{"id":"W3122064841","doi":"10.3386/w20876","title":"Wage Inequality and Firm Growth","year":2015,"lang":"en","type":"preprint","venue":"National Bureau of Economic Research","topic":"Labor market dynamics and wage inequality","field":"Economics, Econometrics and Finance","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Wage inequality; Inequality; Wage; Economics; Labour economics; 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":[0.000773211,0.0002323239,0.0002998998,0.002081344,0.0005010945,0.001470233,0.0003784951,0.0004214214,0.005986033],"category_scores_gemma":[0.005911327,0.00007950149,0.0003065139,0.003450353,0.0005667512,0.001010422,0.001141378,0.0009335939,0.0006639881],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008538325,"about_ca_system_score_gemma":0.0003553585,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01236484,"about_ca_topic_score_gemma":0.01301484,"domain_scores_codex":[0.9994889,0.00007920387,0.0000277354,0.0000978486,0.00008205239,0.0002241095],"domain_scores_gemma":[0.9936548,0.002336879,0.002644693,0.0003038907,0.0004555643,0.0006040708],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001236541,0.0001006471,0.9475433,0.00006447242,0.0001048125,0.0002802285,0.0007322353,0.006857613,0.0004329346,0.01837151,0.001831537,0.02355718],"study_design_scores_gemma":[0.000009337958,0.00004987005,0.9731936,0.00005908236,0.0000240936,0.0001189012,0.001081231,0.008337083,0.0003121626,0.01218258,0.004619064,0.00001289805],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.976028,0.001635674,0.001723079,0.001375836,0.00003429462,0.00001324115,0.002424318,0.00003631438,0.01672932],"genre_scores_gemma":[0.9978283,0.0002325145,0.0001081398,0.00003174596,0.00002623285,0.000006241727,0.0007767418,0.000003705059,0.0009863504],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01236484,"threshold_uncertainty_score":0.02458572,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3637882285507522,"score_gpt":0.456585733464423,"score_spread":0.09279750491367084,"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."}}