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Record W2091596815 · doi:10.7202/038499ar

Autour des départs à la retraite

2009· article· fr· W2091596815 on OpenAlexaffvenueabout
Catherine Arseneault

Bibliographic record

VenueEthnologies · 2009
Typearticle
Languagefr
FieldSocial Sciences
TopicDiverse Cultural and Historical Studies
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsHumanitiesArtPolitical science

Abstract

fetched live from OpenAlex

Prendre la décision de se retirer du marché du travail constitue une étape importante dans la vie d’une personne. À cette étape, le futur retraité se retrouve tout autant au terme de sa carrière, qu’au seuil d’une période nouvelle de sa vie. Comment alors souligner ce passage ? Au Québec, plusieurs usages rituels accompagnent les départs à la retraite et les réactions en regard à ces festivités s’avèrent toutes aussi diverses que les manières de partir. En s’appuyant sur un travail de terrain ethnologique, cet article se penche sur la pratique rituelle spécifique aux départs à la retraite. Aujourd’hui, cette dernière prend régulièrement la forme d’un hommage personnalisé appelé le bien cuit. Habituellement entendue par les ethnologues comme un rite de passage, la célébration d’un départ à la retraite est dans cet article examinée comme une performance rituelle qui influence et accompagne l’individu dans cette transition. L’auteure porte principalement son attention sur le dispositif rituel, le cadre, ainsi que sur le contexte des différentes fêtes de départ à la retraite. Elle examine aussi le rôle joué par l’humour dans l’efficacité significative de ce rituel contemporain.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.090
Threshold uncertainty score0.179

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0120.006
Scholarly communication0.0040.002
Open science0.0010.005
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0280.004

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 head0.086
GPT teacher head0.322
Teacher spread0.236 · 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 designQualitative
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
Published2009
Admission routes3
Has abstractyes

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