthenotionofhumanrightsmethodstoincludearangeoftoolsthatcanbeused,withnormativegoals,byhumanrightsactors,includinglawyers,policyexperts,andactivists.Thechapterhastwoparts,whichreflectchronologicalchangesinthefield.Partoneexplorestheuseoftraditionalstatisticalmethodsforhumanrights,whichuntilthelastdecade,constitutedthebackboneofquantitativemethodsinhuman.Itisnotmeantasatechnicalintroductiontostatisticsbutratherasabroadoverviewoftheusesthatstatisticshavebeenputtointhehumanrightsfield.Thesecondpart,reflectingchangesspurredbythedigitalrevolutionandbeginninginthe2000s,focusesontheemergence3BrianRoot,"NumbersAreOnlyHuman:LessonsforHumanRightsPractitionersfromtheNumeracyMovement",inTheTransformationofHumanRightsFact-Finding,356(PhilipAlston&SarahKnuckeyeds.,2015).4Dataficationreferstothehereaspectsofourlivesaretransformedintocomputeriseddata,whichisincreasinglycommonasaresultofthedigitalrevolution.

ofhugeamountsofdatageneratedamongstotherthingsbytheInternet.Althoughthatdataisalsosubjecttostatisticalanalysis,itcomeswithitsownsetofanalyticalpracticesandpotentialimplicationsfortheworkofdetecting,highlighting,andpossiblydisruptingandpreventinghumanrightsviolations.Althoughbothsectionsaredistinct,theyareintrinsicallylinkedbyasharedquantitativeethos.Inthisway,readerswillbenefitfroma“bigpicture”assessmentofquantitativemethodsanditsevolutionaryarcoverrecentdecades.Thechapterisaimedatacademics,humanrightslawyers,developmentpractitioners,andhumanrightsactivists.Theincentivestoexploretheuses,bothcurrentandpotential,ofquantitativemethodsaresharperthanever:quantitativemethodsarearguablythefastestchangingandgrowingareaofhumanrightswork,bywayofthedigitalrevolution.Bigdataiseffectivelyshapinga“newnormal”inmyriadprofessions,andthereisnoreasontothinkthatthefieldofhumanrightsisexempt.Inthiscontextthefield’straditionalreluctancetowardsnumbersshouldbesurmountedtoharnessthepowerofstatisticalmethodstogreaterhumanrightsunderstanding,promotionandenforcement.

I.TheUseofStatisticsinInternationalHumanRightsLawStatisticsconsistsofsummarizingandanalyzingasetofnumericalfacts.Forpastdecades,thiswasbasedonprocessingdatasetscollecteddirectlyfromsamplesinthefield,andfromprintandanaloguesourcessuchasnewspapersandgovernmentarchives.Suchconventionalstatisticalworkconstitutedthebackboneofhumanrightsquantitativemethodsthroughouttheseyears.Thereisasignificantsocialscientificinterestindrawingonlargenumberstoestablishmacro-correlations,forexamplebetweencertaintypesofregimesandcertaintypesofhumanrightsviolations.5Thissortofworkshedslightonthebroaderfacilitativeconditionsofhumanrightscompliancebutthissectionwillonlysurveyinstancesofstatisticsbeingusedforlegalpurposes.Belowarethreeexamplesofhowhumanrightsprofessionalshaveleveragedstatisticalworkofthistype.

IdentifyingGroupandIndirectDiscriminationStatisticshaveaclearroleininternationalhumanrightsinestablishingcertainpatterns,mostlyofdiscrimination.Unlikemanyotherinternationallyprotectedrights,discriminationinvolvesthesometimessubtleunjustifieddifferentiatedtreatmentofcertainpersonsinrelationtoothers.Ifthediscriminationisblatantinalaworpractice,thenstatisticalevidencemayhaveatbestasupplementaryroletoshowthatthelawdoesindeedhavetheconsequencesitwasintendedtohave.Ifthediscrimination,asismostlikelytobethecase,isnotevidentonitsface(andperhapsnotevenintentional),thenstatisticsmayprovetheonlymeansofprovingthatdiscriminationisactually

5Therelevantliteratureistoovasttoreferencehere.See,forinstance,H.S.Park,Correlatesofhumanrights:Globaltendencies,9HUM.RIGHTSQ.405–413(1987);S.C.Poe&C.N.Tate,Repressionofhumanrightstopersonalintegrityinthe1980s:Aglobalanalysis,88AM.POLIT.SCI.REV.853–872(1994);ChristianDavenport&DavidA.Armstrong,Democracyandtheviolationofhumanrights:Astatisticalanalysisfrom1976to1996,48AM.J.POLIT.SCI.538–554(2004);DavidL.Cingranelli&DavidL.Richards,TheCingranelliandRichards(CIRI)humanrightsdataproject,32HUM.RIGHTSQ.401–424(2010).

happening.Statisticsarenottheonlymeanstoprovediscrimination,6buttheyoftenprovideparticularlyincontrovertibleevidencetothateffect.Asaresult,statisticshavelonghelpedshedlightonpatternsofindirectorsystemicdiscrimination.BodiessuchasCEDAWandtheCRChaverepeatedlyaskedstatestoprovidestatisticalinformationdisaggregatedsoastoevidencethesituationofwomenandchildrenrespectively.7Statisticshavehelpedtouncover,forexample,theparticularlyhighincidenceofviolenceagainstwomeninCanadainthecontextoftheexaminationofthatcountry’sreporttotheHumanRightsCommittee.8Theexaminationofacountry’shumanrightsrecordfrequentlyleadstocallsforthedevelopmentofmorefine-grainedstatisticstoputinevidencepracticesofdiscrimination.9Moregenerally,theHighCommissionerforHumanRightscompilesstatisticstoevaluatetrendsandpracticesinternationallythatmaytheninformnormdevelopment,forexamplerelatingtotheageofmarriage.10Moreambitiously,theOHCHRnowadvocatesa“Human-RightsBasedApproachtoData”andhasformulatedasetofobjectivesandstrategiestoguideglobaleffortsbygovernmentsandcivilsocietyforpovertyreductionandaddressingdiscrimination.11Indirectdiscriminationisnotoriouslydifficulttoestablish,somethingwhichtheEuropeanCourtofHumanRights(ECtHR)hasoftennoted,tothepointofrelaxingevidentiaryrules.12Determiningdiscriminationrequiresattentiontothewayinwhichalawisappliedinpracticetothedetrimentofcertaingroups,atasktowhichstatisticalmethodisuniquelysuited.IntheEUcontext,CouncilDirectives97/80/ECand2000/43/ECencouragepersonswhosuspecttheyhavebeendiscriminatedagainsttoadducestatisticalevidencebeforedomesticauthorities.TheEuropeanCourtofJusticehasacceptedsuchevidence.TheECtHRhasconsideredthat“whenitcomestoassessingtheimpactofameasureorpracticeonanindividualorgroupstatisticswhichappearoncriticalexaminationtobereliableandsignificantwillbesufficienttoconstitutetheprimafacieevidencetheapplicantisrequiredtoproduce.”13Thisiscrucialbecauseitshiftstheburdenofprooftotherespondentstate,effectivelycompellingittoprovethatameasureisnotdiscriminatory,inacontextwherethelackofdiscriminatoryintentisnotconclusive.AclassicexampleofindirectdiscriminationbeingprovedstatisticallyistheD.H.andothersv.CzechRepublicCase.CzechcitizensofRomaoriginallegedthattheywere6ECtHR,Opuzv.Turkey(no.33401/02),9June2nd(inwhichtheCourtacceptedthenotionthatwomenweremorelikelytofacedomesticviolenceinTurkeybasedonanAmnestyInternationalreportandintheabsenceofreliabledata).7CEDAW,acronymfortheConventionontheEliminationofallFormsofDiscriminationAgainstWomen;CRC,acronymfortheConventionontheRightsoftheChild8IndianandNorthernAffairsCanada,AboriginalWomen:ADemographic,SocialandEconomicProfile,(Summer1996).9AmnestyInternational,CanadaFollowUptotheConcludingObservationsoftheUnitedNationsCommitteeontheEliminationofDiscriminationAgainstWomen(2009),p.5.10UNStatisticsDivsion,“LegalAgeforMarriage”,(2012),online:<http://data.un.org/DocumentData.aspx?id=336>.11OfficeoftheUnitedNationsHighCommissionerforHumanRights“AHumanRights-BasedApproachtoData:GuidanceNotetoDataCollectionandDisaggregationtoLeaveNoOneBehindinthe2030DevelopmentAgenda”,(OHCHR2015).12Nachovaandothersv.Bulgari,ECtHR,Judgmentof6July2005.13ECtHR,DHv.CzechRepublic,ECtHR,Judgmentof13November2007(No.57325/00),para188.

