Quand la transformation numérique croise la pandémie : quelles expériences pour les cadres?
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.017 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".