RSI-01: Protection against financial risks in retirement: An economic analysis of the risk of dependency / Protection contre les risques financiers à la retraite: analyse économique du risque de dépendance
Bibliographic record
Abstract
ON RECOMMANDE AUX UTILISATEURS DE COMMENCER PAR LIRE LE FICHIER «READ ME» INCLUS DANS L’ARCHIVE, QUI CONTIENT DES INFORMATIONS IMPORTANTES ET PEUT ÊTRE OUVERT AU FORMAT TEXTE BRUT AVEC LA PLUPART DES LOGICIELS D’ÉDITION. Résumé Enquête déployée en novembre 2016 par le panel Web Qu'en pensez-vous? de la firme Delvinia, pour le compte de membres de l'Institut sur la retraite et l'épargne 2 000 répondants de l'Ontario et du Québec âgés de 50 à 70 ans Questions portant sur Les caractéristiques socioéconomiques Les raisons pour avoir (ou non) acheté de l'assurance soins de longue durée et les préférences pour le type de soins de longue durée Les probabilités de choix parmi des contrats d'assurance soins de longue durée comportant des prestations, prestations de survivant et commission attribuées aléatoirement La perception des risques La littératie financière et les connaissances USERS ARE ADVISED TO START BY READING THE “READ ME” FILE INCLUDED IN THE ARCHIVE, WHICH CONTAINS IMPORTANT INFORMATION AND CAN BE OPENED IN RAW TEXT FORMAT USING MOST TEXT EDITING SOFTWARES. Summary Survey fielded in November 2016 by Delvinia's AskingCanadians web panel, on behalf of members of the Retirement and Savings Institute 2,000 respondents from Ontario and Quebec, aged 50 to 70 years old Questions on Socioeconomic characteristics Reasons for having purchased (or not) long-term care insurance and preferences regarding type of long-term care Choice probabilities for long-term care insurance contracts with randomized benefit, payout to survivors in case of death, and premium load Risk perception Financial literacy and knowledge
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| 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 | 0.002 |
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".