placedinspecialschoolsforchildrenwithlearningdifficulties,whichresultedinsegregationandracialdiscrimination.AlthoughthelawonitsfacedidnotmentiontheRomaandmerelyintroducedatestofabilities,itwasarguedthatitresultedintheexistenceoftwoautonomouseducationalsystems,an“ordinary”oneforthemajorityofthepopulationanda“special”onefortheRoma.14AfterlosingbeforetheConstitutionalCourtandaChamberoftheECtHR,thecasewasreferredtotheGrandChamber.Theevidencedisclosedthat56%ofallpupilsplaceinspecialschoolswereRoma,andthatconverselytheRomarepresentedonly2.26%ofthetotalofnumberofpupilsinordinaryschools.EventhoughtheGrandChamberfoundthatthesestatisticsmightnotbeentirelyreliablebecauseofthelackofofficialinformationontheethnicoriginofpupils,theCourtconsideredthat“thesefiguresrevealadominanttrendthathasbeenconfirmedbothbytherespondentStateandtheindependentsupervisorybodieswhichhavelookedintothequestion.”15Statisticsusedtoprovediscriminationmaybeexistingofficialstatistics.Thesewilloftencarryanevidentweightintermsofreversingtheburdenorproof.16Interestinglysuchofficialstatisticsoftenexist,provingarelativelydamningpieceofevidenceagainstthestateproducedbyitsownadministration.ForexampleintheD.H.casetheCzechauthoritiescouldhardlyclaimlackofknowledgeofexistingpatternsofdiscriminationagainstRomachildrengiventhattheirownreportunderArticle25para.1oftheFrameworkConventionfortheProtectionofNationalMinoritiesindicatedthatbetween80and90%ofthepupilsinspecialschoolswereRoma.Anadvantageofofficialstatisticsistheyareoftennotbasedonsamplesbutonacensusoftheentirepopulation.Nonetheless,statisticscanalsobeproducedbyhumanrightsactivistsorlitigantsthroughnormalmeansofdatacollection,includingdevisingrepresentativerandomsamples.

EstablishingResponsibilityInadditiontobroadpurposesofhighlightingdiscrimination,statisticshavealsobeenusedformoreforensicpurposes,inthecontextofestablishingindividualcriminalresponsibilitybeforedomesticorinternationalcourtsforvariousatrocitycrimes.Internationalcriminaltrialsoftenraisecomplexissuesofdeterminationofthenumberofvictims,theiridentityandwhethertheywereintentionallytargetedassuch.ThefindingsoftheHumanRightsDataAnalysisGroup(HRDAG),agroupthathasbeenkeyinpopularizingastatisticalapproachinthehumanrightsfield,confirmedearlierqualitativeaccountsinChadofprisonerconditionsandhighmortalitywithintheSecurityDirectorate(DDS)prisons.AnanalysisofthousandsofdocumentsfoundinacacheattheabandonedheadquartersoftheDDS,17includingSituationJournalsanddeathcertificates,revealedthatthemortalityratewithintheDDSprisonsvariedfrom30per1,000to87per1,000prisoners.ThisratewassubstantiallyhigherthantheoveralldeathrateofChadinthe1970sand1990s,whichwaslessthan25per1,000.

14ECtHR,DHv.CzechRepublic,ECtHR,Judgmentof13November2007(No.57325/00).15ECtHR,DHv.CzechRepublic,ECtHR,Judgmentof13November2007(No.57325/00),para191.16Hoogendijkv.theNetherlands(dec.)(no.58641/00),6January2005.17RomeshSilva,JeffKlinger,andScottWeikart,“StateCoordinatedViolenceinChadunderHissèneHabré,AStatisticalAnalysisofReportedPrisonMortalityinChad’sDDSPrisonsandCommandResponsibilityofHissèneHabré,1982-1990”,(BENETECH,2010).

ThereportfoundthatdetaineeswithintheDDSprisonswereatleast16timesmorelikelytodiethanthegeneralpublic.TheHRDAGreportwasgiventoaBelgianjudgetoinformhispreparationofanindictmentagainstHabré.18Inadditiontoassessingthegrossnumberofvictimsofparticularepisodes,statisticalmethodsmayhelpinhighlightingthenatureoftheeventsthatledtosuchvictimizationandinparticularestablishtheircriminalcharacter.InthecontextofthetrialofformerYugoslavpresidentSlobodanMiloševićattheInternationalCriminalTribunalfortheFormerYugoslavia(ICTY)inTheHague,forexample,oneofthequestionswaswhetherpeoplefleeingKosovohaddonesobecauseoftheNATOstrikesorbecauseofcampaignofethniccleansingbyMilošević’s.TheHRDAGsubmittedareportthatwasenteredasatrialexhibit.BecauseKosovoAlbaniaborderguardshadactuallykeptarecordofrefugeesthatwentthrough,itwaspossible—bycreatingacomplexmodel—tocorrelaterefugeeflowsandexogenousevents.ThereportconcludedthatthemassexodusofrefugeesfromKosovowasnotcorrelatedtoNATObombingsbutinsteadseemedtorevealacentrallyorganizedcampaignbytheSerbgovernment.Thisinturnwouldprovecrucialinestablishingtheresponsibilityoftheauthorities.Anothergreatchallengeofinternationalcriminaljusticeisestablishingtheresponsibilityofcommanders,particularlyheadofstates.TheHRDAGhasusedstatisticstoestablishapatternofresponsibilityofHissèneHabréinChad.HissèneHabréclaimedthathewasnotawareofcrimescommittedbyhissecurityservices(theDocumentationandSecurityDirectorate,DDS).ThequantitativeanalysiscompletedbyHRDAGassessedtheretrievedDDSdocumentsagainstthedoctrine’smaincriteria(existenceofasuperior-subordinaterelationship,superior’sknowledgeofthesubordinates’crimes,andsuperior’sfailuretoact).ItfoundthatHabréhadreceived1,265directcommunicationsfromtheDDSaboutthestatusof898detainees,suchthathemusthaveknownabouttheirconditionsandsituation.Theanalysisofthedocumentflow“includedmorethan2,700administrativerecordsthattogetherillustrateaclearcommunicationandcommandlinkbetweenHabréandhisstatesecurityforce.”19

TransitionalJusticeStatisticsmayalsobeusedinabroaderwaytoestablishgovernmentalandsocietalresponsibilitiesintransitionalcontexts,beyondindividualguilt.Theymay,tobeginwith,helpdocumentpatternsofvictimization.Forexample,theTruthandReconciliationCommissionofCanadamadeuseofstatisticalanalysistodeterminewhetherthedeathrateinresidentialschoolshadbeenhigherthantheordinarydeathrateinCanada.TheCommissionestablishedthat“ThedeathratesforAboriginalchildrenintheresidentialschoolswerefarhigherthanthoseexperiencedbymembersofthegeneralCanadianpopulation.”20Infactuntilthe1940s,theratewas4.9timeshigher,dueinparticulartoachronictuberculosiscrisiswhichinturnevidencedthe

18MiguelCruz,KristenCibelliandJanaDudukovic,“PreliminaryStatisticalAnalysisofAVRCP&DDSDocuments–AreporttoHumanRightsWatchaboutChadunderthegovernmentofHissèneHabré”,(BENETECH,November4,2003).19HRDAG(summaryofChadinvestigationconductedinChad),online:<https://hrdag.org/chad/>.20FinalReportoftheTruthandReconciliationCommissionofCanada,VolumeOne,TheTruthandReconciliationCommissionofCanad(2015)92.

healthcrisisthataffectedtheaboriginalpopulationmoregenerally.ThelegacyofsuchsocialmiserycouldbemeasuredincontemporarytermsbydataprovidedbyStatisticsCanadaitself,whichfoundinonestudythat“14,225or3.6%ofallFirstNationschildrenagedfourteenandunderwereinfostercare,comparedwith15,345or0.3%ofnon-Aboriginalchildren”,21asituationthatledtheCommitteeontheRightsoftheChildtoraiseconcernsontheoccasionofthesubmissionoftheCanadianreport.Statisticsmayalsohelpdisaggregatevictimsbycategories,andintheprocesshighlightthepeculiardynamicsofatrocities.Forexample,theHRDAGhelpedtheLiberianTruthandReconciliationCommissionwithquantitativemethodology.Thereportcontainedinformationabout86,647victimsand163,615totalviolationsincluding124,225violationssufferedbyindividualvictims;39,376sufferedbygroups;and14byinstitutions.Itfoundthatoldermenwereatagreaterriskofbeingkilled,acounter-intuitiveresult.Itspeculatedthatthereasonwasthatyoungermenweremoreatriskofbeingrecruitedascombatants,andthereforesparedforthatpurpose.Finally,statisticalworkmayhelpapportionresponsibilitybetweengroups,aperennialissueinreckoningwiththepast.Forexample,thedatasuggestedthattheNationalPatrioticFrontofLiberia(NPFL)was“responsibleformorethanthreetimesthenumberofreportedviolationsasthenextclosestperpetratorgroup,theLiberiansUnitedforReconciliationandDemocracy(LURD),”amountingto“approximately40percentoftheviolationsreportedtotheTRC.”22TheTRCdatagatheringprocessalsoexploredstatisticsonexpectationsregardingfutureexpectations,ratherthanonlyfocusingonthepast.Thereportevidencedastrikingwillingnessbybetween50and70percentofrespondentstomeetwiththeperpetratorwhocausedtheirsuffering.Apracticeof“Forgiveandforget”alsoseemedtobefavouredbythemajority.

