{"id":"W7146190887","doi":"","title":"The Struggle for Gender Diversity in the Film Industry in Canada","year":2023,"lang":"ja","type":"article","venue":"Institutional Repositories DataBase (IRDB)","topic":"Cinema and Media Studies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Film industry; Diversity (politics); Gender diversity; Gender relations; Work (physics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003050431,0.0001709671,0.0004606606,0.006975538,0.01382917,0.009120055,0.002032639,0.001083556,0.0102528],"category_scores_gemma":[0.01387939,0.0003038615,0.0003443573,0.009545175,0.003668641,0.001985486,0.002874726,0.001686887,0.0003468395],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.09834851,"about_ca_system_score_gemma":0.1410666,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9957455,"about_ca_topic_score_gemma":0.9983297,"domain_scores_codex":[0.9955669,0.0003858564,0.0001151846,0.0003333775,0.001686556,0.001912039],"domain_scores_gemma":[0.9795448,0.00315106,0.001709964,0.0004136339,0.009358292,0.005822298],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004725235,0.0001735489,0.4419693,0.0003523412,0.0001477702,0.001954035,0.1444575,0.001025941,0.001591098,0.1137727,0.06978284,0.2243004],"study_design_scores_gemma":[0.00001881617,0.00003880924,0.6021026,0.0005408305,0.00006494467,0.0003321055,0.2532858,0.001295815,0.0006227079,0.002855894,0.138745,0.00009668462],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8973398,0.003848631,0.0003632029,0.02896009,0.0001245379,0.00005157934,0.002095701,0.00004038968,0.06717598],"genre_scores_gemma":[0.9906221,0.001058563,0.0001246594,0.0006356299,0.0000198199,0.000006895967,0.0002258294,0.00001447158,0.007292069],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09834851,"threshold_uncertainty_score":0.7135718,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07161578912509879,"score_gpt":0.2509525806716672,"score_spread":0.1793367915465684,"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."}}