{"id":"W2765449540","doi":"10.1108/pijpsm-06-2016-0081","title":"Correlates of subject(ive) resistance in police use-of-force situations","year":2017,"lang":"en","type":"article","venue":"Policing-an International Journal of Police Strategies & Management","topic":"Policing Practices and Perceptions","field":"Social Sciences","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Resistance (ecology); Multinomial logistic regression; Officer; Psychology; Use of force; Situational ethics; Variety (cybernetics); Subject (documents); Psychological intervention; Social psychology; Value (mathematics); Political science; Computer science; Statistics; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001842929,0.0002101354,0.0002437403,0.001547529,0.0009985575,0.001260971,0.000509921,0.0005079657,0.001706484],"category_scores_gemma":[0.01421167,0.0002007039,0.0003376514,0.000762595,0.001303355,0.0004139194,0.001097741,0.0008552338,0.0001592266],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009297609,"about_ca_system_score_gemma":0.0011549,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03584301,"about_ca_topic_score_gemma":0.04110302,"domain_scores_codex":[0.9976325,0.0008754496,0.0002652522,0.0001701256,0.0007475396,0.0003090788],"domain_scores_gemma":[0.9893939,0.002124029,0.005922443,0.000575502,0.001132809,0.0008512525],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002297811,0.0001525664,0.9925897,0.0000214868,0.00002891938,0.00006041479,0.003166319,0.00008798822,0.0002329346,0.0001311518,0.0001022174,0.00340334],"study_design_scores_gemma":[0.000001069613,0.00007464948,0.9950813,0.0000185841,0.000006819914,0.00009192434,0.004150704,0.0002321946,0.00005197249,0.0000444679,0.000241083,0.000005227992],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9982796,0.0000382471,0.0001124632,0.00004901387,0.000003093173,0.00002673676,0.00002873463,0.000003889447,0.001458274],"genre_scores_gemma":[0.9996521,0.00003819774,0.0001050676,0.000007662458,0.000003004149,0.00001280478,0.00005155871,0.000001303035,0.0001283607],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03584301,"threshold_uncertainty_score":0.0712688,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0774768757440838,"score_gpt":0.4143391794747769,"score_spread":0.3368623037306931,"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."}}