{"id":"W1565180830","doi":"10.3386/w8281","title":"Employment, Dynamic Deterrence and Crime","year":2001,"lang":"en","type":"report","venue":"National Bureau of Economic Research","topic":"Crime Patterns and Interventions","field":"Social Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Deterrence (psychology); Criminology; Economics; Political science; Sociology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001622149,0.0004162558,0.0007317474,0.001134261,0.0005077309,0.001896963,0.0007595301,0.001091442,0.009792125],"category_scores_gemma":[0.008828805,0.0005475612,0.0006159739,0.002971316,0.0005067644,0.001087274,0.001338513,0.001754103,0.001181068],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001100348,"about_ca_system_score_gemma":0.001241139,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03133341,"about_ca_topic_score_gemma":0.0458345,"domain_scores_codex":[0.9992397,0.0003371576,0.00004020456,0.0001085067,0.0001137515,0.0001606298],"domain_scores_gemma":[0.9949605,0.002450133,0.0019217,0.0002534211,0.000185921,0.0002281541],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003209436,0.000885804,0.4940882,0.0002758555,0.0006847228,0.0005582349,0.0004283018,0.3119738,0.0003971031,0.0822883,0.02172135,0.08637731],"study_design_scores_gemma":[0.0001655181,0.0003922712,0.2627057,0.0003254416,0.0003847974,0.0003380722,0.0007220706,0.6003497,0.0006017886,0.1119861,0.02190766,0.0001209019],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8784322,0.003736211,0.07621346,0.006873123,0.0001599293,0.0001711326,0.01530795,0.000274112,0.01883187],"genre_scores_gemma":[0.977122,0.002559848,0.007580635,0.0002489352,0.0001131824,0.0001381625,0.005388733,0.00003141197,0.00681716],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03133341,"threshold_uncertainty_score":0.06230205,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5749368054579993,"score_gpt":0.6292229435562371,"score_spread":0.05428613809823779,"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."}}