{"id":"W4394913380","doi":"10.1016/j.econlet.2024.111711","title":"Increasing student access through aid: Differences in difference-in-differences estimates","year":2024,"lang":"en","type":"article","venue":"Economics Letters","topic":"Poverty, Education, and Child Welfare","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Difference in differences; Economics; Econometrics; Psychology; Mathematics education; Demographic economics; Statistics; Mathematics","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":[0.01779847,0.0003483342,0.0007769379,0.001976416,0.0003533447,0.001735389,0.001472846,0.0008423104,0.007639535],"category_scores_gemma":[0.07573102,0.0002537978,0.001770611,0.001926743,0.001117387,0.001812596,0.002725174,0.002216954,0.0006692988],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000517516,"about_ca_system_score_gemma":0.0005730551,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01044907,"about_ca_topic_score_gemma":0.008774587,"domain_scores_codex":[0.9863658,0.009883543,0.0007052703,0.0008416942,0.001263222,0.0009405385],"domain_scores_gemma":[0.8646029,0.1180668,0.004237445,0.00731919,0.00409719,0.001676526],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001386413,0.0004766826,0.9388412,0.0001925653,0.002206005,0.0001640548,0.0009585603,0.005526158,0.0006869241,0.01233191,0.002633106,0.03459646],"study_design_scores_gemma":[0.00012184,0.0007637132,0.955584,0.0000876939,0.001180636,0.0003244376,0.004264963,0.01644062,0.002633212,0.01261268,0.005918306,0.00006794482],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9711292,0.0009666415,0.01445584,0.001409154,0.0001553997,0.00008807152,0.0023153,0.00007812637,0.009402323],"genre_scores_gemma":[0.9969681,0.0001077045,0.001106545,0.00008000967,0.00002964997,0.00001845919,0.000773054,0.00001149882,0.0009050397],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01779847,"threshold_uncertainty_score":0.09412843,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03880214642925866,"score_gpt":0.3164538594482564,"score_spread":0.2776517130189977,"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."}}