{"id":"W1482194397","doi":"10.1086/686262","title":"How the Timing of Grade Retention Affects Outcomes: Identification and Estimation of Time-Varying Treatment Effects","year":2016,"lang":"en","type":"article","venue":"Journal of Labor Economics","topic":"School Choice and Performance","field":"Social Sciences","cited_by":82,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; University of Wisconsin-Madison","keywords":"Unobservable; Grade retention; Retention time; Selection (genetic algorithm); Retention rate; Identification (biology); Employee retention; Estimation; Econometrics; Psychology; Computer science; Developmental psychology; Economics; Academic achievement; Artificial intelligence; Biology; Chemistry","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":[0.03424692,0.0008924301,0.001926982,0.002186388,0.001473002,0.00220428,0.002967905,0.003040754,0.008540385],"category_scores_gemma":[0.09503552,0.0007056507,0.003182683,0.003819504,0.002305182,0.002143176,0.002470821,0.004172572,0.001030789],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001943947,"about_ca_system_score_gemma":0.002340235,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01723379,"about_ca_topic_score_gemma":0.009661558,"domain_scores_codex":[0.9748535,0.017009,0.001055254,0.004267336,0.001142862,0.001672219],"domain_scores_gemma":[0.908919,0.05907897,0.01726089,0.0111448,0.002146355,0.001450023],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002851701,0.002624183,0.7981923,0.0004159693,0.002721639,0.0003724493,0.0030143,0.02586466,0.001082098,0.0274612,0.004347442,0.1310521],"study_design_scores_gemma":[0.0006614232,0.003149813,0.8019061,0.0003588081,0.002686638,0.0002470904,0.002466886,0.1256472,0.003930111,0.04777065,0.01088622,0.0002890364],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8128597,0.00117126,0.173323,0.002173007,0.0003925383,0.001516625,0.003932194,0.0005130143,0.004118694],"genre_scores_gemma":[0.969696,0.0003728607,0.02096377,0.0003120092,0.0001176886,0.001974431,0.001898655,0.00005269169,0.004611965],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03424692,"threshold_uncertainty_score":0.1811172,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03173254093674505,"score_gpt":0.2964977163560911,"score_spread":0.264765175419346,"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."}}