{"id":"W4286951123","doi":"10.48550/arxiv.2110.00116","title":"#ContextMatters: Advantages and Limitations of Using Machine Learning to\\n Support Women in Politics","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Hate Speech and Cyberbullying Detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Politics; Affect (linguistics); Government (linguistics); Political science; Natural experiment; Intervention (counseling); Social media; Inequality; Public relations; Social psychology; Psychology; Medicine; Law","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":[],"consensus_categories":[],"category_scores_codex":[0.0002212583,0.0001532675,0.0002562666,0.0003847736,0.00007870778,0.00008189246,0.0003597644,0.0001073105,0.00001157648],"category_scores_gemma":[0.0001101786,0.0001983065,0.00005558581,0.0004510629,0.00004222201,0.0002693836,0.0008688384,0.0003458622,0.0000054992],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002128864,"about_ca_system_score_gemma":0.0001581754,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004058693,"about_ca_topic_score_gemma":0.0002200373,"domain_scores_codex":[0.9988222,0.0001205352,0.0001737798,0.0005134899,0.00006058471,0.000309422],"domain_scores_gemma":[0.9991535,0.0001217227,0.0001287655,0.0003498924,0.00009114643,0.0001549708],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006768872,0.0003722747,0.1432699,0.000585207,0.0002566402,0.001701959,0.02510454,0.7896004,0.008621901,0.02037483,0.00002067815,0.01002398],"study_design_scores_gemma":[0.001295186,0.0004524166,0.01607522,0.000542983,0.00007669185,0.00005863434,0.008204709,0.9595366,0.003575253,0.008208494,0.0008781885,0.001095663],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8806984,0.00003047698,0.118592,0.00004361498,0.0001370398,0.0001091492,0.000004799592,0.00004675758,0.0003377291],"genre_scores_gemma":[0.9953873,0.000164171,0.003787423,0.00006210498,0.00001360695,5.657321e-7,0.000007694414,0.000009764512,0.0005674151],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1699362,"threshold_uncertainty_score":0.8086705,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08615127937938073,"score_gpt":0.2094336096500253,"score_spread":0.1232823302706445,"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."}}