{"id":"W2140161081","doi":"","title":"Education and Cross-Country Productivity Differences","year":2014,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Economic Growth and Productivity","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Total factor productivity; Economics; Per capita; Per capita income; Productivity; Human capital; Demographic economics; Econometrics; Economic growth; Population; Demography","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":[0.002207934,0.0003916622,0.0004543597,0.001870575,0.0002746366,0.001434662,0.0002535774,0.000426915,0.006613695],"category_scores_gemma":[0.008384123,0.0001190286,0.000796872,0.003214992,0.0004770115,0.0009395776,0.001307886,0.0007244453,0.0009563377],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00039672,"about_ca_system_score_gemma":0.0002599613,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004268796,"about_ca_topic_score_gemma":0.002933,"domain_scores_codex":[0.9988282,0.0003208062,0.00006841962,0.0002839549,0.0001497124,0.0003488534],"domain_scores_gemma":[0.989823,0.005899712,0.002252609,0.0009628958,0.0005232216,0.0005385498],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003613952,0.0001550652,0.9238092,0.0001664163,0.001249216,0.0005850029,0.0009310321,0.01178296,0.00107609,0.01225718,0.00148654,0.04613998],"study_design_scores_gemma":[0.00003656383,0.0001387505,0.9799483,0.00005654072,0.0002661007,0.0003251476,0.0007446217,0.002775471,0.001157698,0.008123768,0.006396716,0.00003033092],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9807286,0.002849743,0.003774261,0.0004174431,0.00006039569,0.00001515936,0.001737834,0.00006650778,0.01035015],"genre_scores_gemma":[0.997072,0.0004247563,0.0003056754,0.00005087593,0.00002345323,0.000007358599,0.0006820263,0.00000736706,0.001426588],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006613695,"threshold_uncertainty_score":0.02212507,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.039317205188028,"score_gpt":0.3020451268236637,"score_spread":0.2627279216356357,"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."}}