{"id":"https://openalex.org/W4414897191","doi":"https://doi.org/10.48550/arxiv.2506.01594","title":"Selecting for Less Discriminatory Algorithms: A Relational Search Framework for Navigating Fairness-Accuracy Trade-offs in Practice","display_name":"Selecting for Less Discriminatory Algorithms: A Relational Search Framework for Navigating Fairness-Accuracy Trade-offs in Practice","publication_year":2025,"publication_date":"2025-06-02","ids":{"openalex":"https://openalex.org/W4414897191","doi":"https://doi.org/10.48550/arxiv.2506.01594"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2506.01594","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2506.01594","pdf_url":"https://arxiv.org/pdf/2506.01594","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2506.01594","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5119878818","display_name":"Hana Samad","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Samad, Hana","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5119878819","display_name":"Michael Akinwumi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Akinwumi, Michael","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Khan, Jameel","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Khan, Jameel","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5119878820","display_name":"Christoph M\u00fcgge-Durum","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"M\u00fcgge-Durum, Christoph","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5061374096","display_name":"Emmanuel Ogundimu","orcid":"https://orcid.org/0000-0001-9252-9275"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ogundimu, Emmanuel O.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13051","display_name":"Qualitative Comparative Analysis Research","score":0.8817999958992004,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T13051","display_name":"Qualitative Comparative Analysis Research","score":0.8817999958992004,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/operationalization","display_name":"Operationalization","score":0.5787000060081482},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.4975999891757965},{"id":"https://openalex.org/keywords/normative","display_name":"Normative","score":0.4925999939441681},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.4546000063419342},{"id":"https://openalex.org/keywords/resource","display_name":"Resource (disambiguation)","score":0.4043000042438507},{"id":"https://openalex.org/keywords/scope","display_name":"Scope (computer science)","score":0.38199999928474426},{"id":"https://openalex.org/keywords/heuristics","display_name":"Heuristics","score":0.38119998574256897}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6854000091552734},{"id":"https://openalex.org/C9354725","wikidata":"https://www.wikidata.org/wiki/Q286017","display_name":"Operationalization","level":2,"score":0.5787000060081482},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4975999891757965},{"id":"https://openalex.org/C44725695","wikidata":"https://www.wikidata.org/wiki/Q288156","display_name":"Normative","level":2,"score":0.4925999939441681},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4546000063419342},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.4043000042438507},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38679999113082886},{"id":"https://openalex.org/C2778012447","wikidata":"https://www.wikidata.org/wiki/Q1034415","display_name":"Scope (computer science)","level":2,"score":0.38199999928474426},{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.38119998574256897},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35199999809265137},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.3452000021934509},{"id":"https://openalex.org/C10485038","wikidata":"https://www.wikidata.org/wiki/Q48996162","display_name":"Hyperparameter optimization","level":3,"score":0.33980000019073486},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.3156999945640564},{"id":"https://openalex.org/C34388435","wikidata":"https://www.wikidata.org/wiki/Q2267362","display_name":"Bounded function","level":2,"score":0.27549999952316284},{"id":"https://openalex.org/C2778137410","wikidata":"https://www.wikidata.org/wiki/Q2732820","display_name":"Government (linguistics)","level":2,"score":0.2734000086784363},{"id":"https://openalex.org/C58694771","wikidata":"https://www.wikidata.org/wiki/Q814385","display_name":"Bounded rationality","level":2,"score":0.26350000500679016},{"id":"https://openalex.org/C29202148","wikidata":"https://www.wikidata.org/wiki/Q287260","display_name":"Resource allocation","level":2,"score":0.25360000133514404}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2506.01594","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2506.01594","pdf_url":"https://arxiv.org/pdf/2506.01594","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2506.01594","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2506.01594","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2506.01594","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2506.01594","pdf_url":"https://arxiv.org/pdf/2506.01594","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4414897191.pdf","grobid_xml":"https://content.openalex.org/works/W4414897191.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"As":[0],"machine":[1],"learning":[2],"models":[3,66],"are":[4],"increasingly":[5],"embedded":[6],"into":[7],"society":[8],"through":[9,82],"high-stakes":[10],"decision-making,":[11],"selecting":[12],"the":[13,29,83,123,147,150,158,208],"right":[14],"algorithm":[15],"for":[16],"a":[17,24,63,95,169,202,214,242],"given":[18],"task,":[19],"audience,":[20],"and":[21,117,127,142,233,239],"sector":[22],"presents":[23],"critical":[25],"challenge,":[26],"particularly":[27],"in":[28,181,241],"context":[30],"of":[31,35,85,146,149],"fairness.":[32],"Traditional":[33],"assessments":[34],"model":[36,48,60,92,165],"fairness":[37,41,74,110,131,163,180,238],"have":[38,78],"often":[39],"framed":[40],"as":[42,50,62,94],"an":[43,51,144],"objective":[44],"mathematical":[45],"property,":[46],"treating":[47],"selection":[49,93],"optimization":[52],"problem":[53],"under":[54],"idealized":[55],"informational":[56],"conditions.":[57],"This":[58],"overlooks":[59],"multiplicity":[61],"consideration--that":[64],"multiple":[65],"can":[67,225],"deliver":[68],"similar":[69],"performance":[70],"while":[71],"exhibiting":[72],"different":[73],"characteristics.":[75],"Legal":[76],"scholars":[77],"engaged":[79],"this":[80,102,227],"challenge":[81,104],"concept":[84],"Less":[86],"Discriminatory":[87],"Algorithms":[88],"(LDAs),":[89],"which":[90],"frames":[91],"civil":[96],"rights":[97],"obligation.":[98],"In":[99],"real-world":[100,221],"deployment,":[101],"normative":[103],"is":[105],"bounded":[106],"by":[107,200],"constraints":[108],"on":[109,220],"experimentation,":[111],"e.g.,":[112],"regulatory":[113],"standards,":[114],"institutional":[115],"priorities,":[116],"resource":[118,183],"capacity.":[119],"Against":[120],"these":[121],"considerations,":[122],"paper":[124],"revisits":[125],"Lee":[126],"Floridi":[128],"(2021)'s":[129],"relational":[130,209],"approach":[132,206,228],"using":[133,201],"updated":[134],"2021":[135],"Home":[136],"Mortgage":[137],"Disclosure":[138],"Act":[139],"(HMDA)":[140],"data,":[141],"proposes":[143],"expansion":[145],"scope":[148],"LDA":[151,159,204,218],"search":[152,160,205,219],"process.":[153],"We":[154],"argue":[155],"that":[156,236],"extending":[157],"horizontally,":[161],"considering":[162],"across":[164],"families":[166],"themselves,":[167],"provides":[168],"lightweight":[170],"complement,":[171],"or":[172],"alternative,":[173],"to":[174,194,229],"within-model":[175],"hyperparameter":[176],"optimization,":[177],"when":[178],"operationalizing":[179],"non-experimental,":[182],"constrained":[184],"settings.":[185],"Fairness":[186],"metrics":[187],"alone":[188],"offer":[189],"useful,":[190],"but":[191],"insufficient":[192],"signals":[193],"accurately":[195],"evaluate":[196],"candidate":[197],"LDAs.":[198],"Rather,":[199],"horizontal":[203],"with":[207],"trade-off":[210],"framework,":[211],"we":[212],"demonstrate":[213],"responsible":[215],"minimum":[216],"viable":[217],"lending":[222],"outcomes.":[223],"Organizations":[224],"modify":[226],"systematically":[230],"compare,":[231],"evaluate,":[232],"select":[234],"LDAs":[235],"optimize":[237],"accuracy":[240],"sector-based":[243],"contextualized":[244],"manner.":[245]},"counts_by_year":[],"updated_date":"2026-08-18T07:49:30.821534","created_date":"2025-10-10T00:00:00"}