{"id":"https://openalex.org/W4412886776","doi":"https://doi.org/10.18653/v1/2025.acl-long.128","title":"Gender Inclusivity Fairness Index (GIFI): A Multilevel Framework for Evaluating Gender Diversity in Large Language Models","display_name":"Gender Inclusivity Fairness Index (GIFI): A Multilevel Framework for Evaluating Gender Diversity in Large Language Models","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4412886776","doi":"https://doi.org/10.18653/v1/2025.acl-long.128"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2025.acl-long.128","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.acl-long.128","pdf_url":"https://aclanthology.org/2025.acl-long.128.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2025.acl-long.128.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Zhengyang Shan","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhengyang Shan","raw_affiliation_strings":["Boston University Carnegie Mellon University Stony Brook University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Boston University Carnegie Mellon University Stony Brook University","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041937705","display_name":"E. Diana","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Emily Diana","raw_affiliation_strings":["Boston University Carnegie Mellon University Stony Brook University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Boston University Carnegie Mellon University Stony Brook University","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5107950655","display_name":"Jiawei Zhou","orcid":"https://orcid.org/0009-0004-9182-5223"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jiawei Zhou","raw_affiliation_strings":["Boston University Carnegie Mellon University Stony Brook University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Boston University Carnegie Mellon University Stony Brook University","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I74973139"],"apc_list":null,"apc_paid":null,"fwci":5.334,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.95048811,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"2548","last_page":"2579"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11432","display_name":"Gender Politics and Representation","score":0.47839999198913574,"subfield":{"id":"https://openalex.org/subfields/3318","display_name":"Gender Studies"},"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/T11432","display_name":"Gender Politics and Representation","score":0.47839999198913574,"subfield":{"id":"https://openalex.org/subfields/3318","display_name":"Gender Studies"},"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/index","display_name":"Index (typography)","score":0.6343327760696411},{"id":"https://openalex.org/keywords/gender-diversity","display_name":"Gender diversity","score":0.6312116384506226},{"id":"https://openalex.org/keywords/diversity","display_name":"Diversity (politics)","score":0.6284809112548828},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5108949542045593},{"id":"https://openalex.org/keywords/multilevel-model","display_name":"Multilevel model","score":0.4407438039779663},{"id":"https://openalex.org/keywords/sociology","display_name":"Sociology","score":0.26142263412475586},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.10335493087768555},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.09334325790405273},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.06734880805015564},{"id":"https://openalex.org/keywords/anthropology","display_name":"Anthropology","score":0.06536257266998291}],"concepts":[{"id":"https://openalex.org/C2777382242","wikidata":"https://www.wikidata.org/wiki/Q6017816","display_name":"Index (typography)","level":2,"score":0.6343327760696411},{"id":"https://openalex.org/C2778397978","wikidata":"https://www.wikidata.org/wiki/Q1501335","display_name":"Gender diversity","level":3,"score":0.6312116384506226},{"id":"https://openalex.org/C2781316041","wikidata":"https://www.wikidata.org/wiki/Q1230584","display_name":"Diversity (politics)","level":2,"score":0.6284809112548828},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5108949542045593},{"id":"https://openalex.org/C53059260","wikidata":"https://www.wikidata.org/wiki/Q374758","display_name":"Multilevel model","level":2,"score":0.4407438039779663},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.26142263412475586},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.10335493087768555},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.09334325790405273},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.06734880805015564},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","level":1,"score":0.06536257266998291},{"id":"https://openalex.org/C39389867","wikidata":"https://www.wikidata.org/wiki/Q380767","display_name":"Corporate governance","level":2,"score":0.0},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2025.acl-long.128","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.acl-long.128","pdf_url":"https://aclanthology.org/2025.acl-long.128.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2025.acl-long.128","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.acl-long.128","pdf_url":"https://aclanthology.org/2025.acl-long.128.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.7599999904632568,"display_name":"Gender equality","id":"https://metadata.un.org/sdg/5"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4412886776.pdf","grobid_xml":"https://content.openalex.org/works/W4412886776.grobid-xml"},"referenced_works_count":1,"referenced_works":["https://openalex.org/W6868564194"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2965417904","https://openalex.org/W2767354473","https://openalex.org/W4306290607","https://openalex.org/W4321464266","https://openalex.org/W1582540633","https://openalex.org/W828612630"],"abstract_inverted_index":{"We":[0],"present":[1],"a":[2,40,55,128,149],"comprehensive":[3,43],"evaluation":[4],"of":[5,51,54,58,78,107,123,151,188],"gender":[6,30,49,72,86,93,117,135,144],"fairness":[7,136,145],"in":[8,115,134,137,146,162,170,174],"large":[9],"language":[10],"models":[11],"(LLMs),":[12],"focusing":[13],"on":[14,28,100],"their":[15],"ability":[16],"to":[17,70,74,180],"handle":[18],"both":[19],"binary":[20,29],"and":[21,42,81,104,110,165,168],"non-binary":[22],"genders.While":[23],"previous":[24],"studies":[25],"primarily":[26],"focus":[27],"distinctions,":[31],"we":[32],"introduce":[33],"the":[34,47,66,121,182],"Gender":[35],"Inclusivity":[36],"Fairness":[37,161],"Index":[38],"(GIFI),":[39],"novel":[41],"metric":[44],"that":[45],"quantifies":[46],"diverse":[48],"inclusivity":[50],"LLMs.GIFI":[52],"consists":[53],"wide":[56],"range":[57],"evaluations":[59,97],"at":[60],"different":[61,85],"levels,":[62],"from":[63],"simply":[64],"probing":[65],"model":[67,79],"with":[68,91,98],"respect":[69],"provided":[71],"pronouns":[73],"testing":[75],"various":[76,186],"aspects":[77],"generation":[80],"cognitive":[82],"behaviors":[83],"under":[84],"assumptions,":[87],"revealing":[88],"biases":[89],"associated":[90],"varying":[92,108],"identifiers.We":[94],"conduct":[95],"extensive":[96],"GIFI":[99,141],"22":[101],"prominent":[102],"open-source":[103],"proprietary":[105],"LLMs":[106,147],"sizes":[109],"capabilities,":[111],"discovering":[112],"significant":[113],"variations":[114],"LLMs'":[116,125],"inclusivity.Our":[118],"study":[119],"highlights":[120],"importance":[122],"improving":[124],"inclusivity,":[126],"providing":[127],"critical":[129],"benchmark":[130],"for":[131],"future":[132],"advancements":[133],"generative":[138],"models.":[139],"1":[140],"FrameworkWe":[142],"evaluate":[143],"through":[148],"series":[150],"progressively":[152],"complex":[153],"tests,":[154],"organized":[155],"into":[156],"four":[157],"stages:":[158],"Pronoun":[159],"Recognition,":[160],"Distribution,":[163],"Stereotype":[164],"Role":[166],"Assignment,":[167],"Consistency":[169],"Performance,":[171],"as":[172],"shown":[173],"Figure":[175],"1.These":[176],"stages":[177],"are":[178],"designed":[179],"assess":[181],"model's":[183],"behavior":[184],"across":[185],"levels":[187],"understanding":[189],"0.0":[190],"0.2":[191],"0.4":[192],"0.6":[193],"0.8":[194],"1.":[195]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
