{"id":"W2821184134","doi":"10.5465/ambpp.2018.62","title":"Does Occupational Licensing Increase Income Inequality?","year":2018,"lang":"en","type":"article","venue":"Academy of Management Proceedings","topic":"Occupational and Professional Licensing Regulation","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Wage; Quantile regression; Distribution (mathematics); Economics; Inequality; Labour economics; Wage inequality; Quantile; Demographic economics; Occupational licensing; Econometrics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.00314254,0.0002443341,0.0006045293,0.001394438,0.001365871,0.002223136,0.001259407,0.001041282,0.009361278],"category_scores_gemma":[0.01624359,0.0001887435,0.00104468,0.002423149,0.001652524,0.001143097,0.001947145,0.001688614,0.0004597681],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008005024,"about_ca_system_score_gemma":0.006048296,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.7385554,"about_ca_topic_score_gemma":0.6750697,"domain_scores_codex":[0.9966092,0.000568889,0.0000842369,0.0004649333,0.0004891364,0.001783686],"domain_scores_gemma":[0.9937178,0.002460391,0.001878227,0.0005061147,0.0008216102,0.0006158149],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001347552,0.0001130016,0.9538359,0.00005064257,0.0001801206,0.000161557,0.001361088,0.002018659,0.0001165174,0.01195219,0.002179788,0.02789585],"study_design_scores_gemma":[0.00001027056,0.00003760587,0.9872365,0.00007880684,0.0001005066,0.00002311624,0.001726678,0.003370647,0.0001224568,0.002707447,0.004572392,0.00001341784],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9546152,0.003002678,0.002864876,0.009141226,0.00009061908,0.0000720239,0.002392024,0.00006981076,0.02775142],"genre_scores_gemma":[0.9975197,0.0003204595,0.0001332453,0.0001689663,0.00002529365,0.000008219778,0.0002876559,0.000007081805,0.001529371],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7385554,"threshold_uncertainty_score":0.5259687,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04088179532349022,"score_gpt":0.2863112908726506,"score_spread":0.2454294955491604,"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."}}