II.ABigDataRevolution?Fordecades,quantitativemethodsforhumanrightsboileddowntoleveragingstatisticsonprimarydatasetsmanuallygatheredinthefieldorfromprintoranaloguedatasets.23Whilstthiskindofuseofquantitativemethodshasachievedsignificantresultsinthepracticeofinternationalhumanrights,itisinpracticelimitedbythedifficultyofaccessingthedata,theprotractednatureofthatprocessandthechallengesinherenttosocialscientificmethods.Moreover,thestatisticalmethodssuggestedaboveallhavearetrospectiveandforensicnature:theyevidentlyseektoestablishhumanrightsviolationsafterthefactsanditisintheirnaturethattheycannotbedevelopedinrealtime.24Itisherethatthe“bigdatarevolution,”asithasbecomeknown,couldhavearadicaleffectoratleastsignificantlycontributetoshakinguptraditionalstatisticalwork.The

21FinalReportoftheTruthandReconciliationCommissionofCanada,VolumeOne,TheTruthandReconciliationCommissionofCanad(2015)186.22HRDAG(summaryofLiberiainvestigation),online:<https://hrdag.org/liberia/>.23Conceptdefined:Statisticsinvolvessummarizingandanalyzingasetofnumericalfacts.Statisticsareusuallyusedonaggregatesofdatatoolargetobeintelligiblebyordinaryobservation.24Theexceptiontothisisstatisticsondiscrimination,thatcanbeusedtodisruptongoinghumanrightsviolations—butstillthere,thecollection,processingandapplicationofstatisticscantypicallytakemonthsifnotyears.

buzzword“bigdata”generallyreferstotheexponentialgrowthofavailabledatainthelasttwodecadesasaproductofthedigitalrevolution.25Conceptually,bigdataisassociatedwithsoaringlevelsofconnectivityvianewandnetworkedInformationCommunicationsTechnologiessuchasmobilephoneandcyberspace.Today,forexample,therearemorecellphonesthanhumansonearthandconnectivityhassoaredfrom350millionpeoplein2000tonearly3.5billionasofNov2015.Bigdataalsoreferstothedigitalrevolution’smassiverecordingofhumanactivity—aseverydigitalphonecall,mouseclick,uploadanddownload,intheorycan(andoftenis)recorded.Furthermore,thisdataisinherentlyquantifiable,itsbuildingblocksmadeofsmalldiscreteunitscalled“bytes”.Infact,increasinglyallhumanactivitiesaredatafiedinawaythattheycanbeprocessedbycomputersforanalysis(forexample,thewayTwitterhasdatafiedstraythoughts).26TheInternet,itissaid,neverforgets.Theconsequenceoftheabovecombinationofconnectivity,datafication,andloggingisaveritabledatadeluge:Forexample,thereare200hoursofvideouploadedperminuteandthereismoredataproducedinthelasttwoyearsthanintheprevious3000yearsofhumanactivity.27Notonlyisthiscontinuouslogofhumanactivitywithoutprecedenceintermsofitsmassivequantity;itisalsoradicallymoreopenthanpreviouslarge-scaleregistriessuchasofficialgovernmentdataorCCTVcamerafootagethatremainedcentralizedandclosed-off.Italsoappliestosituationsofintensehumanrightsconcernssuchaswarzones.Forexample,theSyriancivilwarhasbeendubbed“thefirstYouTubewar”andhasinfactgeneratedmorehoursofonlinewarfootagethanactualhoursofcombatontheground.28Attheircore,bigdataanditsconcomitantdigitalrevolutionheraldatleastthreemajortrendsforquantitativepracticesandhumanrights:moredata,moreautomizationofanalyticalwork,andmorecrowd-sourcing.Inthissectionwepresentanumberofinnovativepracticesthathighlighttheinterplayofthesetrends.Theseoftengobeyondconventionalmethodsthatmightbeusedincourttoincludearangeoftoolsthatcanbeused,withnormativegoals,byhumanrightsactors,includinglawyers,policyexperts,andactivists

DetectingandtrackingsocietaltrendsThesocalledtransitionfromsmalltobigdatapresentsalluringnewopportunitiestodetectandexplorepatternsandtrendsusefultohumanrightswork(asopposedtofindingindividualincidentsofinterest).TheprizedexampleofbigdataforanalysisofsocialtrendsisarguablytheuseofGoogle’ssearchdata.Itusesrecordsfrompeople’sonlinesearchesonGoogle’ssearchengine.GoogledominatestheInternetsearchengine

25Howtodefinethebuzzwordbigdataishotlycontested.Variousstrictquantitativedefinitionsexist(forexample:Adatasetwithoverabilliondatanodes).Variousqualitativedefinitionsexist(suchasthedataset’sapproximationtocapturingtheentiredatapopulationweintendtomeasure,ortheinabilityfortypicaldatabasesoftwaretoolstoprocessdatabecauseitistoolarge,unstructured,andcomplex.Thischapteremphasizestheimportanceofthedigital.ThisissimilartotheUNOHCHR’sdefinition:“Extremelylargedatasetsassociatedwithnewinformationtechnologyandwhichcanbeanalysedcomputationallytorevealpossiblepatterns,trendsandcorrelations”(OHCHR2015).26“RiseofBigData”,ForeignAffairs(2013),online:<https://www.foreignaffairs.com/articles/2013-04-03/rise-big-data>.27StephenSprattandJustinBaker,“BigDataandInternationalDevelopment:Impacts,ScenariosandPolicyOptions”(InstituteofDevelopmentStudies,December2015)4.28TheCarterCentre’sSyrianMappingProjectdocumentedthistrendandhasmeasuredattimesinthecivilwar’sdurationanaverageofover600videosuploadedperdayfromthewar(Authors’interview,July2014).

marketinmostcountries.ThismeansthatGoogleusersgenerateastaggering40,000queriespersecond(overatrillionperyear).29TheallureinusingdatalikeGoogletofindandanalyzesocialtrendsisitsomnipresence:Anunfilteredpanocticumforallfacetsoflifefromsearchesforjobsortheday’sweather,toqueriesonextraordinaryissuessuchasviolentmasskillingsinParisorPeshawar.Whatismore,Googletracksnotonlysearchwords,butotherdataincludinguser’slocationviaIPaddresses,andthesedataarecombinedandanalyzedthroughautomatedcomputationalmethodstoderive,forexample,statisticalaveragesmadequickly,openly,andfreelyavailabletothepubliconplatformslikeGoogleTrends.30Googleattractedconsiderableattentionandgeneratedappetiteforitsdatawithitsapparentabilityin2008topredictthespreadoffluintheUSAtwoweeksinadvanceoftheconventionaldataandstatisticsgeneratedbytheUSCentreforDiseaseControlandPrevention(thelatter,basingitselfonrandomsamplingof“realworlddata”),basedonananalysisofsearchqueriesassociatedwithflusymptoms.Googledatahassincebeenusedtotacklemyriadissuesincludinghumanrights.Forexample,2014and2015studiesanalyzedthegeographicdistributionofracisminAmericatowardsAfricanAmericans.31MostlyusingfreeGoogleTrendsdata,theleadresearcherSethStephens-DavidowitzreviewedthesearchvolumeintheUSAforthediscriminatoryterm“nigger”.Google’ssearchdatafromtheUnitedStatesisdisaggregatedgeographically(bycountyandstate),whichallowedStephens-DavidowitztocorrelatethehighestvolumeofsuchsearcheswithregionstraditionallyassociatedwithracismtowardsAfricanAmericans(suchasAppalachiaandtheUSA’sDeepSouth).Asisthecaseforconventionalstatisticalworkcoveredinthischapter’sPart1,correlationdoesnot=causation.Forexample,itisnotclearwhytheterm“nigger”isusedmoreintenselyinthoseregions—however,suchstatisticalresultspointtopotentialproblemspotsinawaythattraditionalmethodslikeinterviewingpeopleonthestreetmightnot.32Incombinationwithmoreconventionaldatacollectionitmightputinevidencecertainstronggeographicandtemporalconnections.Andofcourse,suchwidelyavailablestatisticsopenthedoortomyriadresearchpossibilities—forexample,thefindingswereusedtoexploretheexistenceofacorrelationbetweentheseattitudesandhigherratesofAfricanAmericanmortality.33Morerecentlyandwiththeaimofexploring“realtime”events,similarGoogledatawasusedtoinvestigateracismandpotentialrace-baseviolenceagainstMuslimsinthehoursanddaysfollowingtheDecember22015SanBernardinoshootinginCalifornia.Theresearcherssearchedfor,andfound,acorrelationintheUSAbetweenanti-Muslim29InternetLiveStats,GoogleSearchStatistics(2016),online:<http://www.internetlivestats.com/google-search-statistics/>.30GoogleTrends,online:<https://www.google.com/trends/>.Ofcourse,thisraisesquestionsofauthenticityandrepresentativenessofdata,whichwillbeaddressedlaterinthechapter.31SethStephens-Davidowitz,“ Thecostofracialanimusonablackcandidate:EvidenceusingGooglesearchdata”(2014)118JournalofPublicEconomics26-40.32DavidAuerbach,“BigAnecdata”Slate(May62015),online:<http://www.slate.com/articles/technology/bitwise/2015/05/google_searches_and_racism_why_big_data_studies_don_t_explain_society_as.html>33DavidChaeetal.,“AssociationbetweenanInternet-BasedMeasureofAreaRacismandBlackMortality”(April2014)10:4PLoSONE,online:<http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0122963>.

