{"id":"W4293065657","doi":"10.1016/j.healthpol.2022.08.007","title":"The gender earnings gap in medicine: Evidence from Canada","year":2022,"lang":"en","type":"article","venue":"Health Policy","topic":"Diversity and Career in Medicine","field":"Social Sciences","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Earnings; Receipt; Demographic economics; Revenue; Distribution (mathematics); Census; Business; Economics; Demography; Accounting; Population","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.002854978,0.00004791886,0.0001110156,0.00005010813,0.001912214,0.00001320637,0.0005357274,0.00001658231,0.0006717238],"category_scores_gemma":[0.001245963,0.00003852036,0.00001202958,0.000521611,0.0002118905,0.00004638244,0.0001292665,0.0003012016,0.000005690048],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001324668,"about_ca_system_score_gemma":0.006606565,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.998893,"about_ca_topic_score_gemma":0.9811781,"domain_scores_codex":[0.9975228,0.0006742207,0.000153563,0.0001306607,0.001111994,0.000406789],"domain_scores_gemma":[0.9988823,0.0006742122,0.00008443203,0.0001339455,0.00002885189,0.0001962623],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001915024,0.00000909751,0.05204018,0.0000152295,0.000006734852,0.00002316916,0.1828686,0.00004638154,0.000001627257,0.02053688,0.7313725,0.01306045],"study_design_scores_gemma":[0.0001348006,0.00003289898,0.05920312,0.00002425222,0.000001708246,3.605454e-7,0.1083826,0.000005740271,1.360529e-7,0.001114285,0.8310611,0.00003895912],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.1488983,0.004134057,0.000004838036,0.8172298,0.001147093,0.0002608799,0.00001744798,0.00002845461,0.02827918],"genre_scores_gemma":[0.9402434,0.001464808,0.000008132364,0.05475066,0.0008305605,0.00001431181,0.00000384744,0.000003772204,0.002680471],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7913452,"threshold_uncertainty_score":0.9993871,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.146527138470129,"score_gpt":0.4219264662028746,"score_spread":0.2753993277327456,"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."}}