La fabrique de repères dans l'alimentation : entre objectivation stratégique de l’organisation de la valeur et euphémisation marchande. Le cas du Franco-Score d’Intermarché
Bibliographic record
Abstract
Peu après la mise en place en France du Nutri-Score évaluant la qualité nutritionnelle des produits alimentaires, le distributeur Intermarché (groupe agroindustriel Les Mousquetaires) lance le « Franco-Score » afin de permettre aux consommateurs et consommatrices d’accéder à la proportion d’ingrédients français contenus dans les produits par un affichage sur l’emballage. L’enjeu de cet article est d’interroger cette forme particulière qu’est le score au prisme des médiations marchandes qui le traversent. À l’aide d’une méthodologie croisée alliant les dimensions discursive et sémiologique, il s’agit de comprendre en quoi la mise en place de ce dispositif procède d’une objectivation stratégique de l’organisation de la valeur et d’une euphémisation marchande qui nous renseignent sur la relation didactique instituée entre la marque et le consommateur ou la consommatrice.
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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 | 0.010 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
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".