{"id":"W6922300211","doi":"10.1184/r1/6705392.v1","title":"Estimating a Dynamic Adverse-Selection Model: Labor-Force Experience and the Changing Gender Earnings Gap 1968- 97.","year":2018,"lang":"en","type":"article","venue":"Figshare","topic":"Labor market dynamics and wage inequality","field":"Economics, Econometrics and Finance","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Rochester; Northwestern University; York University; University of Pennsylvania; University of Minnesota; Purdue University","keywords":"Earnings; Statistical discrimination; Imperfect; Productivity; Human capital; Gender gap; Gender pay gap","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.002369587,0.0003427124,0.0005178667,0.0008546432,0.0005054674,0.001011353,0.0007198166,0.0007966054,0.002771943],"category_scores_gemma":[0.005516097,0.0002707854,0.0005312896,0.001041765,0.0004719734,0.0007798616,0.001057794,0.00111632,0.0005990452],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009547716,"about_ca_system_score_gemma":0.001124227,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02648795,"about_ca_topic_score_gemma":0.02206681,"domain_scores_codex":[0.9995228,0.0002397691,0.00002138943,0.00008836585,0.00004271969,0.00008484894],"domain_scores_gemma":[0.9982308,0.001076619,0.0004262374,0.0001046159,0.00006863991,0.0000931174],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004074083,0.0003965235,0.5671773,0.00007925624,0.0003006316,0.0007121157,0.001205473,0.2608584,0.0004257193,0.08020561,0.008466121,0.07976545],"study_design_scores_gemma":[0.000129456,0.0003248515,0.1706626,0.00009044126,0.0001404034,0.0003306605,0.001392524,0.7216057,0.000503975,0.09396821,0.01078964,0.0000615664],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9408712,0.0007505704,0.04911803,0.002433126,0.00007172734,0.00007538872,0.001961917,0.00005572063,0.00466226],"genre_scores_gemma":[0.9856278,0.0004942268,0.006831669,0.0001154173,0.00004016546,0.00006815813,0.001686339,0.00001202024,0.005124243],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02648795,"threshold_uncertainty_score":0.05266756,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04865256304451031,"score_gpt":0.2601872922107544,"score_spread":0.2115347291662441,"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."}}