{"id":"W70209539","doi":"10.32920/ryerson.14647797.v1","title":"Shaping Policy Discourse in the Public Sphere: Evaluating Civil Speech in an Online Consultation","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Social Media and Politics","field":"Social Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for Social Innovation","funders":"","keywords":"Civility; Public sphere; Civil society; Public relations; Government (linguistics); Political science; Civil discourse; The Internet; Public policy; Public discourse; Function (biology); Discourse analysis; Affect (linguistics); Style (visual arts); Deliberative democracy; Online discussion; Public administration; Sociology; Politics; Democracy; Law; Linguistics; 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":[0.03040211,0.0006542878,0.0006757218,0.002051453,0.006449633,0.008021569,0.001160519,0.002562502,0.005995872],"category_scores_gemma":[0.1268434,0.0003357412,0.0007001918,0.00259384,0.007276876,0.005230065,0.00496924,0.002216377,0.001087795],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007173478,"about_ca_system_score_gemma":0.006091286,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0227442,"about_ca_topic_score_gemma":0.02045414,"domain_scores_codex":[0.959666,0.03160376,0.00115839,0.001204232,0.004839375,0.001528288],"domain_scores_gemma":[0.8021792,0.1656501,0.008748014,0.004535712,0.01427473,0.004612329],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.008069695,0.01061509,0.08082481,0.002597308,0.0002547225,0.001726261,0.7152035,0.01217395,0.02465542,0.02279712,0.002912469,0.1181696],"study_design_scores_gemma":[0.001327503,0.01392448,0.2046176,0.001109418,0.000518612,0.0004821616,0.6560462,0.02645074,0.03326343,0.02087291,0.04084145,0.0005455496],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9699877,0.00006720663,0.001514129,0.000254077,0.0000254721,0.0007819736,0.00009465875,0.00003321368,0.02724163],"genre_scores_gemma":[0.9930057,0.00007353986,0.00298132,0.0001638859,0.00002420679,0.001076024,0.0001392933,0.00002850554,0.002507679],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03040211,"threshold_uncertainty_score":0.1607836,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2755273089443981,"score_gpt":0.494863873699903,"score_spread":0.2193365647555049,"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."}}