{"id":"W2561787847","doi":"10.3386/w22950","title":"Targeting Policies: Multiple Testing and Distributional Treatment Eﬀects","year":2016,"lang":"en","type":"report","venue":"National Bureau of Economic Research","topic":"Gender, Labor, and Family Dynamics","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Social Sciences and Humanities Research Council of Canada; Michigan Diabetes Research Center, University of Michigan","keywords":"Computer science; Economics; Econometrics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.1759277,0.001439175,0.003118416,0.00375592,0.002684992,0.004088462,0.005826353,0.003679472,0.007764561],"category_scores_gemma":[0.5300758,0.001031734,0.003348646,0.003802841,0.01443794,0.006913057,0.00474178,0.007151065,0.0004166508],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003754317,"about_ca_system_score_gemma":0.005258595,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004282812,"about_ca_topic_score_gemma":0.002960541,"domain_scores_codex":[0.6515717,0.3000457,0.006451435,0.0173889,0.02165724,0.002885123],"domain_scores_gemma":[0.3426444,0.5883785,0.02807562,0.03024551,0.00864907,0.002006859],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.002409418,0.001143776,0.1363375,0.001103156,0.004489874,0.001699895,0.005587887,0.03027907,0.001636581,0.3695008,0.01077498,0.435037],"study_design_scores_gemma":[0.0005733727,0.001423746,0.03994082,0.0004349689,0.0007551541,0.0007823731,0.002171213,0.2878456,0.004797857,0.6529886,0.008071772,0.0002145969],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1615884,0.001178448,0.8005279,0.01122858,0.0009593529,0.00215912,0.0005708722,0.0008104567,0.02097691],"genre_scores_gemma":[0.7753161,0.0002139426,0.2188637,0.0009493605,0.0002953939,0.002559789,0.0001911368,0.000100606,0.001509914],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1759277,"threshold_uncertainty_score":0.9304058,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3520851917905788,"score_gpt":0.5063554751075703,"score_spread":0.1542702833169914,"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."}}