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Record W3083632884

Portrait sociodémographique des aînés - Région de Laval

2020· article· fr· W3083632884 on OpenAlexaboutno aff
Nassirou Ibrahim, Alexandre Prud’homme, Jolianne Bolduc, Roxane Borgès Da Silva

Bibliographic record

VenueCIRANO Project Reports · 2020
Typearticle
Languagefr
FieldHealth Professions
TopicAging, Elder Care, and Social Issues
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHumanitiesArt
DOInot available

Abstract

fetched live from OpenAlex

Le vieillissement de la population est un phénomène qui touche la majorité des sociétés occidentales. Ce phénomène se traduit par une croissance du poids relatif, en proportion de la population totale, des personnes âgées de 65 ans et plus, combinée à une décroissance de la proportion des autres groupes d’âge. Cette réalité démographique engendre de nouveaux enjeux sociaux et économiques concernant spécifiquement les aînés tels que l’accès au logement, la précarité financière, l’isolement social et la mise en place de structures adéquates (ex. : soins à domicile) permettant de combler les besoins en assistance et en soins. Des actions publiques sont alors nécessaires afin d’assurer une qualité de vie adéquate à ce groupe d’individus généralement plus vulnérables que l’ensemble de la population. Des données probantes et à jour sont essentielles à la prise de décisions et la mise en place d’actions concrètes. Si ces données existent aux niveaux fédéral et provincial, une carence s’observe au niveau régional. Il s’agit du cas de la région de Laval. Dans le but de combler cette insuffisance, ce document présente le portrait sociodémographique et économique des personnes de 65 ans et plus de la région de Laval à partir des données de recensement de Statistique Canada.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.605
Threshold uncertainty score0.786

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.001

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.

Opus teacher head0.070
GPT teacher head0.379
Teacher spread0.309 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2020
Admission routes1
Has abstractyes

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