{"id":"W2315067022","doi":"10.1177/1462474516635884","title":"“It’s for their own good”: Techniques of neutralization and security guard violence against psychiatric patients","year":2016,"lang":"en","type":"article","venue":"Punishment & Society","topic":"Torture, Ethics, and Law","field":"Social Sciences","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University; University of Ottawa","funders":"","keywords":"Harm; Security guard; Guard (computer science); Intervention (counseling); Use of force; Criminology; Militant; Psychological intervention; Feeling; Power (physics); Law; Psychology; Medicine; Psychiatry; Political science; Social psychology; Politics; Computer security; International law","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007997206,0.0001200297,0.0001652261,0.00001646315,0.0003841458,0.00003511246,0.0001956082,0.0002044352,0.00001135686],"category_scores_gemma":[0.00007268063,0.00008447689,0.0001561945,0.000132173,0.0003941386,0.0002240928,0.00004225229,0.00008581517,5.791622e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000909682,"about_ca_system_score_gemma":0.00009572378,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00015029,"about_ca_topic_score_gemma":0.0003096309,"domain_scores_codex":[0.9988679,0.0000965354,0.0002473265,0.0002456411,0.0002817302,0.000260866],"domain_scores_gemma":[0.9991848,0.0001624135,0.0002000886,0.0001542514,0.0002147281,0.00008366744],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007921746,0.001164687,0.3332556,0.0005103499,0.0001833425,1.830224e-7,0.2408826,8.150707e-7,0.001271574,0.1574256,0.07601982,0.1892063],"study_design_scores_gemma":[0.001702866,0.000434956,0.02489998,0.0004209167,0.00008758916,1.154695e-7,0.0126115,0.00003212004,0.006601687,0.08305554,0.8694647,0.0006880666],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9508731,0.0008537389,0.004271804,0.02186776,0.001275046,0.003041053,0.0003669737,0.0003994188,0.01705112],"genre_scores_gemma":[0.9909761,0.006362916,0.001014596,0.001273068,0.000182712,0.00005048386,0.00001369404,0.00001088556,0.0001155388],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7934449,"threshold_uncertainty_score":0.3444868,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01667443889338077,"score_gpt":0.2901546790288104,"score_spread":0.2734802401354296,"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."}}