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Record W2894240210 · doi:10.14428/emulations.011.007

Une histoire de vocation ? Comment les aides-soignantes occultent le processus de transmission de leurs compétences professionnelles.

2012· article· fr· W2894240210 on OpenAlexaffabout
François Aubry

Bibliographic record

VenueEmulations - Revue de sciences sociales · 2012
Typearticle
Languagefr
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsHumanitiesPolitical scienceSociologyArt

Abstract

fetched live from OpenAlex

Cet article a pour but de montrer comment les aides-soignantes travaillant dans les organisations gériatriques en France et au Québec se représentent le processus par lequel leurs compétences professionnelles leur ont été transmises. Nous avons réalisé vingt-quatre entretiens semi-directifs en France et vingt-trois au Québec (Canada). Nos résultats prouvent que les aides-soignantes utilisent une rhétorique spécifique, celle de la vocation, pour expliquer le sens de leur trajectoire professionnelle. Cet usage rhétorique leur permet de se représenter leur trajectoire dans l’ordre de la continuité. Afin de structurer cette croyance, les aides-soignantes se créent une identité d’endettées, en s’identifiant comme les récipiendaires d’une aide transmise par leurs proches parents, notamment féminins. Elles se disent dans l’obligation morale de rendre ce don aux aînés vivant dans les organisations gériatriques. Ainsi, en utilisant la rhétorique de la vocation, les aides-soignantes françaises tout autant que québécoises occultent le processus de transmission de leurs compétences professionnelles. Ce découpage mémoriel leur permet d’accepter plus facilement les difficultés du métier et de « tenir » face à des situations professionnelles difficiles.

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)0.005
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.464
Threshold uncertainty score0.922

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0190.039
Scholarly communication0.0090.006
Open science0.0010.004
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0070.001

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 head0.160
GPT teacher head0.369
Teacher spread0.209 · 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

Citations3
Published2012
Admission routes2
Has abstractyes

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