{"id":"W7117160390","doi":"10.1145/3756681.3757051","title":"Understanding Underrepresented Groups in Open Source Software","year":2025,"lang":"en","type":"article","venue":"","topic":"Open Source Software Innovations","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Diversity (politics); Context (archaeology); Inclusion (mineral); Open source software; Affect (linguistics); Ethnic group; Focus group; Perspective (graphical)","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":["open_science"],"consensus_categories":[],"category_scores_codex":[0.02639588,0.000377343,0.0008304857,0.00779692,0.003835275,0.006823752,0.001088527,0.001562143,0.003491734],"category_scores_gemma":[0.07809083,0.0003633008,0.0007563373,0.005036818,0.004192679,0.01240315,0.007334496,0.001414379,0.000279204],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002578973,"about_ca_system_score_gemma":0.008855158,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00509142,"about_ca_topic_score_gemma":0.008967311,"domain_scores_codex":[0.9777204,0.01356155,0.001856799,0.001934845,0.00389688,0.001029563],"domain_scores_gemma":[0.925511,0.05039073,0.01392889,0.00226284,0.005589106,0.002317403],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001932766,0.0002283333,0.1928446,0.01411491,0.0004402649,0.001314838,0.3308679,0.0003128676,0.001745834,0.0323413,0.00343979,0.4221559],"study_design_scores_gemma":[0.00006096955,0.0003857007,0.1791717,0.04397704,0.0009422495,0.001643007,0.5828552,0.0007980521,0.002502837,0.05613293,0.1314014,0.0001288261],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8424171,0.0874087,0.0109421,0.02819851,0.0007347491,0.0003048191,0.0003395345,0.00002309982,0.02963144],"genre_scores_gemma":[0.9677971,0.02490458,0.003080838,0.002445888,0.0002165018,0.0002397565,0.0001372838,0.00001434058,0.001163648],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9989115,"threshold_uncertainty_score":0.1395964,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.102429313987809,"score_gpt":0.3241825045997828,"score_spread":0.2217531906119738,"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."}}