{"id":"W2587939649","doi":"","title":"\"Crazy B****\": Discriminatory Language, Radio Censorship, Regulation, and Enforcement Policies in Canada","year":2016,"lang":"en","type":"dissertation","venue":"YorkSpace (York University)","topic":"Hate Speech and Cyberbullying Detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Censorship; Enforcement; Political science; Law enforcement; Computer security; Business; Computer science; Law","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":[0.001592673,0.0001979228,0.0003679658,0.002919601,0.006323868,0.003998109,0.0009995356,0.0003900264,0.00315396],"category_scores_gemma":[0.01016411,0.0002025647,0.0003217609,0.007052307,0.002873599,0.0008450965,0.001542305,0.001099119,0.000208722],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06807584,"about_ca_system_score_gemma":0.09858774,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9982812,"about_ca_topic_score_gemma":0.9990978,"domain_scores_codex":[0.9974195,0.0001842274,0.00008850763,0.0002422092,0.00120961,0.000856096],"domain_scores_gemma":[0.9914367,0.001039311,0.001293306,0.0002969337,0.004269992,0.001663719],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001698856,0.00006339684,0.9005356,0.0001797645,0.00009750453,0.000220301,0.01803982,0.001102197,0.0004851822,0.009214288,0.01638117,0.05351089],"study_design_scores_gemma":[0.000007243381,0.00002055875,0.9581379,0.0001610418,0.00003234438,0.00003719014,0.02356564,0.0007047882,0.0002193952,0.0002975721,0.01678087,0.00003556918],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.954444,0.002384372,0.0004705304,0.00477775,0.0000578688,0.00007127854,0.005079267,0.00003060423,0.03268439],"genre_scores_gemma":[0.9914578,0.001337369,0.0002741426,0.0002893558,0.00001223587,0.00001580707,0.00140861,0.00001405896,0.005190639],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06807584,"threshold_uncertainty_score":0.4939271,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005525343225973517,"score_gpt":0.1833169224602673,"score_spread":0.1777915792342938,"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."}}