{"id":"W1980513654","doi":"10.1177/000312240707200506","title":"Corporate Demography and Income Inequality","year":2007,"lang":"en","type":"article","venue":"American Sociological Review","topic":"Labor market dynamics and wage inequality","field":"Economics, Econometrics and Finance","cited_by":87,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Diversity (politics); Labour economics; Inequality; Wage; Economics; Proxy (statistics); Variance (accounting); Economic inequality; Demographic economics; Horizontal and vertical; Variation (astronomy); Wage dispersion; Census; Efficiency wage; Geography; Population; Sociology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004593329,0.0001759101,0.0008651724,0.0000565582,0.00008687614,0.00001984182,0.000190161,0.00007498718,0.0001546606],"category_scores_gemma":[0.0007467038,0.0001475779,0.0001719009,0.0005323998,0.0006307974,0.00006659173,0.0001079733,0.0002388035,0.00007706631],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004378181,"about_ca_system_score_gemma":0.000008249167,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001622486,"about_ca_topic_score_gemma":0.000008336921,"domain_scores_codex":[0.9981929,0.0001054766,0.0008666343,0.0004400579,0.00004138746,0.0003535641],"domain_scores_gemma":[0.9981979,0.0003496972,0.0009298035,0.0003080896,0.00004078601,0.0001737863],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000007226457,0.00003593463,0.5921894,0.0001749641,0.00002561195,0.000006926263,0.00001939224,5.026281e-8,0.000001952235,0.3875285,0.0000698014,0.01994018],"study_design_scores_gemma":[0.0001273717,0.0001270725,0.7270657,0.0000933718,0.00001004537,0.00000336378,0.00002374823,0.00001179103,4.193397e-7,0.2470725,0.02518321,0.0002813926],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9116673,0.07308915,0.00562307,0.001756995,0.00009384294,0.0002868691,0.0001033329,0.00006856685,0.007310893],"genre_scores_gemma":[0.9003839,0.09125192,0.001324661,0.006921126,0.00005011394,0.00001283269,0.00001676065,0.00001017559,0.0000285121],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.140456,"threshold_uncertainty_score":0.6018051,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06676515257192964,"score_gpt":0.2960416840640138,"score_spread":0.2292765314920842,"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."}}