Comment améliorer le télétravail dans le secteur public : leçons de la littérature en administration publique
Bibliographic record
Abstract
Sommaire Le télétravail est une réalité omniprésente dans les organisations publiques, surtout depuis la COVID‐19. Toutefois, comme il s’agit d’une réalité complexe qui affecte à la fois l’employé, le gestionnaire, l’organisation et la société, il est intéressant de s’interroger sur la façon dont on peut améliorer sa mise en œuvre. Cet article poursuit cet objectif en analysant les recommandations pratiques issues d’une revue systématique de la littérature sur le sujet à partir de la revue notoire et détaillée d'Allen et coll. (2015). Le second objectif abordé par cette revue est celui de savoir comment le télétravail est étudié et par conséquent, quel design devrait guider les prochaines recherches et serait utile aux praticiens.
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 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 | 0.012 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.012 | 0.012 |
| Scholarly communication | 0.014 | 0.010 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.018 | 0.002 |
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".