searchesandanti-Muslimhatecrimesinthe2004-2013period.Theycouldbreakthesefindingsdownfurther,tothestateandeventothecountylevel,tofindpocketsofpotentialrace-basedviolentsentimentsinrealtime.Theauthorsofthestudysuggestthatthedatacouldeventuallyallowobserverstonotonlydetectconcentrationsofracism,butalsotorespondpre-emptivelytopotentialrace-based,forexampleastheresearchernoted:“Thedata(...)couldtellpolicechiefswhensendingacoptodoanextradrivethroughaMuslimneighbourhood,ormakingsurethatthetownmosquewassafeovernight,wouldbeagoodidea.”34Oneobviouschallengeintheswirlofbigdataissiftingthoughthe“noise”ofunrelateddata.Toaddressthis,researchersresorttoinnovativeBooleansearchestofilterthroughbigdata’smountainsoftext-basedcontent.35Forexample,Stephens-Davidowtizscreenedoutvariantspellingscommonlyusedinraplyrics,suchasnigga,thoughfalsepositivesmayremaininthedata.Otherresearchershavedecidedtomonitorhighlynichecontent–whichislesslikelytosurveybroadsocialtrends,andmorelikelytozero-inonextremefringesegmentsofsociety.AstudyofpubliconlinecontentbytheCanada-basedSecDevGrouponextremistWhiteSupremacistsfounditusefultominethephrase“the14words”,aversefromthebibleassociatedwithWhitesupremacistgroups.36TheuseofthesehighlytargetedphrasesinBooleanqueriesmeanthat,althoughlessfrequent,theyarealsolesslikelytobedrownedoutinnumerous“falsepositive”searchesandtheymaycorrelatemoreoftenwithactualeventsandattitudesofconcerntohumanrightsprofessionals.

MappingSocialDataBigdatacanbecombinedwithcommercialorevenfreelyavailableonlinerelationalmappingtoolstounderstandthesocialbackdroptohumanrightsphenomena.37AnexampleofthisVeryLargeScaleConversationMapping(LSCM)ofsocialmediaactivity,whichcandetect,mapandmonitorsocialrelationsamonggroups,conversations,particularmessages,andindividuals(forexample,tensofthousandsofmessagesandonlineaccounts).Forinstance,organizationsrangingfromGovernmenttoNGOshavebeengathering,organizing,andanalyzingthetotalityofcertainconversationsonpublicFacebookpagesoronTwitteraroundhumanrightsviolationsinSyria.TwitterandpublicFacebookdatacanbereadily“scrapped”onlineandisavailablefromthirdpartyvendorsandevenfromfreeapplications.38Thisdataisthenanalyzedbylocation,content,andactorstoidentifyrelevantcontent.Itcanthenbeprocessedinrelationalsoftwaretoidentifysocialnetworksandtheirrelations.Theresultis"verylargescale34EvanSoltasandSethStephens-Davidowitz,“TheRiseofHateSpeech”NewYorkTimes(Dec.122015),online: <http://www.nytimes.com/2015/12/13/opinion/sunday/the-rise-of-hate-search.html?smprod=nytcore-iphone&smid=nytcore-iphone-share&_r=0>.35Evenifformalizedinthe19thcentury,Booleanlogicremainspivotalinmuchoftoday’sbigdataprocessingduetoitsrecognitionbymyriad“electronicsearchingtoolsasawayofdefiningasearchstring”,ElmerRasmusonLibrary,“BooleanSearching”,online:<http://library.uaf.edu/ls101-bolean>.36The14wordsare“wemustsecuretheexistenceofourpeopleandafutureforwhitechildren”.See:“DetectingToxicContentusingOpenSourceSocialMedia:AContentCentricApproach”(TheSecDevGroup,2014),online:https://preventviolentextremism.info/sites/default/files/Detecting%20Toxic%20Content%20using%20Open%20Source%20Social%20Media-%20A%20Content%20Centric%20Approach.pdf37Anexampleofwidelyusedandfreesoftwareofthissortis“Gephi”,online:<https://gephi.org/users/>.38Forexample,oneleadingvendorofsuchdatais“GNIP”,online:<https://gnip.com/sources/>.

conversationmapping”thatcan,forexample,captureanimpressionofthetotalityoftheconversationinSyriaonTwitteroveragivenperiodoftimelinkedtoaserioushumanrightsissue,suchasamilitarycampaign.Thistypeofanalysiscanhelpidentifyandhighlightkeycommunicators(thedots),keymessages(thelines,thatconnectthedotstogether),andthecommunitiesofinterest(indifferentcolours).Theimagebelowforexamplecontainsover100,000messagesgeneratedfromnearly30,000users,anditsanalysisrevealsthepresenceofseveralmajorgroupsincludingAssadregimemembersandsupporters,armedanti-Assadrebels,non-violentNGOs,Kurdishresistancemovements,andInternationalmedia.39

Image:SyrianMilitants(FSA)andKurdishnetworkofTwitterusersemergingfromalocalizedJan2013armedclashbetweenbothsidesinRasal-Ain(NortheastSyria).ResearchconductedbytheSecDevGroup.Suchdatacreatesovertimeanindexofwhoarethekeycommunicators-whatdefinesaparticularcommunity.Researcherscanquery:Whereandwithwhomdoesviolentorextremistcontentresonateonline?Howdoonlinealliancesevolveoverthecourseofabattleorwar?Whichgroupsareactivelyengagedindisinformationonlinethroughtheuseof“botnets”?40Wheredoesfalsecontentonhumanrightsincidentsemergefromandwhichonlinecommunitiesdoitscreatorsassociatewith?Inaddition,someexpertsarguethatunliketraditionalinventoriesofbackgrounddataonactorsandnarrativesthatorganizationshavecreatedfordecadesandareusuallyformulatedonthebasisofsubjectmatterexperts,verylargescaleconversationmappingallowsthedatatospeakforitself.Theconcentrationofactorsandofmessagesinsuchanalysisisformednotonthebasisofanapriorihypothesessubjecttothebiasesofaresearcher,butratherbytherawlevelsofinteractionthatexistinthedataandasinferredthroughrelationalsoftware’sstatisticalanalysis.41

39SecDevGroupResearch,2013.40“WhatisaBotnet?”,MicrsoftSecurityIntelligenceReport,online:<https://www.microsoft.com/security/sir/story/default.aspx#!botnetsection>.41RaghebAbdo,“AssessmentofaForeignFighter’sTwitterTrajectory”(TheSecDevGroup,2014)3online:<https://preventviolentextremism.info/sites/default/files/Assessment%20of%20a%20Foreign%20Fighter%E2%80%99s%20Twitter%20Trajectory-%20Before%20and%20After%20Travel_1.pdf>.Still,thiskindofresearchraisesseveralquestionsonauthenticityandrepresentativeness,aswellasregardingthe

Thismappingofsocialbackgroundandchatterprovidesanewsetofeyesandearsaroundmacrophenomenasuchasconflicts.Importantly,thisanalysisofsocialmediacontentcanalsobeusedtoidentifyspecifichumanrightsorhumanitarianviolations(forexample,videofootageofthekillingofunarmedprisonersofwarortheuseofbannedclustermunitions)orhumanrightsrelatedcontent(forexample,theflowofillegalweapons).Thisdatacanthenbeminedtogenerateevidence,asexplorednext.Together,thesemethodsareespeciallyusefulincaseswhereauthoritieshavefewactualeyesandearsonthegroundsuchasSyria’scivilwar.

ProducingEvidenceWhiletheabovecanprovidevaluableinformationtohumanrightsprofessionals,itdoesnotdocumentactualhumanrightsviolations.Searching“killMuslims”onGoogleorthegeneralebbsandflowsoftheonlinestrategiccommunicationsofISISortheSyrianAssadregimegenerallyarenotuntothemselvespatternsofhumanrightviolations.However,aspractitionersaswellasacademicslikeJayAronsonandDanielNeilandFengChenhavenoted,thisbigdatacanalsobedrilledforpatternsorindividualcasesof“HumanRightsEvents”(HREs)orhumanrights-relatedevidence.42Critically—anddifferentlyfromstatisticalanalysis—forthediscoveryofsuchthe“needleinthehaystack”evidence,itisnotdecisivewhethertheHREsarerepresentativeoflargerphenomenon;whatmattersmostisthattheevidenceisaccurate.Oneexampleistheroleofanalysingsocialmediacontentsimilartothatinverylargescaleconversationmapping,buttodetectparticulardatapointsthatcanbeusedforevidence.Forexample,oneissueintheSyrianconflictistracingtheoriginofvariousweaponsthatfeedviolenceandhumanrightsviolations.Asoneprofessionalweaponstrackerputit,however,“thepathtoSyriacanbequitecircuitous,”hesays.“Unlessyouhaveafairlyrobustpapertrail,whichwedon’thave,identifyingthegovernmentortraffickingnetworksthatprovidedtheweaponsreallyisn’tpossible.”43Inthiscontext,forexample,theCarterCenterandCarnegieMellonUniversityusedanimagerecognitionscripttosweepthroughthevastquantityofvideosoftheSyrianconflicttodetectthepresenceofTOWATGMs(ananti-tankmissile).44Thisdatacouldthenbeautomaticallysetasideforfurtheranalysissuchasmapping.BecauseTOWATGMsarenotintheSyrianArmy’sstocks,anyoneusingonemusthaveobtaineditabroad.Thisgivesresearchersahinttodocumentthatsuchgroupsaregettingweaponsfromforeigncountries,andresearcherscanbeginmappingapatternofwheretheyare.Similarly,theanalysisofsocialmediachannelshasprovedkeytoidentifyingthesourceofMANPADSsmuggledintoSyriaprovidingconsiderablevisualevidencethatwasparticularlyusefulinacontextwherefewjournalistsandofficialobserverswereabletooperateonthe

