{"id":"https://openalex.org/W3009975871","doi":"https://doi.org/10.30844/wi_2020_q2-schmalenbach","title":"Does Data-Driven Recruitment Lead to Less Discrimination? \u2013 A Technical Perspective","display_name":"Does Data-Driven Recruitment Lead to Less Discrimination? \u2013 A Technical Perspective","publication_year":2020,"publication_date":"2020-03-06","ids":{"openalex":"https://openalex.org/W3009975871","doi":"https://doi.org/10.30844/wi_2020_q2-schmalenbach","mag":"3009975871"},"language":"en","primary_location":{"id":"doi:10.30844/wi_2020_q2-schmalenbach","is_oa":false,"landing_page_url":"https://doi.org/10.30844/wi_2020_q2-schmalenbach","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"WI2020 Zentrale Tracks","raw_type":"book-chapter"},"type":"book-chapter","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5079258967","display_name":"Kian Schmalenbach","orcid":"https://orcid.org/0009-0007-0194-6841"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Kian Schmalenbach","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5058015959","display_name":"Sven Laumer","orcid":"https://orcid.org/0000-0002-9430-5774"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sven Laumer","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5079258967"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5221,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.63596491,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1649","last_page":"1664"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.8834999799728394,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.8834999799728394,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11161","display_name":"Consumer Market Behavior and Pricing","score":0.8784000277519226,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10991","display_name":"Game Theory and Voting Systems","score":0.8776999711990356,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.7985010743141174},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6748024225234985},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6352202296257019},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.610504686832428},{"id":"https://openalex.org/keywords/lead","display_name":"Lead (geology)","score":0.5006074905395508},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.4945501983165741},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.4914759397506714},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4282224178314209},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42698901891708374},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3821659982204437},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.06940627098083496}],"concepts":[{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.7985010743141174},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6748024225234985},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6352202296257019},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.610504686832428},{"id":"https://openalex.org/C2777093003","wikidata":"https://www.wikidata.org/wiki/Q6508345","display_name":"Lead (geology)","level":2,"score":0.5006074905395508},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.4945501983165741},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.4914759397506714},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4282224178314209},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42698901891708374},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3821659982204437},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.06940627098083496},{"id":"https://openalex.org/C114793014","wikidata":"https://www.wikidata.org/wiki/Q52109","display_name":"Geomorphology","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.30844/wi_2020_q2-schmalenbach","is_oa":false,"landing_page_url":"https://doi.org/10.30844/wi_2020_q2-schmalenbach","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"WI2020 Zentrale Tracks","raw_type":"book-chapter"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6899999976158142,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4255463199","https://openalex.org/W4281691423","https://openalex.org/W2411039299","https://openalex.org/W1856410221","https://openalex.org/W2318949977","https://openalex.org/W2334139353","https://openalex.org/W4243014959","https://openalex.org/W2415764305","https://openalex.org/W4254613272","https://openalex.org/W2374523667"],"abstract_inverted_index":{"Due":[0],"to":[1,37,55,109,138,143],"its":[2,130],"large":[3],"cost-saving":[4],"potential,":[5],"data-driven":[6],"recruitment":[7,59],"is":[8],"becoming":[9],"increasingly":[10],"popular":[11],"across":[12],"various":[13],"industries.":[14],"However,":[15],"several":[16],"cases":[17],"were":[18],"reported":[19],"where":[20,68],"the":[21,69,111,118,126],"use":[22],"of":[23,90,120],"corresponding":[24],"technologies":[25],"had":[26],"caused":[27],"systematic":[28],"discrimination":[29,41,83,122],"against":[30],"certain":[31],"candidate":[32,92],"groups.":[33],"While":[34],"existing":[35],"approaches":[36],"discover":[38],"and":[39,129,133],"prevent":[40],"in":[42,64],"data":[43,103],"classification":[44],"mostly":[45],"perform":[46],"well":[47],"within":[48],"a":[49,81,101,140],"specific":[50],"context,":[51],"it":[52,136],"remains":[53],"unclear":[54],"what":[56],"extent":[57],"datadriven":[58],"can":[60],"be":[61],"conducted":[62],"discrimination-free":[63],"real-world":[65],"business":[66],"applications,":[67],"respective":[70],"context-specific":[71],"assumptions":[72],"do":[73],"not":[74],"necessarily":[75],"hold.":[76],"Hence,":[77],"we":[78],"first":[79],"define":[80],"generic":[82],"model":[84,108],"that":[85,117],"allows":[86],"for":[87],"arbitrary":[88],"descriptions":[89],"job":[91],"characteristics,":[93],"before":[94],"applying":[95],"two":[96],"sophisticated":[97],"discrimination-prevention":[98],"algorithms":[99],"on":[100,125],"sample":[102],"set":[104],"generated":[105],"from":[106],"our":[107,144],"evaluate":[110],"algorithms\u2019":[112],"performance.":[113],"Our":[114],"analysis":[115],"shows":[116],"amount":[119],"removed":[121],"highly":[123],"depends":[124],"application":[127],"context":[128],"underlying":[131],"definitions":[132],"assumptions,":[134],"making":[135],"hard":[137],"provide":[139],"holistic":[141],"answer":[142],"research":[145],"question.":[146]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2026-01-13T01:12:25.745995","created_date":"2020-03-13T00:00:00"}