{"id":"W2470938125","doi":"","title":"Recruiting and retaining women in armed forces : the cases of Canada, Sweden and Norway","year":2013,"lang":"en","type":"dissertation","venue":"BIBSYS Brage (BIBSYS (Norway))","topic":"Gender, Security, and Conflict","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Political science; Engineering; Demographic economics; Geography; Operations management; Economics","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":[0.00497094,0.0005876973,0.0007503426,0.00315951,0.02742314,0.006690788,0.00279674,0.003613825,0.003730409],"category_scores_gemma":[0.01084123,0.0005006849,0.0005049004,0.006991102,0.007170297,0.001545312,0.00477585,0.003371254,0.0004125757],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.08138305,"about_ca_system_score_gemma":0.1168251,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9839,"about_ca_topic_score_gemma":0.9928833,"domain_scores_codex":[0.9887384,0.001965491,0.0002573456,0.0003915938,0.00244342,0.006203851],"domain_scores_gemma":[0.9907958,0.0025398,0.0008263148,0.0001798267,0.002232979,0.003425292],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0003322861,0.0004034021,0.1951375,0.0009011893,0.0000756945,0.02087421,0.6620074,0.000809814,0.0007274698,0.04201803,0.03088672,0.04582627],"study_design_scores_gemma":[0.00001558064,0.00005137071,0.07106712,0.0005551834,0.00002606749,0.0009860044,0.8945876,0.0001937851,0.0001504056,0.0003279835,0.03199521,0.00004375224],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.947866,0.003923713,0.0001509396,0.008331472,0.0001615454,0.0002068855,0.0005232241,0.00001093755,0.03882539],"genre_scores_gemma":[0.9786477,0.005360475,0.0004274632,0.002481765,0.00004198739,0.0001004688,0.0003721879,0.00002297831,0.01254501],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08138305,"threshold_uncertainty_score":0.5904781,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03549341982029682,"score_gpt":0.287647379102459,"score_spread":0.2521539592821622,"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."}}