{"id":"W3161598376","doi":"10.24149/wp2028","title":"The Geography of Jobs and the Gender Wage Gap","year":2020,"lang":"en","type":"article","venue":"Federal Reserve Bank of Dallas, Working Papers","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Wage; Residence; Differential (mechanical device); Economics; Labour economics; Distribution (mathematics); Spatial mismatch; Compensating differential; Demographic economics; Efficiency wage; Wage share; Mathematics","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":[0.0009397384,0.0001729537,0.0002654279,0.0005844432,0.0004630343,0.0009502437,0.0002670226,0.0004140508,0.008626923],"category_scores_gemma":[0.00366097,0.0001062136,0.0002624764,0.0006499082,0.000901994,0.0005930818,0.000898884,0.0003853391,0.0004927485],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004720501,"about_ca_system_score_gemma":0.0003604943,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004024133,"about_ca_topic_score_gemma":0.00503467,"domain_scores_codex":[0.9996215,0.0001460292,0.00001569002,0.00006125055,0.00006409246,0.00009138733],"domain_scores_gemma":[0.9986275,0.0008397013,0.0002932683,0.00005852359,0.00005353532,0.0001274899],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003930538,0.0002867372,0.7844765,0.0001346511,0.0001129749,0.0005272471,0.005398058,0.009549954,0.000832795,0.1461881,0.003737723,0.04836233],"study_design_scores_gemma":[0.00005315238,0.000238232,0.8285695,0.0001443471,0.00006423763,0.0005240156,0.009682935,0.01355886,0.0006027404,0.1328007,0.01373243,0.00002885279],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9813862,0.0006676919,0.001986258,0.001063806,0.00002812319,0.00001104158,0.000341944,0.0000085879,0.01450638],"genre_scores_gemma":[0.998847,0.0001488345,0.0001287736,0.00004093957,0.000007906025,0.000005676337,0.00006073011,0.000001981519,0.0007581642],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008626923,"threshold_uncertainty_score":0.02885985,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05082507538310851,"score_gpt":0.2837631929989474,"score_spread":0.2329381176158389,"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."}}