{"id":"W4239886047","doi":"10.32920/ryerson.14655852","title":"Technology, Culture and Industry: Canadian Communications Regulation and Digital Policy","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Cultural Industries and Urban Development","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; York University","funders":"","keywords":"Net neutrality; Media policy; The Internet; Government (linguistics); Digital economy; Public relations; Digital divide; Digital media; Political science; Business; Information and Communications Technology; Telecommunications; Engineering; World Wide Web; Politics; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005037139,0.0005128958,0.0004478137,0.003958461,0.02806246,0.0153028,0.002385981,0.005508336,0.01126438],"category_scores_gemma":[0.01354995,0.0004462069,0.0004768355,0.008617336,0.0154024,0.003637924,0.003732121,0.004531797,0.0005295507],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.27374,"about_ca_system_score_gemma":0.3942361,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9975635,"about_ca_topic_score_gemma":0.9973891,"domain_scores_codex":[0.9893666,0.001352166,0.0002106869,0.0006934489,0.004886147,0.003491046],"domain_scores_gemma":[0.9923075,0.002400837,0.0003140874,0.0002407948,0.003594069,0.001142625],"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":[0.00002007184,0.00001667399,0.002229284,0.0001062429,0.000007545425,0.0001235858,0.007287133,0.000401693,0.0001194577,0.9169955,0.05158867,0.02110404],"study_design_scores_gemma":[0.00002978049,0.000019271,0.02417307,0.0007151742,0.00004792232,0.00008788295,0.01973813,0.001554182,0.0004265901,0.08727456,0.8657857,0.0001477396],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.05029835,0.03531772,0.001300765,0.2847399,0.001050917,0.00007901638,0.0009478362,0.00008219515,0.6261833],"genre_scores_gemma":[0.7862776,0.02125205,0.002270954,0.02773749,0.000299585,0.00009407637,0.0004718027,0.0001027951,0.1614936],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7262599,"threshold_uncertainty_score":0.8423586,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04629524756950784,"score_gpt":0.3156788481536408,"score_spread":0.269383600584133,"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."}}