{"id":"W2472066353","doi":"10.29173/cais460","title":"Bias in Subject Access Standards: A Content Analysis of the Critical Literature","year":2013,"lang":"en","type":"article","venue":"Proceedings of the Annual Conference of CAIS / Actes du congrès annuel de l ACSI","topic":"Higher Education Learning Practices","field":"Social Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Subject (documents); Nationality; Race (biology); Ethnic group; Content analysis; Human sexuality; Psychology; Content (measure theory); Social psychology; Gender studies; Computer science; Sociology; Political science; World Wide Web; Immigration; Social science; Anthropology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0912634,0.0006800761,0.001326857,0.04972263,0.006623599,0.008003211,0.001814532,0.001012683,0.002787451],"category_scores_gemma":[0.253785,0.0007102885,0.0008525581,0.03250419,0.007998797,0.008232426,0.005601363,0.001365951,0.000436803],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01421034,"about_ca_system_score_gemma":0.02004381,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004569823,"about_ca_topic_score_gemma":0.004338592,"domain_scores_codex":[0.919988,0.04480671,0.01087113,0.003795214,0.01860666,0.001932278],"domain_scores_gemma":[0.5356215,0.3701004,0.02035361,0.009319304,0.06354762,0.001057591],"domain_codex":null,"domain_gemma":"reporting","domain_candidate":"reporting","domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002424806,0.0001187195,0.02398938,0.006650786,0.0001145883,0.0005281774,0.7880989,0.0001959793,0.003804062,0.03057382,0.005868763,0.1398143],"study_design_scores_gemma":[0.00007800292,0.0002462664,0.03747847,0.01255044,0.0003949603,0.0005239074,0.8386534,0.001517945,0.006891646,0.02678414,0.07470039,0.0001804229],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8457075,0.009461544,0.0714066,0.00851895,0.001051978,0.01530783,0.003860629,0.0002955105,0.04438939],"genre_scores_gemma":[0.8756849,0.006539195,0.09804247,0.001763799,0.0004145643,0.01120051,0.001600971,0.0003323624,0.004421353],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9087366,"threshold_uncertainty_score":0.4826527,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08818707045863096,"score_gpt":0.3767200775014438,"score_spread":0.2885330070428129,"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."}}