{"id":"W4417397913","doi":"10.2139/ssrn.5922580","title":"On Productivity and Distortions across Countries","year":2025,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Corruption and Economic Development","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Productivity; Developing country; Exploit; Production (economics); Download; Empirical research; Aggregate (composite)","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":[0.003190472,0.000600135,0.001622089,0.002704504,0.0007840093,0.003237229,0.0005104712,0.001413374,0.01409609],"category_scores_gemma":[0.02350085,0.0003314859,0.0006869151,0.005060291,0.003414083,0.003712844,0.002955812,0.001878019,0.0006181087],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003406623,"about_ca_system_score_gemma":0.001588252,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009890627,"about_ca_topic_score_gemma":0.004885616,"domain_scores_codex":[0.9980335,0.0008459304,0.000109591,0.0002486094,0.0003625953,0.0003998389],"domain_scores_gemma":[0.9715575,0.02131506,0.003671225,0.001475259,0.001472454,0.0005085327],"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":[0.0002471137,0.00007776461,0.02105431,0.000283889,0.0003084262,0.0003062309,0.0007501139,0.04354677,0.0003560408,0.8898056,0.006179113,0.03708462],"study_design_scores_gemma":[0.00004823066,0.00007505387,0.01788124,0.0001775635,0.0001432649,0.0001635417,0.00106222,0.009831349,0.0003372372,0.9636741,0.00657261,0.0000335613],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7488979,0.0164586,0.02579369,0.02696947,0.0003767122,0.00006752867,0.002492683,0.0001211983,0.1788222],"genre_scores_gemma":[0.9859672,0.004921225,0.0008998379,0.0003373374,0.000235682,0.00002485911,0.0002149229,0.00002867396,0.007370407],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01409609,"threshold_uncertainty_score":0.0471561,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01512877564669771,"score_gpt":0.3187199502140149,"score_spread":0.3035911745673172,"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."}}