Promouvoir la saine alimentation sur Facebook Live : vers de nouvelles compétences communicationnelles dans les organisations de santé publique ?
Bibliographic record
Abstract
Cet article analyse la gestion des commentaires numériques faite par le ministère de la Santé du Brésil (Ministério da Saúde) lors de la diffusion d’une vidéo en direct sur Facebook Live dans le cadre de la Journée mondiale de l’alimentation 2018. Notre étude a examiné les interventions communicationnelles des travailleurs de la santé qui participent à la vidéo, à travers une analyse qualitative du contenu. Les résultats révèlent qu’il est possible de trouver des traces indiquant que cette organisation a engagé un processus continu de professionnalisation dans le volet de communication numérique qui se traduit par la reconnaissance de l’existence des profils de travail et l’intention de réglementer leurs pratiques professionnelles au sein de l’organisation. En outre, ces actions communicationnelles s’appuient tacitement sur des techniques de changement de comportement (TCC) pour gérer les retours d’informations numériques générés par les textes primaires utilisés pour promouvoir une alimentation saine.
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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 | 0.009 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".