{"id":"W2610436526","doi":"10.1080/23337486.2017.1320055","title":"Unmaking militarized masculinity: veterans and the project of military-to-civilian transition","year":2017,"lang":"en","type":"article","venue":"Critical Military Studies","topic":"Gender, Security, and Conflict","field":"Social Sciences","cited_by":113,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mount Saint Vincent University","funders":"Social Sciences and Humanities Research Council of Canada; Canada Research Chairs; Medical Research Council; Australian Government; U.S. Department of Veterans Affairs","keywords":"Militarization; Masculinity; Militarism; Gender studies; Liminality; Sociology; Political science; Law; Politics","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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":["sts"],"category_scores_codex":[0.00179186,0.000198266,0.0005304622,0.00006623549,0.002687721,0.00002102756,0.0004376993,0.00009540424,0.00001942544],"category_scores_gemma":[0.0051197,0.0001455543,0.0002084219,0.0001010287,0.005210917,0.0002676627,0.000151458,0.0002013522,0.000006311905],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003723047,"about_ca_system_score_gemma":0.00008533199,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02017781,"about_ca_topic_score_gemma":0.02233742,"domain_scores_codex":[0.9977074,0.0006187641,0.0003765358,0.0004076643,0.0004242711,0.0004653856],"domain_scores_gemma":[0.9977898,0.00123824,0.00002561043,0.0004962322,0.0003210191,0.0001291045],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0007501871,0.0001819078,0.0009477808,0.0006149834,0.0003842693,0.00002341054,0.9470459,0.000003159577,0.0001054279,0.04149273,0.001266751,0.007183507],"study_design_scores_gemma":[0.004854513,0.0006735699,0.02755871,0.0006006503,0.0007216364,0.000006839703,0.8496614,0.0004000888,0.0000985252,0.09026107,0.02434326,0.0008197987],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8519644,0.06392357,0.0002133983,0.07483719,0.0008788187,0.001278907,0.00008164063,0.00007590411,0.00674614],"genre_scores_gemma":[0.9927356,0.005494319,0.0005960022,0.0007435998,0.0002527084,0.00007287202,0.000001728296,0.00001037283,0.00009279863],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1407712,"threshold_uncertainty_score":0.9986106,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09518919167536642,"score_gpt":0.4037873214610966,"score_spread":0.3085981297857301,"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."}}