{"id":"W1557454727","doi":"","title":"Le Remboursement Proportionnel au Revenu (RPR) : Un système pour les prêts d'études alliant efficacité et accessibilité","year":2006,"lang":"fr","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Canadian Policy and Governance","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Political science; Humanities; Art","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01383898,0.0004964027,0.0007567281,0.002516356,0.003640213,0.007352498,0.00196475,0.001691804,0.01793152],"category_scores_gemma":[0.02543757,0.0005646701,0.00079247,0.003510931,0.004074905,0.005836698,0.003667517,0.002205308,0.001711808],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0162579,"about_ca_system_score_gemma":0.02839717,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2058895,"about_ca_topic_score_gemma":0.2153912,"domain_scores_codex":[0.9899823,0.004467637,0.0005241482,0.001661036,0.002387027,0.0009779121],"domain_scores_gemma":[0.9868089,0.00328007,0.00209807,0.002858368,0.003525393,0.001429295],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002433076,0.0001265345,0.02096109,0.0005148537,0.0001411943,0.000150421,0.004520986,0.007980198,0.002742776,0.6880146,0.01915996,0.2554441],"study_design_scores_gemma":[0.0002983315,0.0008483276,0.0939958,0.0008830816,0.0002288799,0.0007040295,0.004050315,0.03623163,0.00419863,0.247428,0.6107334,0.0003995724],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1988574,0.006359652,0.4374046,0.03728822,0.0005647605,0.001679194,0.004146778,0.002629731,0.3110696],"genre_scores_gemma":[0.7778556,0.001630602,0.1580722,0.0009240404,0.0001957308,0.0005665199,0.0005647242,0.0002791735,0.05991138],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9837421,"threshold_uncertainty_score":0.4093822,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04366812275821439,"score_gpt":0.3390436551880964,"score_spread":0.295375532429882,"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."}}