{"id":"W3080430851","doi":"10.2139/ssrn.4069205","title":"Import Competition and Gender Differences in Labor Reallocation","year":2022,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Global trade and economics","field":"Economics, Econometrics and Finance","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Competition (biology); Labour economics; Economics; Demographic economics; Biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009625605,0.0001491025,0.0002381924,0.0005346269,0.0003068758,0.001107783,0.000277225,0.0006350066,0.02807929],"category_scores_gemma":[0.004916801,0.0001629605,0.000324413,0.0006183069,0.000642673,0.0007217667,0.0005748149,0.0005353997,0.001365569],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003309699,"about_ca_system_score_gemma":0.0003382205,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00644282,"about_ca_topic_score_gemma":0.009434815,"domain_scores_codex":[0.9996928,0.00009108791,0.00001372409,0.00005908264,0.00003418564,0.0001090898],"domain_scores_gemma":[0.9947025,0.003343709,0.0009525053,0.0002148936,0.0001440925,0.000642251],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00346328,0.0006783897,0.9376491,0.0001288042,0.0002578838,0.001057,0.005261595,0.001177009,0.003741684,0.01444844,0.002086434,0.0300504],"study_design_scores_gemma":[0.00004861213,0.0002088999,0.9890704,0.00004132916,0.00006197666,0.0002586252,0.004195082,0.0003773494,0.0003133501,0.003727433,0.001682988,0.00001380217],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.992831,0.0007160755,0.0001206961,0.0005384765,0.00002031696,0.000003762154,0.0002037467,0.000002350571,0.005563443],"genre_scores_gemma":[0.9975701,0.0001211026,0.00002887056,0.0000427776,0.0000119939,0.000001488808,0.00007570953,0.000003257501,0.002144743],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02807929,"threshold_uncertainty_score":0.0939346,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03838745174379869,"score_gpt":0.2078806480882594,"score_spread":0.1694931963444607,"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."}}