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Record W3161991797 · doi:10.14428/rcompro.vi11.53343

Promouvoir la saine alimentation sur Facebook Live : vers de nouvelles compétences communicationnelles dans les organisations de santé publique ?

2021· article· fr· W3161991797 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueRevue Communication & professionnalisation · 2021
Typearticle
Languagefr
FieldSocial Sciences
TopicCommunication and COVID-19 Impact
Canadian institutionsUniversité Laval
FundersUniversidad Michoacana de San Nicolás de HidalgoUniversité Laval
KeywordsPolitical scienceHumanitiesArt

Abstract

fetched live from OpenAlex

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.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.569
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0040.001
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.065
GPT teacher head0.372
Teacher spread0.307 · 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