Plateformisation des métiers de la communication: Formation, collaboration, organisation, résistances
Bibliographic record
Abstract
La revue Communication & Professionnalisation souhaite présenter des travaux relatifs aux mutations des métiers de la communication dans un contexte de recours généralisé aux plateformes numériques dans les pratiques professionnelles et les transitions organisationnelles. Ce phénomène, appelé « plateformisation » (Acar et al., 2021.), peut être défini comme un processus technique (Helmond, 2015) et organisationnel majeur au sein de l’économie numérique visant à prescrire des appariements entre une offre – relevant de la multitude – et une demande – relevant de l’individualisation des pratiques (Benghozi & Paris, 2014). L’un des effets de bord de cette plateformisation est également de permettre, voire enjoindre à, de nouvelles formes de travail collaboratif (Mabi & Zacklad, 2021). Les GAFAM, grandes plateformes-entreprises à l’origine de cette économie d’intermédiation numérique, regroupent plusieurs industries (divertissement, connaissance, publicité, crowdworking, matériels informatiques, etc.) et proposent des services informationnels et communicationnels (stockage, synchronisation, externalisation, web 2.0, web 3.0, intelligence artificielle, métavers, etc.) incontournables aujourd’hui pour le fonctionnement des organisations.
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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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.006 | 0.022 |
| Scholarly communication | 0.016 | 0.016 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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".