“bias”generatedbythealgebrathatundergirdsanalyticalsoftwaresuchasGephi—issuesexploredintheconclusionandsectiononchallenges,below. 42FengChenetal,“Non-parametricScanStatisticsforEventDetectionandForecastinginHeterogeneousSocialMediaGraphs”,Proceedingsofthe20thACMSIGKDDInternationalConferenceonKnowledgeDiscoveryandDataMining(2014),1166.43MattSchroederin“Syrianrebelshavestockpileofanti-aircraftweapons”(SmallArmsSurvey,Aug192014),online:<http://www.swissinfo.ch/directdemocracy/small-arms-survey-report_syrian-rebels-have-stockpile-of-anti-aircraft-weapons/40562956>.44Authors’interviewwithCarterCenter’sSyrianMappingProject(2016).

ground.45Whiletheaboveexamplesfocusonweapons,thissortofevidence-discoveryinbigdataappliestomyriadotherformsofHREs:Warcrimes,sexualassault,crimesagainsthumanity,forexample,canalsobedocumentedonline.TheinnovationintheaboveisthatsiftingthroughthebigdatadelugeofdigitaldataallowsthediscoveryofHREsthatareotherwisenotreadilyfoundoffline.

Thepointisthatbigdata,evenifsimplytoovastforasingleresearcherorsmallteam,toexploremanually,canbefilteredthroughautomatedmethodssuchawordandimagefiltering,or,asdiscussedbelow,viacrowd-sourcing(anotherbigdatarelatedmethod).Importantly,onceindividualHREsareidentified,theycanbeverifiedandeventuallyusedincourts.46

III.FromSmalltoBigData:PotentialandChallengesWhilstitistemptingtofindthetransitionfromsmalltobigdataappealing,thisisadevelopmentthatmustbeanalyzedcriticallyandwithcaretounderstanditstruepotentialandsomeofitslimitations.ThereisnodoubtthattheriseofBigDataisrichwithchallengesaswellaspotential.

OpenempowermentBigdataforhumanrightscantransformhowdataiscollected.AsMollyK.Landputsit,newtechnologiesandtheirconcurrentdecentralizedtendencies“enablethecollectionofmuchmoreinformationthanispossiblewithtraditionaltechniques”which“relyheavilyoninterviewingvictims,witnesses,andperpetratorsasaprimarysourceofgeneratinginformationabouthumanrightsissues.”47Together,thisissueisbothonethatcanaffecthowevidenceiscreated,aswellashowitismanaged—andoftenbothoccuratonce:Forexample,adataplatformmaycrowd-sourceitscontent,aswellasutilizethepublic’scrowdsourcedlabourtoanalyzedata. Oneofthemostsignificantchangesbroughtaboutbybigdata,accordingtoMollyK.Landisthattheverynatureofhumanrightsfact-findingmaywellcometochange.Thisisbecausenewtechnologies:

…provideopportunitiesforordinaryindividualstoinvestigatethehumanrightsissuesthataffectthem.Thosewhowereformerlythe‘subjects’ofhumanrightsinvestigationsnowhavethepotentialtobeagentsintheirownright.Thisnewkindoffact-finding,whichIcall‘participatoryfact-finding’maynotbeaseffective

45“Syrianrebelshavestockpileofanti-aircraftweapons”(SmallArmsSurvey,Aug192014),online:<http://www.swissinfo.ch/directdemocracy/small-arms-survey-report_syrian-rebels-have-stockpile-of-anti-aircraft-weapons/40562956>.46Initiativesareontherisetofacilitatetheadmissibilityincourtsofsuchevidencedrawnfromsocialmedia’sbigdata.OnenascentexampleistheeyeWitnessproject,thatisdevelopinganappthatrecordsandbundlesmetadatainsocialmediasuchascoordinates,timeofday,authorandcameradata,nearbycelltowers,andnearbyWi-Fisignals.See,eyeWitnessProject,online:<www.eyewitnessproject.org/>.

in‘namingandshaming’statesandcompaniesthatviolatehumanrights,becausetheabsenceoftheimprimaturofanestablishedorganizationmayrendertheinformationcollectedvulnerabletocritique.Atthesametime….Participatoryfact-findinghasthepotentialtobefact-findingasempowerment–thecollectionofinformationanddocumentationoffactsasmeansforempoweringthoseaffectedbyabusestoadvocatefortheirchange.48

JayAronsongoesontocharacterizethesechangesasachallenge,inthattheydiminishtheformalhumanrightsfield,leadingtoan“increasingfragmentationofthefact-findingcommunity,wheretheboundaryoftheprofessionalandamateurcommunityisbeingblurred.”49Indeed,thesechangesareoftenhappeningoutsidetheboundsofformalhumanrightsinstitutions.Assomehaveargued,theincreasingscaleandscopeofquantificationisacceleratingfasterthaninstitutions’abilitytoadaptexistingrulesandnorms.However,perhapsthistrendisbestviewedasanexpansionofthehumanrightscommunity’swork,ratherthanafragmentation.Itishardnottoseehowsuchchangesinandofthemselvesreconnectwitharadical,grass-roots,anddecentralizedhumanrightsethos.50Atanyrate,seekingtoworkwithcrowd-sourcingtoleverage“thecrowd”maybemorefruitfulthanseekingtomanagetheprofessionalsilowithintheseachange.

Lookingahead,onebrightopportunitymaybehighlightedbytheHumanitarianSector(disasterandemergencyresponse).Thisconsistsofprofessionalizingcrowd-sourcedinitiatives.Forexample,withUN-backingaStandbyTaskForce(SBTF)andtheDigitalHumanitarianNetwork(DHN)wereformedfromdigitalvolunteersacrosstheglobethatcanrespondonshortnoticetoassistinemergencies.Nicknamed“digitaljedis”,theSBTFforexamplenumbersover1800individualsinover100countries.51Intherecent2015NepalEarthquake,withinaweek,morethat1200ofthesedigitaljedissiftedthrough35,000imagesand7,000tweetstoidentifybuildingandneighbourhoodsofKathmandumostatriskofprolongedcrisis.TheyevenleveragedafleetofUnmannedArialDrowns(UAVs).Thisresultedwithinaweekinover300relevantpicturesofdisasterdamagedisplayedonmapsavailabletoprofessionalsontheground.52Theresultoftheaboveis“theleadinginterfacebetweenestablishedhumanitariannetworks…[the]dinosaurs”and“theseverytech-savydistributed,veryagilevolunteergroups”,statesoneofthenetworks’founders,PatrickMeir.53Thesamecouldbedonewithhumanrightswork,werethepowerofthecrowdcouldbeleveragedwithexpertguidance(andawarenessandguidanceonimportantethicalquestionsandinter-institutionalexpertise),andmainstreamedintooperationalworksuchasinvestigations.

48MollyK.Land,“DemocratizingHumanRightsFact-Finding”,inTheTransformationofHumanRightsFact-Finding,400(PhilipAlstonandSarahKnuckeyeds.,2015).49JayAronson,“MobilePhones,SocialMedia,andBigDatainHumanRightsFact-Finding”,inTheTransformationofHumanRightsFact-Finding,442(PhilipAlstonandSarahKnuckeyeds.,2015).50Itisheretoothatitmaybepositivetoexpandthenotionofhumanrightsmethodsbeyondthesortofconventionalmethodsthatmightbeusedincourttoincludearangeoftoolsthatcanbeused,withnormativegoals,byhumanrightsactors,includinglawyers,policyexperts,andactivists.51StandbyTaskForce,online:<http://standbytaskforce.com/>.52“AForceforGood:HowDigitalJedisareRespondingtotheNepalEarthquake”(iRevolutions,April2015),online:<https://irevolutions.org/2015/04/27/digital-jedis-nepal-earthquake/>.53“CrisisMappingandtheDigitalRevolutioninHumanitarianDatawithPatrickMeier”(TheRobertStraussCentreforInternationalSecurityandLaw,November2015),online:<https://www.youtube.com/watch?v=7JgJ7xAq4m0>.

