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Record W2524836701 · doi:10.1017/s0714980816000477

Université du troisième âge : les besoins en formation continue des personnes âgées francophones au Nouveau-Brunswick

2016· article· en· W2524836701 on OpenAlexaffabout
Suzanne Dupuis‐Blanchard, Danielle Thériault, Lise Mazerolle

Bibliographic record

VenueCanadian Journal on Aging / La Revue canadienne du vieillissement · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicRetirement, Disability, and Employment
Canadian institutionsUniversité de Moncton
Fundersnot available
KeywordsContinuing educationAutonomyGerontologyPsychologyPolitical scienceSociologyMedical educationMedicine

Abstract

fetched live from OpenAlex

Continuing education is the ideal mechanism to allow retired people to maintain their autonomy and health for as long as possible. Despite the importance of education in the development of human beings, very few studies have been identified on the need for continued education in older adults. This quantitative descriptive study allowed us to better understand the interests and the needs of seniors related to continuing education in French-speaking older adults in New Brunswick (n = 408), and to identify the perceptions of participants with regard to the benefits, the challenges and the preferences of seniors for continuing education. Study results indicate that the main interests of participants were for training in technology (computers), gardening and health matters. Given the lack of research in this domain, these results will be useful for future planning of continuing education initiatives for seniors.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.120
Threshold uncertainty score0.241

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.031
GPT teacher head0.259
Teacher spread0.227 · 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

Citations3
Published2016
Admission routes2
Has abstractyes

Explore more

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