{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005423574,0.0001223034,0.0001120107,0.0002717723,0.0003339312,0.0004774147,0.0004696518,0.00008683393,0.00002898771],"category_scores_gemma":[0.00009595056,0.0001116657,0.0001030935,0.001063393,0.00001528271,0.001009758,0.0001280851,0.00008795156,0.0007484955],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000049212,"about_ca_system_score_gemma":0.00004989728,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008855823,"about_ca_topic_score_gemma":0.0001985285,"domain_scores_codex":[0.9986535,0.00002064427,0.0001867306,0.0003674987,0.0002313245,0.0005402737],"domain_scores_gemma":[0.9992369,0.00006828434,0.00005292067,0.0004018029,0.0001250415,0.0001150256],"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":[0.00001410902,0.00002432307,0.00004817905,0.00002800644,0.00002840325,0.00001073171,0.0001045759,0.0001387637,0.02301739,0.06574877,0.009619058,0.9012177],"study_design_scores_gemma":[0.0006720791,0.0003833529,0.0003080419,0.00001031416,0.00000588768,0.00005559499,0.00007720582,0.3488085,0.3701017,0.01754369,0.2616629,0.0003707196],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01425937,0.00001097941,0.9671295,0.001856367,0.001323807,0.000401774,0.000001474942,0.001956285,0.01306041],"genre_scores_gemma":[0.9402523,0.00001554126,0.02713098,0.0003542444,0.000174014,0.0001358866,0.000009317449,0.00002183197,0.0319059],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9399986,"threshold_uncertainty_score":0.9620645,"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."}}