Accuracy,interpretation,andrepresentativenessDataabundance,ofcourse,isnotnecessarilysynonymouswithmoreacuityandinfactsomebigdatamaycreatecolossalproblemsofverification.Itissometimesclaimedthatbigdataisinasensemore“honest”inthatitisproducedinmassivelydecentralizedfashionandwithastrongexpectationofprivacy.Stephens-Davidowitz(aformerGoogleemployeehimself)whoauthoredthestudyonracismbasedonGooglesearch,forexample,hasarguedthatsuchdataactslike““aconfessionalbox”thatcangaugepublicsentimentoncontroversialviewsthatpollsandsurveyscannotalwayscapture—“SometimespeopletypejustrandomthoughtstheyhaveintoGoogle…Thesesearchestendtofeellikeconfessionals.They'readmittingthingsthattheymightnotwanttoadmitinpolitecompanyormightnottelltoasurvey.”54Nonethelessevenifbigdataismore“honest”(andfurtheraccessible)itmaymisleadandconfuseasmuch,ormore,thantraditionalsourcesofdata.RecentfieldresearchinPakistanforexamplerevealsthatitiscommonforFacebookuserstocreateandmanageseveralaccounts,allservingdistinctsocialpurposesandpersonas—andthatamplebehaviourthatwouldbeconsideredunrestrainedinothersocialcontexts,isdramaticallyalteredtherebylocalmores.55Withoutunderstandingthesecomplexnuancesintermsofusers’underlyingintentandidentity,itiswouldbehardforanoutsidertoinferobservationsonthebasisofadatasetmadeofsuchuseractivity.Further,bigdatacanbeplainlywrong.TheBostonMarathonexplosionin2013ledtoamassivespikeinsocialmediaactivityandwasa“casestudy”inhowdatageneratedbyordinarybystanderstocrisescanbethemostrapidsourceofinformation.However,ofthe8milliontweetsthatwentoutaroundthebombing,astoundinglyonly20%wereaccurate,asrevealedbyanextensiveexpostfactoanalysis.56Therealityisthatpeoplelie,overstate,areconfused,misrepresent,andparrotinformationandthisremainsunchangedandpotentiallyincreasedonline.The“crowd”isnotalwaysright,andoftenfarlessinsituationsofcrisis.Compoundingconcernsonaccuracy,inthecaseoftheBostonBombing,thecrowd-sourceddetectiveworkonpopularwikiplatformslikeRedditledtoa“witchhunt”wherepersonswereunfairlysingledoutandaccusedofwrongdoing.57Finally,behaviouronlineisoftenshapedbyproprietaryalgorithmscreatedbysoftwareplatformandthatarenotaccessibletopublicscrutiny.Thesealgorithmsdetermine,forexample,whatpeoplelookforonlineandwhatmessagestheysee.Forinstance,Googlesearchpatternsarebasedon“suggested”preferences,asisthecontentandfriendsFacebookusersengagewith.Searchresultscanchangedependingoncookies,countryof

54“WhatGooglecantellusaboutpeople’ssecretthoughts”(PRI,Jan32016),online:<http://www.pri.org/stories/2016-01-03/what-google-can-tell-us-about-people-s-secret-thoughts>.55EmrysShoemaker,“Digitalpurdah,orhowFacebookmaintainstraditionalpracticesofgendersegregation”(LSE,July2015),online:<http://blogs.lse.ac.uk/parenting4digitalfuture/2015/07/29/around-the-world-3/>.56ColinSchultz,“IntheWakeoftheBostonMarathonBombing,TwitterWasFullofLies”(Smithsonian.com,Oct2013),online:<http://www.smithsonianmag.com/smart-news/in-the-wake-of-the-boston-marathon-bombing-twitter-was-full-of-lies-5294419/?no-ist>.57Hueypriest(officialRedditmoderator),“ReflectionsontheRecentBostonCrisis”(Blog.Reddit,April2012),online:<http://www.redditblog.com/2013/04/reflections-on-recent-boston-crisis.html>.

origin,behaviourpatterns,andevenlaptopmodel.58Furthercomplicatingmatters,thealgorithmsandtheirparametersareuniquefromplatformtoplatform,andcanchangewithinthesameplatformdependingonauser’scountry.59What’smore,these“trafficrules”ononlinecontent’sflowcanandareregularlytweakedandchangedbythecorporationsthatruntheplatforms.60Thesenuancesarerarelyexplicitand,withouttransparency,arehardorimpossibleforresearcherstoaccountfor.Anotherconcernwithaccuracyistheriskoferroramongthosehandlingthedata.Dataisnotinandofitselfusableordoesnotspeakindependentlyoftheanalysisthatismadeofit.Traditionally,dataattheveryleastneedstobecodedaccordingtorelevantfunctional,geographic,temporalcriteria,basedonwhatoneislookingfor.TheexperienceoftheHRDAGinSierraLeoneshowssomeofthedifficultiesencountered.Forexample,howdoesone:

“avoidcountingcertainviolationstwiceunderdifferentlabels,tokeeptrackofmultipleperpetratorsofsingleviolations,ortounderstandhowonecansimultaneouslybeavictim,perpetratorandwitness.Forexample,whatdistinguishes“rape”from“sexualabuse”?Thetwocategoriesmustbedefinedclearlysothatpeopledoingthecodingapplythedefinitionsinastandardway.Thedefinitionmustbesoclearthatifthesamenarrativestatementisassignedtotheentirecodingstaff,theywillclassifyitinpreciselythesameway.”61

Problemsmaybecompoundedbythemultiplicityofthoseinvolvedinthecodingprocesstoensureconsistency(hencetheimportanceofatoolsuchasinter-raterreliability(IRR)).ThesemethodologicalproblemsarelikelytocontinuetohauntBigData-basedhumanrightsresearchandpractitionerswillarguablybehobbledbythesamelimitationsthathavelongmadestatisticalworkchallenging.Whiledataprocessingtoolslikealgorithms,scripts,androbotscansiftthroughmassivedatasetsfor“automated”factfinding,theirparametersneedtobeguidedbyqualitativefieldexperiencetobeeffective(oftenreferredtoas“fusion”teamsandmethodologies,combiningtechnicalexpertiseinbigdatawithqualitativesubjectmatterexpertise).Forexample,ifseekingcasesoftortureormurderinthecontextofMexico’snarcowaronthebasisofbigdatascrappedfromonlineactivity,specializedknowledgeofvocabularyoroftheonlineenvironmentisneededtoguidewhateverautomatedtoolwillbeused.62Itisinsufficienttoguidesuchtoolswithstockvocabularylike“torture”and“execution”ortolookupcontentonstandardsocialmediaplatformslikeTwitterandYouTube.Incaseslikethese,nicheonlineplatformslikeBlogdelNarcowillbecentraltouncovering

58Fordefinitionsofonlinetermssuchascookies,seeTechTerms.com,adictionarymaintainedbycomputerscientistPerChristensson,online:<http://techterms.com/definition/cookie>.59Forexample:“Googlestoresandreportsfinalsearchessubmitted,afterauto-completionisdone,asopposedtothetextactuallytypedbytheuser”and“Twitterdismantlesretweetchainsbyconnectingeveryretweetbacktotheoriginalsource(ratherthanthepostthattriggeredthatretweet)”.DerekRuthsandJürgenPfeffer(28Nov2014),“SocialMediaforLargeStudiesofBehaviour”346:6213Science1063-1064.60Id.61HRDAG(summaryofLiberiainvestigation),online:<https://hrdag.org/liberia/>.62AntoineNouvetandJamesFarwell,“StrategiccommunicationsandcyberspaceinMexico'sdrugwar”,inOpenEmpowerment:FromDigitalProtesttoCyberWar(RobertMuggahandRafalRohozinskieds.,2016).

