{"id":"W3123183447","doi":"","title":"Income Inequality and Economic Development: Evidence from the Threshold Regression Model","year":2000,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Income, Poverty, and Inequality","field":"Social Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Economics; Economic inequality; Inequality; Econometrics; Panel data; Sample (material); Regression; Threshold model; Economic model; Regression analysis; Income inequality metrics; Income distribution; Mathematics; Statistics; Macroeconomics","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":[0.00592098,0.000428708,0.001057934,0.001202749,0.0006066253,0.001761058,0.001105246,0.0008715242,0.005598355],"category_scores_gemma":[0.02519442,0.0003143441,0.0009068513,0.004128991,0.001091733,0.001581031,0.00181146,0.00188058,0.0007610273],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004883535,"about_ca_system_score_gemma":0.0004475692,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01359487,"about_ca_topic_score_gemma":0.007326215,"domain_scores_codex":[0.9970773,0.001945671,0.0001156401,0.0003264748,0.000242922,0.0002919618],"domain_scores_gemma":[0.9648435,0.0220311,0.006735445,0.004130248,0.00118748,0.001072198],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001652248,0.0005666245,0.8024461,0.0002979291,0.002897008,0.0006668457,0.0009308123,0.07273518,0.0007592817,0.06430244,0.01189453,0.04085106],"study_design_scores_gemma":[0.0003218152,0.0004925526,0.4664038,0.0001612553,0.001693404,0.000535654,0.001345932,0.3828441,0.001071234,0.13966,0.005360411,0.0001099213],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9569066,0.002322068,0.02711291,0.002566966,0.00007160237,0.00003535078,0.002255483,0.0001622465,0.008566748],"genre_scores_gemma":[0.9972836,0.0005782729,0.0008133863,0.0001006534,0.00003998551,0.00001165553,0.0006752457,0.0000128304,0.0004843281],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01359487,"threshold_uncertainty_score":0.03131348,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1131283096451735,"score_gpt":0.3859250136064982,"score_spread":0.2727967039613247,"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."}}