{"id":"W2916530830","doi":"10.22230/cjc.2019v44n1a3321","title":"The Representation of Women and Racialized Minorities as Expert Sources On-Air in Canadian Public Affairs Television","year":2019,"lang":"en","type":"article","venue":"Canadian Journal of Communication","topic":"Media Studies and Communication","field":"Social Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Toronto Metropolitan University","funders":"","keywords":"Disadvantaged; Representation (politics); Corporation; Public broadcasting; Political science; Gender studies; Race (biology); Broadcasting (networking); Sociology; Advertising; Law; Business; Politics; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001952383,0.00006150156,0.0001686346,0.000281114,0.0007521543,0.00009183932,0.000659058,0.00006310692,0.00006629407],"category_scores_gemma":[0.001099832,0.00005170651,0.00003574462,0.0003013661,0.0003381804,0.0002499379,0.00002586028,0.0001789512,0.000004209882],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007391511,"about_ca_system_score_gemma":0.002084092,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.75082,"about_ca_topic_score_gemma":0.9782409,"domain_scores_codex":[0.9984244,0.0006565012,0.000334177,0.00006118199,0.0002140717,0.0003096882],"domain_scores_gemma":[0.9979983,0.0006152251,0.0002915126,0.0004253075,0.0002576009,0.0004120613],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009439541,0.00003681332,0.1887054,0.00001349022,0.0000863126,0.000003430543,0.4260577,0.00004137329,0.0001002738,0.2416024,0.00276101,0.1404973],"study_design_scores_gemma":[0.0005185922,0.0001211052,0.04422297,0.0001269854,0.000004628253,0.000002811714,0.2601184,0.00004263518,0.00004720288,0.005790344,0.6888898,0.0001145207],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.938637,0.005755668,6.843679e-7,0.03194338,0.0001323086,0.0001994681,0.000001585181,0.000002252063,0.02332763],"genre_scores_gemma":[0.9922581,0.007263634,0.00004794944,0.0001640439,0.00003495969,0.00001145805,0.000002843739,0.000005220532,0.0002117817],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6861288,"threshold_uncertainty_score":0.5785039,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02780505883434192,"score_gpt":0.3072357974845405,"score_spread":0.2794307386501986,"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."}}