{"id":"W3148246334","doi":"10.1257/mac.20200318","title":"Hours, Occupations, and Gender Differences in Labor Market Outcomes","year":2022,"lang":"en","type":"article","venue":"American Economic Journal Macroeconomics","topic":"Gender, Labor, and Family Dynamics","field":"Social Sciences","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Nonmarket forces; Narrative; Productivity; Welfare; Economics; Labour economics; Demographic economics; Microeconomics; Factor market; Economic growth; Market economy","routes":{"ca_aff":true,"ca_fund":false,"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":[],"consensus_categories":[],"category_scores_codex":[0.001173553,0.0001874132,0.0004408403,0.0002816502,0.0008993212,0.0002273952,0.0004619026,0.00003783128,0.0008448901],"category_scores_gemma":[0.0000499949,0.0002125995,0.00009417938,0.0001326749,0.0004885601,0.0003096292,0.000161277,0.0004401105,0.00001674549],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009915375,"about_ca_system_score_gemma":0.0006239729,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002838559,"about_ca_topic_score_gemma":0.003904729,"domain_scores_codex":[0.9981585,0.0003682094,0.000523325,0.0003194764,0.000104362,0.0005261706],"domain_scores_gemma":[0.9988328,0.0002720044,0.0004638103,0.000175331,0.00002243008,0.0002336329],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002144391,0.00003533423,0.9832985,0.000001517339,0.00005242429,0.000006965295,0.005981857,0.0004156621,6.418904e-7,0.004488687,0.001177141,0.004519782],"study_design_scores_gemma":[0.0004544375,0.0000541819,0.9221194,0.000001364013,0.00001366509,0.00002577101,0.06269092,0.0007756191,9.270544e-8,0.004711008,0.008888991,0.0002644785],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9906908,0.0002604794,0.00005292352,0.001873302,0.0008556347,0.0001592382,0.0001806206,0.00002559971,0.005901408],"genre_scores_gemma":[0.9936929,0.003149175,0.0006259052,0.001675512,0.0001699332,0.00002445473,0.000005145521,0.00002433062,0.0006326392],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06117908,"threshold_uncertainty_score":0.9250954,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01944023007201895,"score_gpt":0.2811563708652293,"score_spread":0.2617161407932103,"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."}}