{"id":"W2129152249","doi":"","title":"Gender Discrimination and Growth: Theory and Evidence from India","year":2004,"lang":"en","type":"article","venue":"London School of Economics and Political Science Research Online (London School of Economics and Political Science)","topic":"Gender, Labor, and Family Dynamics","field":"Social Sciences","cited_by":216,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Gender discrimination; Economics; Human capital; Inequality; Investment (military); Stigma (botany); Per capita; Demographic economics; Gender inequality; Labour economics; Sociology; Political science; Psychology; Economic growth; 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":[0.0008336107,0.0002371421,0.0002451312,0.001817961,0.0007939281,0.001488005,0.0005796321,0.000470405,0.003661878],"category_scores_gemma":[0.003676901,0.0001739006,0.0003500211,0.004746278,0.002059665,0.0007303763,0.001189718,0.000778531,0.0003682153],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001345753,"about_ca_system_score_gemma":0.000692996,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06412909,"about_ca_topic_score_gemma":0.05234073,"domain_scores_codex":[0.9996233,0.0001233652,0.00002137286,0.00004899197,0.00007273057,0.000110341],"domain_scores_gemma":[0.9936821,0.003968894,0.001461425,0.0002452646,0.000395197,0.0002471896],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002297781,0.0001792017,0.898824,0.0003681654,0.0001576127,0.0007411423,0.00845388,0.003455736,0.000165579,0.02334206,0.004496763,0.05958606],"study_design_scores_gemma":[0.00001416758,0.00007257258,0.9710516,0.0002160285,0.0001258664,0.0002675953,0.01049481,0.001985286,0.0002392725,0.007370991,0.008136614,0.0000252087],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9579751,0.008802139,0.0004622561,0.002942318,0.00002947361,0.00001270682,0.001026566,0.00001748556,0.02873196],"genre_scores_gemma":[0.9957607,0.003448014,0.00007744053,0.00009107198,0.00002179882,0.000003178988,0.0002240844,0.000002356636,0.0003712862],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06412909,"threshold_uncertainty_score":0.1275116,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06807607560565652,"score_gpt":0.3744138772859288,"score_spread":0.3063378016802723,"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."}}