Bibliographic record
Abstract
Dans cet article, nous analysons le lien entre l’âge de déclenchement de la rente de retraite du Régime de rentes du Québec (RRQ) et le revenu disponible (après impôts) une fois à la retraite. Malgré le fait que plusieurs déclenchent hâtivement la rente, nous montrons que ceux-ci atteignent un taux de remplacement à la retraite particulièrement élevé au Québec. Font-ils un bon choix de prendre la rente hâtivement? Nous exploitons un modèle prédictif de la mortalité estimé sur des données fiscales incorporant les effets du Supplément de revenu garanti (SRG) sur le report de la rente. Nous montrons que l’hétérogénéité d’espérance de vie n’est pas suffisante pour justifier financièrement un âge hâtif du début de la rente. Nous montrons que le gain financier du report est grandement affecté par la récupération du SRG, qui touche plus de 40% des cotisants. Malgré cet impact, le rendement alternatif mesuré par le rendement moyen effectif observé sur l’épargne demeure faible en comparaison, même sans ajustement pour le risque accru dans un placement alternatif.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".