{"id":"W4405419747","doi":"10.2139/ssrn.5053890","title":"Structural Change and Inequality in Africa","year":2024,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Income, Poverty, and Inequality","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"Inequality; Political science; Mathematics; Mathematical analysis","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":[0.0006920066,0.0001340869,0.000184644,0.001163929,0.001440935,0.001732409,0.0002405493,0.0004934509,0.004869441],"category_scores_gemma":[0.002696649,0.00007405363,0.0001155015,0.002932795,0.002400981,0.001461114,0.001568247,0.0008384463,0.0001034147],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00210901,"about_ca_system_score_gemma":0.001526519,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01688023,"about_ca_topic_score_gemma":0.02917548,"domain_scores_codex":[0.9995779,0.0001337402,0.00001064987,0.00002745153,0.00004494318,0.0002052906],"domain_scores_gemma":[0.9991919,0.0003817999,0.0002094756,0.00002524093,0.00006524238,0.0001262428],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0002608258,0.0002787885,0.3028739,0.0002191156,0.00009287718,0.000795368,0.02108391,0.00352353,0.0005350267,0.6003081,0.003299044,0.06672952],"study_design_scores_gemma":[0.00002889838,0.0001337908,0.7184043,0.0004388808,0.00005353088,0.0003189899,0.03462356,0.003358464,0.0003427396,0.2078048,0.03446807,0.00002393271],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9377835,0.005665753,0.0004881248,0.01270829,0.00005800714,0.000008719484,0.0002083619,0.000004492654,0.04307467],"genre_scores_gemma":[0.9984665,0.0009157449,0.00002535163,0.00004894382,0.00002311737,0.000001949705,0.00001476324,6.713288e-7,0.0005029751],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01688023,"threshold_uncertainty_score":0.03356397,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05533374739286845,"score_gpt":0.3284421787051123,"score_spread":0.2731084313122438,"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."}}