{"id":"W3121168755","doi":"10.3386/w13340","title":"The Effect of Credit Constraints on the College Drop-Out Decision A Direct Approach Using a New Panel Study","year":2007,"lang":"en","type":"report","venue":"National Bureau of Economic Research","topic":"Higher Education Research Studies","field":"Social Sciences","cited_by":59,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Spencer Foundation; Andrew W. Mellon Foundation; National Science Foundation","keywords":"Drop (telecommunication); Panel data; Drop out; Econometrics; Economics; Computer science; Actuarial science; Business; Demographic economics; Telecommunications","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","sts"],"consensus_categories":["metaresearch","sts"],"category_scores_codex":[0.06764955,0.0002581304,0.0006803729,0.0007871524,0.001697227,0.0001548913,0.0014836,0.0002983524,0.0004652937],"category_scores_gemma":[0.0314734,0.0001565828,0.0002582312,0.0006996415,0.002949361,0.00009255973,0.0003174998,0.001051075,0.00005597114],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003306905,"about_ca_system_score_gemma":0.01625386,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01094767,"about_ca_topic_score_gemma":0.002275353,"domain_scores_codex":[0.9879953,0.003166266,0.0009596689,0.0006117271,0.006527628,0.0007394431],"domain_scores_gemma":[0.9507341,0.04532336,0.0005256445,0.0005271792,0.002683144,0.000206608],"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":[0.001294602,0.001128809,0.02001781,0.0002542213,0.00271243,0.00001565784,0.0135319,0.0004678622,0.00005190427,0.1352496,0.7980141,0.02726104],"study_design_scores_gemma":[0.009440491,0.007805206,0.04076661,0.002535435,0.0005433964,0.00003507632,0.116356,0.001631348,0.001112561,0.1190712,0.6980417,0.002660909],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.03860774,0.0007573476,0.00001151073,0.001290749,0.001117982,0.004678776,0.0001429137,0.0000162755,0.9533767],"genre_scores_gemma":[0.979601,0.0007819302,0.0000880263,0.000006792964,0.00179704,0.0002228353,0.00002221853,0.00003477193,0.01744535],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9409933,"threshold_uncertainty_score":0.999764,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5123957849261382,"score_gpt":0.5994190069953745,"score_spread":0.0870232220692363,"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."}}