HRE-relatedcontent,aswilldistinctlocalandconstantlyevolvingslang.63Finally,a“spiral”methodologyisappliedwherethehighlytailoredsearchparametersmustbeconstantlyreviewedinacontinuousiterativeprocess.FurtherhobblingresearchersandasPatrickBallhasnoted,humanrightsdataispreciselythekindofdatathatpersonstrytohideandthatislesslikelytobeonline.Bigdataanalysismethodsfromothercontextssuchasindustryandbusinesswillnotwork—acompanycananalyzeperfectlythemovementofitsgoodsalongasupplychain;suchprecisionisusuallyunimaginableiftracking,forexample,howmanypeopleweretorturedandkilledbyastate’ssecurityapparatus.64Therisksofmiscountingandmiscodingarevarious,ashasbeenoutlinedwithempiricalexamplesbyresearchersrangingfromIraqandSyria,toColombiaandtheUSA.65Atamoreconceptuallevel,quantitiesdonottellusmuchaboutgravity,orwhycertainviolationswerecommitted,orhowwearetoassessthemnormativelyeventhoughintheorythereisnoendtowhatamountinformationcanbecoded.Even“themostreadilymeasurable”violence,homicide(asremarkstheUNODCinitsannualsurveyofglobalhomiciderates),hasvastlimitationswhenexaminedforhumanrights-relatedpurposes.66AstheglobalmassatrocitypreventionspecialistBirgerHeldthasnoted,whenconductinganalysisforexampleofamassatrocity,itisimportantnotjusttoquantifythatpersonswerekilled,butthattheywereintentionallytargetedandpartofaspecificgroup,ratherthanunintentionallyshotincrossfire.67Whenrecordingtheamountofpeoplekilledbygunfire,researchersneedtodocumentnotjustpersonskilled,butintent.Howdoresearchersprogrammeanalgorithmforthatpurpose?Otherhumanrightsliketherighttoprivacyorfreedomofexpression,maybemuchhardertoassessquantitativelyunlessonecanidentifysomelimitedproxy(e.g.:casesofunauthorizedsurveillanceexecutedbythepolice,orwhereastudentwasaskedtoremoveherhijab).68Finally,alongsideaccuracyistheoftenoverlappingandinseparablechallengeofrepresentativeness.Thedifferenceisthatevenifalltheaboveconsiderationsonaccuracyandinterpretationwereadequatelydealtwithforveracity,theanalysismaystillmiss-leadgiventheunderlyingdataisnotrepresentativeofwhatusersimagineorpurportittobe.Theclassicwayofcorrectingforaccuracyisbyobtaininglargedatasamplesthatminimizeindividualdistortions.Theworkofstatisticiansishencetraditionallycharacterizedbythesearchforrepresentativesamples.Forexample,in63BlogdelNarcoisoneofthemyriadunofficial,butwidelyused,wikiplatformsdocumentingviolenceandrightsabusesassociatedwithMexico’snarcowar.Id.64PatrickBall,“DigitalEchoes:UnderstandingPatternsofMassViolencewithDataandStatistics”(DataandSocietyInstitutepresentation,March2016),online:<https://www.youtube.com/watch?v=KNnvZVKWas8>.65Id.66“GlobalStudyonHomicide”(UNODC,2013)9,online:<https://www.unodc.org/documents/data-and-analysis/statistics/GSH2013/2014_GLOBAL_HOMICIDE_BOOK_web.pdf>.67Authors’interviewwithBirgerHeldt(February2016).68Insomecases,thisisincreasinglypossible:Forexample,organizationsliketheUniversityofToronto’sCitizenLabseektoapplyempiricalmethodsto“watchthewatchers”andmeasure,forexample:theflowofinternettrafficintocountriestodetectandinvestigatepatternsofcensorship;computerattacksonwebsitessuchasDDOSattacksnumberingintheorderof100,000s;ortotrackpatternsofsurveillanceofinternetservers.“FiresideChat:RonDeibert,EdwardSnowden&AmieStephanovich”(RightsConConferencepresentation,2016),online:<https://www.youtube.com/watch?v=yGDqXokPGiE>.

Guatemala,discoveryofmassivepaperarchivesoftheNationalPoliceArchivescouldnotbeexaminedmanually,astheynumbered80milliontextrecords.Instead,statisticalsamplingofthedocumentswasappliedtofindarepresentativesampleoftheircontent.69IstheuseofBigDatainsteadofstatsbetter?Ismorebetter?Thesizeofthesedatasets,somelikeVictorMayer-SchonbergerandKennethCukierargue,meanstheyresultinarepresentativesnapshotofhumanactivity.70Somepunditsevencontendthatdatasetswilleventuallybecomplete;suchdatasetswillcapture“allthethingsintheuniverse”weintendtomeasure,whatinstatisticalterminologymeansN=All.Indeed,somehavearguedthatbigdatamighteventuallyleadtotheendofstatistics.Whyselectasample,whentheentiredatapopulationisavailable?Whytestahypothesisonwhat’sgoingon,whenthedatacanspeakforitself,live,onwhatishappening?Theideaisthatflawsinrepresentativenessgetdrainedoutinthesheersizeofthesamples.Inpractice,forthemostutopianamongbigdataenthusiasts,bigdatawouldprovideapseudo“census-like”snapshotavailableliveandanytime,thusdoingawaywithmuchofthepainstakingworkthathistoricallymadeupstatisticssuchasthoseinGuatemala.71Long-timeexpertsontheuseofstatistics,likeMeganPriceandPatrickBallcontendthattherealityisfarmorecomplex.BigDataisnotthe“fullpopulation”.Onecancasuallyobservethatthereachofmobilephones,Facebook,orGoogleisomnipresent—butintheliteralsense,theyarenot.Socialmedia’sbigdataisanaptexample:alotofthepopulationofinterestisnotonlineandimportantbiasescanbebuiltintothedataasaresult.Tosuggestthatbecausemanyareonline,thesamplefrombigdataisrepresentativeofthebroaderpopulation,createsvariousproblems.Inshortwhenitcomestorepresentativeness,moredatadoesnotmaskadatabias.72Indeed,PatrickBallcontendsthattheargumentthatbigdataleadstomoreaccuratefindingsisadebatethatwasasalreadyarguedandsettled80yearagobytheleadingmathematiciansofthetime—itdoesnot.Whatmattersnow,likethen,isimprovedsamplequalityandthe“probabilitymodelusedtolinkthesampletotheworld”.73Ultimately,quantitativeanalysisisonlyasgoodasthedataitrelieson.Whilstthemassiveavailabilityofspontaneouslygenerateddataasaresultofcyberspacemayseemlikeaboonforthedevelopmentofhumanrightsresearch,itcreatesmethodologicalcomplicationsofitsown.Thereisnoavoidingthatdependingontherelativebreadthanddepththatanyanalysisofhumanrightsviolationsseekstoachieve,trade-offswillexistbetweenquantitativeandotherresearchmethods.74

69DanielGuzmán(2011),“SpeakingStatstoJustice:ExpertTestimonyinaGuatemalanHumanRightsTrialsBasedonStatisticalSampling”,24:3CHANCE23-29.70VictorMayer-SchonbergerandKennethCukier,BigData:TheRevolutionThatWillTransformHowWeLive,WorkandThink(2013).72PatrickBallnotesthatsocialmediadatausedinresearchisoften“collectednonrandomly”andconstitutesasortof“conveniencesamples”.PatrickBall,“TheBignessofBigData”,inTheTransformationofHumanRightsFact-Finding,428(PhilipAlstonandSarahKnuckeyeds.,2015).73438,Id.74M.Satterthwaite&JusticeC.Simeone,"AConceptualroadmapforsocialsciencemethodsinhumanrightsfact-finding",inTheTransformationofHumanRightsFact-Finding,344(PhilipAlston&SarahKnuckeyeds.,2015).

FromDetectiontoPrevention?Anotherimplicationoftheriseofbigdatainhumanrightsworkistheincreasingpossibilitytodisruptandpreventhumanrightsviolations,ratherthanonlyreactex-postfacto.Inadditiontochangingwhereandhowhumanrightsdataiscollected,bigdatacouldalsoaffecttheentiresequencingbehindhumanrightsdataprocessing.Thebigdatarevolutionmeansafasterdatacollection,analysis,anddisseminationcyclethatcanaltertherelationshipbetweenincidentsandactions.Whilemostuseofdatadiscussedsofarbothinpartoneandparttwohasbeenforensicandretrospectiveinnature,theincreasedspeedenabledbycyberspacemeansdatacouldbeusedtodetectandevenpossibly,predictandpreventfuturehumanrightsviolations.Datacanbeminedforpatterns,andpatternsanalyzedfortriggers,withstatisticalmethodsusedtoderivesomepredictiveknowledge.Possibilitiesaboundandmaybeunavoidable.Forexample,itbearsmentionthatoutsidetheboundsofformalhumanrightswork,civilsocietyandotherwilluserapidlyaccessibledatafromsocialmediaorothermeanstoshedlightonHREs.CorporationssuchasGooglearealreadyapplyingtheirsearchpatterndatatoredirectpotentiallyviolent“IslamicState”searchbehaviourtowardsresultsfocusedonextremismpreventionmaterial.Inreal-time,GooglesearchdatainbecomesnotonlyasourceforHRE-relateddata,butalsothemediuminwhichinterventionsareimplementedtopreventfutureHREs.75Theimplicationsofnewactors,whethercorporateorgrassroots,beingableinthefuturetotakethefront-stageinreactingtohumanrightsissuesmeritsreflection.Asexcitingasthisprospectsounds,threecaveatsbearmention:First,itappearsthatmoreevidence,availablemorequickly,doesnotofcoursenecessarilymeanmoreaction.Forexample,eventhoughithasbeenfrequentlypositedthatlightingonstreetscanreduceinstancesofstreetcrime,76itisnotclearatallifthisprincipleappliestothe“internetspotlight”castonhumanrightsviolationslikeSyria’scivilwar.77Secondly,therobustnessofthedataonwhichprojectionsandtrendanalysiswouldbeneededforeffectivepre-emptivework—anissuediscussedfurtherbelowundertheinterlinkedissuesofaccuracyandrepresentativeness–wouldbekey,inacontextwheretrendsandpatternscannoteasilybeequatedwithhardfacts,andtheriskofmanipulationslurks.Thirdly,creatingthetypeofindicatorsthatcouldcapturethedesiredtrendsischallenging.AsAronsonpointsout“todetectabnormalityonemusthavesomepictureofnormalbaselineconditions”.78Compoundingthedifficultiesofcollectingsucha

