{"id":"W2160634710","doi":"","title":"Dropout, School Performance and Working while in School : An Econometric Model with Heterogeneous Groups","year":2001,"lang":"en","type":"preprint","venue":"Érudit documents and data repository (Érudit Consortium, University of Montreal)","topic":"School Choice and Performance","field":"Social Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"School dropout; Microdata (statistics); Dropout (neural networks); Unemployment; Context (archaeology); Demographic economics; Economics; Humanities; Political science; Labour economics; Psychology; Sociology; Demography; Geography; Economic growth; Population; Art; Census","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006483957,0.0004228285,0.0006735934,0.000531168,0.000984417,0.0002974177,0.001280588,0.0003937394,0.00009255075],"category_scores_gemma":[0.00006099439,0.0004638328,0.00005862552,0.0003796464,0.000557443,0.001899121,0.001236595,0.0007058564,0.000007128127],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006250415,"about_ca_system_score_gemma":0.0006188163,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.0406439,"about_ca_topic_score_gemma":0.09847904,"domain_scores_codex":[0.9969358,0.0002115996,0.0004769017,0.001276771,0.0005312412,0.0005676359],"domain_scores_gemma":[0.997152,0.0001099941,0.0006364331,0.001337709,0.0001397263,0.0006241073],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006721985,0.0002762048,0.9750447,0.0002755417,0.0002904311,0.0004227546,0.001111582,0.007225611,0.00001126318,0.0001188572,0.002179252,0.0123716],"study_design_scores_gemma":[0.01513685,0.001585759,0.5766887,0.005279485,0.002281078,0.0004299079,0.01682818,0.1983922,0.00009003772,0.001659171,0.1749663,0.006662246],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9835964,0.002199108,0.000104145,0.0002237584,0.00023014,0.0006182262,0.0001625236,0.00006912866,0.01279652],"genre_scores_gemma":[0.9716474,0.02454078,0.0006213253,0.00004905805,0.0002832045,0.000004200785,0.0002301804,0.00002650379,0.002597315],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.398356,"threshold_uncertainty_score":0.9997813,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02963304525394727,"score_gpt":0.2526150006712937,"score_spread":0.2229819554173464,"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."}}