{"id":"W3029735766","doi":"10.1515/bejeap-2019-0269","title":"Hi-tech Sexism? Evidence from Bangladesh","year":2020,"lang":"en","type":"article","venue":"The B E Journal of Economic Analysis & Policy","topic":"Demographic Trends and Gender Preferences","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Abortion; Quarter (Canadian coin); Preference; Demography; Odds; Girl; Confidence interval; Hazard ratio; China; Odds ratio; Economics; Medicine; Psychology; Geography; Pregnancy; Sociology; Developmental psychology","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001222469,0.0001159794,0.000409922,0.0003058655,0.0002823523,0.0001239853,0.001039589,0.00006749439,0.001150131],"category_scores_gemma":[0.0002326004,0.00008009606,0.0004646791,0.000923477,0.000237506,0.0003676943,0.00006588207,0.0002243117,0.0000882863],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009866605,"about_ca_system_score_gemma":0.0004954737,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02274496,"about_ca_topic_score_gemma":0.008886542,"domain_scores_codex":[0.9984336,0.0004173519,0.000521342,0.000147067,0.0002327339,0.000247876],"domain_scores_gemma":[0.9983781,0.0004771061,0.000609296,0.0002045388,0.00006427973,0.0002667026],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004613556,0.0001467547,0.4175673,0.00001493918,0.01741331,0.00002903975,0.3614268,0.01352321,0.0006309369,0.04795427,0.0362427,0.1045894],"study_design_scores_gemma":[0.002011132,0.0007779441,0.523541,0.0001677048,0.01800274,0.0000168196,0.104568,0.008248008,0.0006580946,0.1282414,0.2119867,0.001780474],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9027696,0.002468086,0.0009489611,0.08425502,0.000144677,0.00006090331,0.0000212999,0.00002444769,0.009307024],"genre_scores_gemma":[0.9941025,0.002482076,0.0001558621,0.001143318,0.001710417,6.831027e-7,0.000001234822,0.000006022185,0.000397933],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2568588,"threshold_uncertainty_score":0.999763,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09074155633213514,"score_gpt":0.3538606555058393,"score_spread":0.2631190991737041,"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."}}