Le métissage à l’œuvre dans la communication des multinationales
Bibliographic record
Abstract
La transformation de la notion de métissage en concept, voire en paradigme, permet de déplacer les questionnements des recommandations marketing adressées aux entreprises, à l’analyse plus en profondeur du nouement des cultures dans leurs communications. Les auteurs focalisent leur analyse sur McDonald’s. La recherche se déploie sur deux terrains nationaux retenus pour leurs tensions culturelles plus susceptibles de mettre en évidence le métissage de la communication : la France et le Liban. L’analyse se fonde sur un corpus produit par McDonald’s entre le début des années 2000 et le milieu des années 2010. Ce premier point d’analyse sera doublé du recueil du discours de responsables nationaux de l’enseigne et de plusieurs entretiens semi-directifs conduits au Liban.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.008 | 0.019 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".