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Record W6913017226 · doi:10.5683/sp2/pp5u7y

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

2019· dataset· fr· W6913017226 on OpenAlexaffabout

Bibliographic record

VenueBorealis · 2019
Typedataset
Languagefr
Field
Topic
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsEconomic analysisCommissionLife insuranceQuarter (Canadian coin)Economic impact analysisDependency (UML)

Abstract

fetched live from OpenAlex

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

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.375
Threshold uncertainty score0.745

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.002

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.

Opus teacher head0.035
GPT teacher head0.270
Teacher spread0.235 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreDataset

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".

Quick stats

Citations1
Published2019
Admission routes2
Has abstractyes

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