Agencement et transformation numérique des pratiques d’engagement en situation de crise : le cas du Gouvernement ouvert du Canada
Bibliographic record
Abstract
Cet article s’intéresse à l’agencement des pratiques d’engagement au sein du Gouvernement ouvert du Canada dans la foulée des transformations numériques pendant la pandémie de Covid-19. Notre recherche, qui s’inscrit dans l’approche fondée sur les pratiques et la communication constitutive des organisations, suit les étapes de l’analyse thématique et se penche sur les discours de cinq gestionnaires recueillis lors de treize réunions tenues en ligne suite à la directive du télétravail. Nos analyses montrent que la transformation numérique des pratiques d’engagement est un processus d’agencement qui va au-delà de l’intégration d’outils et de technologies numériques. La transformation numérique, influencée par des processus communicationnels oscillant entre savoir et faire, est marquée par l’émergence et le développent de savoirs permettant la facilitation de la communication en contexte numérique.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.032 | 0.028 |
| Scholarly communication | 0.015 | 0.004 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 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".