{"id":"W4367681302","doi":"10.32920/22732472","title":"Gender Representation on Canadian Television News during Provincial Elections: A Longitudinal Study","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Media Studies and Communication","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"CLIPS; Politics; Population; Public opinion; Representation (politics); Content analysis; Political science; Psychology; Demography; Medicine; Sociology; Law; Social science","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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0006471119,0.0001803682,0.000230595,0.000330571,0.001934136,0.0002117796,0.0004909285,0.0001935301,0.0001847564],"category_scores_gemma":[0.0006709477,0.0001774823,0.00009917537,0.0004514962,0.00006659904,0.00008381913,0.0004152136,0.0005429956,0.0001678527],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009491852,"about_ca_system_score_gemma":0.001109941,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9178066,"about_ca_topic_score_gemma":0.9908214,"domain_scores_codex":[0.9976125,0.0004606386,0.0003292274,0.0005622077,0.0006309198,0.0004044856],"domain_scores_gemma":[0.9986181,0.0001434758,0.0001538627,0.0006811591,0.000194805,0.0002086528],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001098601,0.0006632237,0.8434955,0.00009654414,0.0004326212,0.00006169737,0.09576051,0.0006943665,0.00001242071,0.01458499,0.02389344,0.02019486],"study_design_scores_gemma":[0.0003944933,0.0001199519,0.9111485,0.00007466912,0.00008789688,4.538778e-7,0.07669923,0.00009875137,0.00001047652,0.004188003,0.006713944,0.0004636013],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8779574,0.0001130999,0.00009038514,0.008223883,0.00251583,0.00386739,0.00001612455,0.0004658299,0.10675],"genre_scores_gemma":[0.9927364,0.0007747872,0.0001090575,0.00006162239,0.00106845,0.0004820004,0.00003548403,0.00002373699,0.004708434],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.114779,"threshold_uncertainty_score":0.9993652,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1905214612662837,"score_gpt":0.4072717808313669,"score_spread":0.2167503195650832,"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."}}