75MenchieMendoza,“GoogleToCounterRadicalizationByServingAnti-ISISAdsAsResultsToExtremistSearchQueries”(TechTimes,Feb2016),online:<http://www.techtimes.com/articles/131042/20160206/google-to-counter-radicalization-by-serving-anti-isis-ads-as-results-to-extremist-search-queries.htm>.76Forexample:“24/7electricityboostsjobsandreducescrime”(WorldBank,Aug2015),online:<http://www.worldbank.org/en/news/feature/2015/08/27/lese-crime-more-jobs-thanks-to-electricity>.77Indeed,thenotionthatSyria’sis“thefirstYouTubewar”(generatingunprecedentedhoursofnear-realtimecoverageonline)hasclearlynotresultedinarestrainedorshortconflict.78JayAronson,“MobilePhones,SocialMedia,andBigDatainHumanRightsFact-Finding”,inTheTransformationofHumanRightsFact-Finding,447(PhilipAlstonandSarahKnuckeyeds.,2015).

baselinearetherisksofarbitrarilycodifyingdata,giventheperennialrealitythatlocalandglobalunderstandingofwhatconstituteshumanrightscandifferentiatevastly.79Warningunitsalreadyexitswithinvariousinstitutionsformassatrocitycrimes,includingtheUN’sofficeforGenocidePrevention(OSAPG).However,theOSAPGwithitsroughly150early-warningindicatorsofatrocitycrimeshasoptedentirelyforqualitativemetricsbecauseithasnotfoundreadilypossiblemeanstoconvertthesetoquantitativemeasures.80

Conclusion:ImplicationsforHumanRightsWorkQuantitativemethodshavearelativelyrecentpedigreeamonghumanrightsmethodologiesbutseemincreasinglyusefulinthecomplexworldofdomestic,transnationalandglobalrightsviolations.Theuseofquantitativemethodsinhumanrightsisclearlyontheriseandthereisreasontowelcomethis.Suchmethodsoftenaddalayerofbreadthandunderstandingtowhatmayotherwisebeundulyanecdotal.Theyalsomodifyevidentiarypracticesincludingburdensofproof,thenatureoffact-finding,andeventheveryrelationshipofhumanrightsenforcementwithtimeandplace.Inthiscontext,bigdatarepresentsbothcontinuityandradicalchangeforquantitativepracticesengagedunderthehumanrightsbanner.Howradicalthechangeitportendsremainsamatterofsignificantspeculationatthisstage.Itmaybethatquantitativemethodsareparticularlysuitedtocertaintasks.Itistritetosay,forexample,thatquantitativemethodsmeasurewhatisquantifiable.Theythusseemnaturallysuitedtoassessingthenumbersofcasualtiesinanarmedconflictandasaresultshedlightonitsdynamics;orahiddensituationofindirectdiscriminationonwhichstatisticsshedacrudelight;orindetectingemergingpatternsofhumanrightsviolationsthroughanalysisofbigdata.But,precisely,noteverythinginhumanrightsisquantifiable,oratleastnotinawaythatwouldavoidtheimpoverishmentofthediscourseofhumanrights.Quantitativemethodsmaybeuniquelysuitedtoevaluatinghumanrightsthatcanbeunderstoodintermsofhavingbeenrelativelystraightforwardlyviolatedornot,forexamplepersonsbeingunlawfullykilledinthecontextofacampaignofviolence.Onepotentiallyperniciousconsequenceofanexcessivefocusonthequantifiablewouldbeafocusonthoserelativelyfewviolationsthatlendthemselvesmoreeasilytoquantitativemethodology:suchaprocessmightevenreinforceprejudicesaboutcertainrightsbeingnon-enforceable,aspirationalornon-justiciable.Indeedtheremaybesomethingabitdiscomfortingaboutthenarrowpositivismofquantitativemethods,somethingunappealingaboutnumbercrunchingforitsownsakeifthatiswhatisinvolved.Quantitativedata,especiallyinviewofitspower,needstobereadandunderstoodcarefullysoasnottobemadetosaymorethanitcanactuallysay,andcannotbeasubstituteforqualitativemethods.Itrequiresonetointerrogatethemethodologybothasregardsdatacollectionandanalysis.Evenasapparentlysimplea79Thisparadoxofhumanrightsmeasuresisexploredindepthin:TheHumanRightsParadox:UniversalityandItsDiscontent(ScottStrausandSteveJ.Sterneds.,2014).80“FrameworkofAnalysisforAtrocityCrimes”(OSAPG,2014),online:<http://www.un.org/en/preventgenocide/adviser/pdf/framework%20of%20analysis%20for%20atrocity%20crimes_en.pdf>.

questionaswhatconstitutesahumanrights“violation”mayinfactleadtomultilayereddefinitions,thatwillthenhavetobrokendownforcodingpurposes,leavingampleopportunityforinterpretation,error,overlap,etc.Biasisaconstantfeatureofquantitative,andnotjustofqualitativeinvestigationandmaybeparticularlyatworkgiventheclandestinenatureofmanyhumanrightsviolations(sothatquantitativeanalysismaycontributetomakeevenmorevisiblewhatisalreadymostvisibleandviceversa).

Thisallgoestoshowthatforallthepotentialandusesofbigdatalistedinthischapter,wearestillverymuchinanageofproofsofconcept.AsLetouzé,Meier,andVincknote,systemssuchastheseareoften“bestcharacterizedby[theirpotentialratherthanby[their]trackrecord”.81TheUNhasalsoinsistedthat,inthecontextofdevelopment,thepromiseofbigdata“willbebestfulfilledwhenitslimitations,biases,andultimatelyfeaturesareadequatelyunderstoodandtakenintoaccountwheninterpretingthedata”.82Indeed,humanrightspractitionersmustrecognizethedouble-edgednatureofthesechanges:AsnotesAronson:“themajorcaveats…arethatmerelygatheringandanalyzingthisinformationdoesnotguaranteeitsutility(indeedsuchendeavoursmayleadtofalseormisleadingconclusions),andthathumanrightsabusersandrepressivestatesoftenhaveaccesstothesame(orbetter)toolsandtechniquesthanhumanrightsadvocatesandinvestigatorsdo.Thus…socialmediaandbigdataanalysiswilllikelybeaproverbialdouble-edgedswordthatbothenhancesanddetractsfromourabilitytoprotectandpromotehumanrights”.83Naturally,thesestrengthsmayalsoposerisks,asgovernmentstakeincreasingcontroloftheweb.Still,ifinternationalhumanrightslawisnottobecomeanexclusivelyandnarrowlyadjudicativeenterprisefocusedonindividualviolationsandistobeseenaspartofglobalprocessesofgovernancegearedtowardsmaximizingrightsthroughcarefullycalibrateddataonwhereandwhenharmsoccur,thenquantitativemethodsindisputablyhaveaplace.Takeanapparentlyeminently“qualitative”issuesuchastheabilitytowearthehijabinaTurkishuniversityintheLeylaŞahinv.Turkeycase,onecriss-crossedbycompetingdiscoursesoffreedomofthought,religion,secularism,terrorism,genderequality,etc…Onemightthinkthatsuchissuesareonlytherealmofcarefulprincipledreasoningfromthelaw,withattentionatbesttoindividualfacts.Yettherecouldhavebeenaplaceforquantitativeanalysiseventhere.TheTurkishgovernmentclaimedthattherewasaconnectionbetweenthehijabandproselizitinginwaysthatmadenon-practicingstudentsfeelthreatened,andperhapsevenalinkwithterrorism.ThisisaclaimthattheECtHRwasbasicallyreadytoacceptatfacevalue,butitisonethatcouldhavebeendissectedfromastatisticalperspectivetoseeifitrestedonanythingelsethanpoliticalprejudiceandexpediency.Whatistheproportionofstudentswhowearthehijab,whatpercentageofthemisinclinedtoproselitizeorevenbepoliticallyactive,howmanytoradicalize,andwhatproportionofstudentsislikelytoactuallyfeelintimidated?Indiscussingtheseissuesasissuesofbroadpolicynotneeding

81EmmanuelLetouzé,"Bigdatafordevelopment:challenges&opportunities"36(UNGlobalPulse,2012),online:<http://www.unglobalpulse.org/sites/default/files/BigDataforDevelopment-UNGlobalPulseJune2012.pdf>.8236Id.83JayAronson,“MobilePhones,SocialMedia,andBigDatainHumanRightsFact-Finding”,inTheTransformationofHumanRightsFact-Finding,444(PhilipAlstonandSarahKnuckeyeds.,2015).

tobeinformedbyquantitativedata,theECtHRwasarguablyledtodeferexcessivelytoTurkey’smarginofappreciationandreifyanumberofimplausiblegeneralities.Atanyrate,thechangesheraldedspeciallybythedigitalrevolutionandbigdatamaysimplymakeengagementofquantitativemethodsunavoidable.Theincreasingscaleandscopeofquantificationisacceleratingfasterthaninstitutions’abilitytoadaptexistingrulesandnorms.Concernsaboutaccuracyandrepresentativenessareunlikelytocurbtheappetitetoapplystatisticaltoolstobigdatasourcesforhumanrights.Thechallengesofsamplevalidityandrepresentativenessarehardlyuniquetodigitaldatathatconstitutesmostbigdata.Ultimately,perhapsthebestthingthatcanbesaidofquantitativemethodsininternationalhumanrightsisthat,asonecoursedescriptionputit,they“providecertainkindsofanswerstocertainkindsofquestions.”84

84PersonalwebsiteoflegalscholarToddLandman,online:<www.todd-landman.com/quantitative-methods-for-human-rights-research>.