{"id":"W4417049661","doi":"10.1177/20539517251396069","title":"Cross-cultural challenges in generative AI: Addressing homophobia in diverse sociocultural contexts","year":2025,"lang":"en","type":"article","venue":"Big Data & Society","topic":"AI in Service Interactions","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"Budapesti Corvinus Egyetem","keywords":"Generative grammar; Sociocultural evolution; Context (archaeology); Viewpoints; Cultural diversity; Variety (cybernetics); Dilemma; Cultural relativism","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03053348,0.0005531677,0.0005132767,0.001676961,0.006900707,0.007950305,0.001855257,0.001522865,0.003477398],"category_scores_gemma":[0.0454523,0.0004406695,0.0005013917,0.0009185309,0.01035558,0.006251548,0.0122138,0.002780446,0.0005118559],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002033782,"about_ca_system_score_gemma":0.0030673,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002278047,"about_ca_topic_score_gemma":0.003876484,"domain_scores_codex":[0.9699767,0.02546802,0.0005688801,0.001010762,0.001859301,0.001116278],"domain_scores_gemma":[0.9315861,0.05625144,0.002643181,0.004190921,0.002438799,0.00288949],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00008037112,0.0001942897,0.02196703,0.0004129594,0.00003068022,0.0005738631,0.9198862,0.0001440221,0.004140354,0.004271671,0.0006546613,0.04764397],"study_design_scores_gemma":[0.00002526214,0.0003495246,0.01890687,0.0007062443,0.00005676025,0.001101758,0.9239136,0.001616491,0.003393701,0.0123566,0.03749329,0.00007987169],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9491252,0.0005864856,0.0193368,0.005495043,0.0001469008,0.0002833067,0.00003551312,0.0001805884,0.02481019],"genre_scores_gemma":[0.9913102,0.0002444748,0.005604309,0.001217141,0.00004053418,0.0001847284,0.00002292736,0.00004408071,0.001331544],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03053348,"threshold_uncertainty_score":0.1614784,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2409162857066321,"score_gpt":0.411376591822173,"score_spread":0.1704603061155409,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}