{"id":"W4389518882","doi":"10.18653/v1/2023.findings-emnlp.730","title":"Legally Enforceable Hate Speech Detection for Public Forums","year":2023,"lang":"en","type":"article","venue":"","topic":"Hate Speech and Cyberbullying Detection","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada; Queen's University","keywords":"Task (project management); Law enforcement; Computer science; Perspective (graphical); Enforcement; Set (abstract data type); Speech act; Free speech; Computer security; Internet privacy; Law; Political science; Artificial intelligence; Linguistics; Engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.00346399,0.00147865,0.0007768528,0.001617413,0.001405482,0.001628226,0.001216182,0.002276619,0.00315191],"category_scores_gemma":[0.01383518,0.0003372393,0.0008881794,0.0005927518,0.0008664614,0.003306652,0.002025086,0.002944764,0.00250235],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001424968,"about_ca_system_score_gemma":0.001225178,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008234229,"about_ca_topic_score_gemma":0.01574612,"domain_scores_codex":[0.9960751,0.00198287,0.0001858316,0.001059955,0.0004379819,0.0002582267],"domain_scores_gemma":[0.9884,0.007440543,0.000761734,0.0015093,0.001314608,0.0005737955],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00331199,0.003528805,0.1009427,0.003004186,0.000366357,0.002307015,0.01214224,0.04781519,0.06698538,0.007159852,0.1581584,0.5942779],"study_design_scores_gemma":[0.0002367448,0.001150468,0.07372639,0.0003569347,0.0001498739,0.00179477,0.008363237,0.7878338,0.04962705,0.0120647,0.06441166,0.0002843169],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8828758,0.002302776,0.07393511,0.002400565,0.0009204571,0.0006405867,0.01428299,0.0124543,0.01018734],"genre_scores_gemma":[0.9117871,0.0002573422,0.05194007,0.0004952357,0.000190088,0.0003032812,0.02975181,0.000348652,0.004926395],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008234229,"threshold_uncertainty_score":0.01831949,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02937263265629363,"score_gpt":0.2469914875447365,"score_spread":0.2176188548884429,"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."}}