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Record W4414153945 · doi:10.14428/rcompro.vi15.77643

Agencement et transformation numérique des pratiques d’engagement en situation de crise : le cas du Gouvernement ouvert du Canada

2025· article· fr· W4414153945 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueRevue Communication & professionnalisation · 2025
Typearticle
Languagefr
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsUniversité du Québec à MontréalUniversité de MontréalUniversity of Ottawa
Fundersnot available
KeywordsContext (archaeology)EthnographyLegislationDiversity (politics)

Abstract

fetched live from OpenAlex

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.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.527
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.040
GPT teacher head0.348
Teacher spread0.308 · 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