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Record W4402418806 · doi:10.53379/cjcd.2024.390

Quand la transformation numérique croise la pandémie : quelles expériences pour les cadres?

2024· article· fr· W4402418806 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueCanadian Journal of Career Development · 2024
Typearticle
Languagefr
FieldAgricultural and Biological Sciences
TopicAgriculture and Rural Development Research
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsMedicine

Abstract

fetched live from OpenAlex

Le chamboulement qu’a connu le monde du travail avec l’avènement de la crise sanitaire a eu des répercussions substantielles notamment sur les entreprises et par ricochet sur les travailleurs, dont les cadres. Cet article vise à rendre compte des expériences de travail des cadres en contexte de pandémie de Covid-19. Il s’appuie sur la théorie du « travail vivant » (Dejours, 2013) afin d’appréhender les enjeux des mutations du monde du travail et leurs répercussions sur les expériences de travail. La recherche repose sur une méthode qualitative menée à l’aide de groupes de discussion auprès de 20 cadres. Les résultats révèlent entre autres les dimensions économique, instrumentale, humaine et sociale soutenant leur travail afin de faire face à la transformation numérique. Les analyses ouvrent sur des réflexions sur les modes d’organisation du travail à construire afin de favoriser le maintien durable en emploi et la conciliation des projets de vie.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.746
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.035
GPT teacher head0.240
Teacher spread0.205 · 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