{"id":"W4256692176","doi":"10.1257/rct.843-4.0","title":"The Effects of Child Care Subsidies on Women’s Economic Opportunities in the Slums of Nairobi","year":2015,"lang":"en","type":"dataset","venue":"AEA Randomized Controlled Trials","topic":"Poverty, Education, and Child Welfare","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"African Population and Health Research Center; Department for International Development; Government of the United Kingdom; Comic Relief; Wellcome Trust; Styrelsen för Internationellt Utvecklingssamarbete; Bill and Melinda Gates Foundation; William and Flora Hewlett Foundation; International Development Research Centre; McGill University; Rockefeller Foundation","keywords":"Subsidy; Child care; Demographic economics; Business; Economic growth; Socioeconomics; Economics; Medicine; Pediatrics; Market economy","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.03501127,0.00042886,0.006893861,0.0002762287,0.0006334919,0.0001458601,0.001283102,0.0003534069,0.0001210509],"category_scores_gemma":[0.03047217,0.0002056703,0.001453624,0.0001161932,0.0008947678,0.00009521565,0.00003358898,0.0003179174,0.00001075821],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003407834,"about_ca_system_score_gemma":0.002001003,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008093303,"about_ca_topic_score_gemma":0.01639501,"domain_scores_codex":[0.9783488,0.0177088,0.002406918,0.0003046126,0.0007551705,0.0004756999],"domain_scores_gemma":[0.9413677,0.05462456,0.002920006,0.0007372726,0.0002458168,0.000104652],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.1952792,0.0001090685,0.000001343314,0.0001291154,0.001249836,0.000002133541,0.02351623,0.000006221599,2.472998e-7,0.004222773,0.7749887,0.000495251],"study_design_scores_gemma":[0.389202,0.00009281208,0.000003050997,0.0002196704,0.0007035517,2.915946e-7,0.02340747,4.025684e-7,0.000006128297,0.00107966,0.5851229,0.0001620154],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.007959304,0.09305337,4.247501e-7,0.01085202,0.009968274,0.02548923,0.8327469,0.00003862494,0.0198918],"genre_scores_gemma":[0.1657305,0.3959775,0.000003695166,0.002009557,0.006125498,0.01645011,0.4108654,0.00009966366,0.002738071],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4218815,"threshold_uncertainty_score":0.9985119,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02455699503644089,"score_gpt":0.304112496921905,"score_spread":0.2795555018854641,"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."}}