{"id":"W2108528580","doi":"10.1111/jors.12197","title":"THE URBAN–RURAL GAP IN UNIVERSITY ATTENDANCE: DETERMINANTS OF UNIVERSITY PARTICIPATION AMONG CANADIAN YOUTH","year":2015,"lang":"en","type":"article","venue":"Journal of Regional Science","topic":"Urban, Neighborhood, and Segregation Studies","field":"Social Sciences","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Statistics Canada; McMaster University","funders":"","keywords":"Attendance; Incentive; Demographic economics; Work (physics); Immigration; Survey data collection; Hierarchy; Geography; Economic growth; Sociology; Socioeconomics; Political science; Economics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002161312,0.00004639039,0.0001095193,0.0001872448,0.0007266471,0.00002637656,0.00045725,0.00003086449,0.000003128625],"category_scores_gemma":[0.0004835942,0.00003597292,0.00004318127,0.0008778703,0.001688233,0.0006763099,0.00002975044,0.00009271556,0.000001316494],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005914737,"about_ca_system_score_gemma":0.00216327,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1011344,"about_ca_topic_score_gemma":0.4759814,"domain_scores_codex":[0.99868,0.0001760269,0.000154006,0.00007501814,0.0006659713,0.000248958],"domain_scores_gemma":[0.9985607,0.0001524768,0.0002874941,0.0000652104,0.0006387402,0.0002954228],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005410565,0.00001538076,0.9613468,8.390094e-7,0.000004152167,0.00001909932,0.03279405,0.0000596629,0.000005998616,0.003994688,0.0009899924,0.0007152093],"study_design_scores_gemma":[0.0003774469,0.00006165323,0.8433471,0.00004500438,0.00001407317,0.000002220032,0.1407413,0.0001977246,0.00001440418,0.000347177,0.01477671,0.00007516688],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9937617,0.00008326052,0.00001694444,0.001259264,0.0002300559,0.00004902947,0.000003074377,0.000002275629,0.004594411],"genre_scores_gemma":[0.9989625,0.0001148721,0.00003196745,0.00002239001,0.0000573976,3.115747e-8,1.065115e-7,0.000001093023,0.0008095995],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3748471,"threshold_uncertainty_score":0.9048513,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08766928659882173,"score_gpt":0.3031111381048531,"score_spread":0.2154418515060314,"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."}}