{"id":"W1599658449","doi":"","title":"Producing Superstars for the Economic Mundial: The Mexican Predicament with Quality of Education","year":2009,"lang":"en","type":"book-chapter","venue":"London School of Economics and Political Science Research Online (London School of Economics and Political Science)","topic":"Labor market dynamics and wage inequality","field":"Economics, Econometrics and Finance","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Lagging; Human capital; Quality (philosophy); Quarter (Canadian coin); Benchmark (surveying); Political science; Development economics; Demographic economics; Geography; Economic growth; Economics; Mathematics; Statistics; Cartography; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002374103,0.0001884516,0.0003214237,0.001495564,0.001747358,0.006794169,0.0005956925,0.0007843591,0.008275796],"category_scores_gemma":[0.009244191,0.0001652322,0.0003034012,0.002936967,0.003690399,0.002498722,0.002434318,0.001660776,0.0003683701],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003461176,"about_ca_system_score_gemma":0.001902087,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03022704,"about_ca_topic_score_gemma":0.03642921,"domain_scores_codex":[0.9988905,0.0002710675,0.00002930881,0.000154459,0.0003520523,0.0003026458],"domain_scores_gemma":[0.9921758,0.001670231,0.0031903,0.0008133193,0.001234881,0.0009154752],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000399873,0.0001874314,0.5518261,0.0003807706,0.0001672444,0.0005110377,0.00481319,0.001793173,0.0006378792,0.3228546,0.02755058,0.08887802],"study_design_scores_gemma":[0.00006498538,0.0002278776,0.8217587,0.001232615,0.0001529101,0.0003325731,0.01243611,0.001708817,0.0007594847,0.06349225,0.09776898,0.00006475727],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7417174,0.007731809,0.003519131,0.07593879,0.0002908458,0.00004028511,0.001135757,0.00007409706,0.1695519],"genre_scores_gemma":[0.9927669,0.00164957,0.0007632417,0.0009898752,0.0001003112,0.00001050466,0.0001920189,0.00001874564,0.003508766],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03022704,"threshold_uncertainty_score":0.06010216,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07502169171642237,"score_gpt":0.3547148340594035,"score_spread":0.2796931423429811,"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."}}