{"id":"W2101634860","doi":"10.1177/1557085113502518","title":"The Equalizer? Crime, Vulnerability, and Gender in Pro-Gun Discourse","year":2013,"lang":"en","type":"article","venue":"Feminist Criminology","topic":"Gun Ownership and Violence Research","field":"Social Sciences","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"University of Toronto","keywords":"Criminology; Vulnerability (computing); Privilege (computing); Perspective (graphical); Politics; Sociology; Crime control; Computer security; Political science; Criminal justice; Law; Computer science","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":[0.003754905,0.0004631013,0.0004510737,0.002098088,0.008803375,0.007582022,0.0006319468,0.002006869,0.004335868],"category_scores_gemma":[0.006689821,0.0002326256,0.0002309648,0.001347479,0.03106477,0.009341277,0.005500939,0.002196815,0.0002329918],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003988833,"about_ca_system_score_gemma":0.001848409,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006590296,"about_ca_topic_score_gemma":0.006237596,"domain_scores_codex":[0.9952689,0.003505094,0.0000725718,0.0002656071,0.0003367525,0.0005510827],"domain_scores_gemma":[0.9960997,0.002872416,0.0004554454,0.0001616542,0.0001576645,0.0002530699],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00004490546,0.00003071716,0.004066636,0.00006495423,0.00001135262,0.000276378,0.5031026,0.0000789316,0.0003257315,0.4824185,0.001078,0.008501332],"study_design_scores_gemma":[0.00001607341,0.00004638476,0.007322008,0.0005608511,0.00002591679,0.0004611116,0.8041381,0.0003751875,0.0007729961,0.1340243,0.05222433,0.00003263669],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7929834,0.005233185,0.002643739,0.03016495,0.0002436983,0.00001822969,0.00003614215,0.00001846749,0.1686583],"genre_scores_gemma":[0.9981925,0.000332393,0.00007416011,0.0002840029,0.00002224903,0.000006139426,0.000002362084,0.000005203884,0.001081017],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008803375,"threshold_uncertainty_score":0.02894115,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2410524494661389,"score_gpt":0.4508475654913764,"score_spread":0.2097951160252375,"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."}}