{"id":"W2971468303","doi":"","title":"Subverting Democracy to Save Democracy: Canada’s Extra-Constitutional Approaches to Battling 'Fake News'","year":2019,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Hate Speech and Cyberbullying Detection","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Misinformation; Democracy; Politics; Context (archaeology); Political science; Internet privacy; Marketplace of ideas; Free speech; Scope (computer science); Law and economics; Constitutional law; Fake news; Freedom of expression; Law; Human rights; Sociology; Computer science; History","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001378707,0.000264576,0.0002592687,0.0002417987,0.000688237,0.0002989302,0.0009830632,0.00008476015,0.0000300024],"category_scores_gemma":[0.0001535399,0.0002563092,0.0001146191,0.0005814939,0.00002682859,0.0005748662,0.000159703,0.001444987,0.0002398947],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002239509,"about_ca_system_score_gemma":0.01132162,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01416387,"about_ca_topic_score_gemma":0.2170624,"domain_scores_codex":[0.9954915,0.0001054127,0.0004553263,0.0005567597,0.0006842373,0.002706744],"domain_scores_gemma":[0.9988002,0.00009164551,0.000160144,0.0004063066,0.0001112503,0.0004304118],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00009195093,0.00006530064,0.00726482,0.00001416577,0.0001755385,0.000041471,0.0004317377,0.01346604,0.003748621,0.7389975,0.0008620854,0.2348408],"study_design_scores_gemma":[0.00607769,0.004421912,0.01475251,0.0007506473,0.0001987495,0.01920491,0.006668111,0.06933569,0.03351923,0.6921979,0.1463345,0.006538081],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3297424,0.0002642728,0.651535,0.01434576,0.001141547,0.0003353649,0.00000171695,0.0001011579,0.002532745],"genre_scores_gemma":[0.9874792,0.00004061407,0.009352054,0.001044769,0.0003859693,0.000006318715,0.000001950778,0.00001899923,0.001670193],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6577367,"threshold_uncertainty_score":0.9999889,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02129176603461211,"score_gpt":0.2062889735766338,"score_spread":0.1849972075420217,"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."}}