Management stratégique BoP : une modélisation à l’épreuve d’une recherche-intervention chez Nestlé Cameroun
Bibliographic record
Abstract
Cet article a pour objectif de tester sur le terrain la pertinence et la validité d’un framework intégré et systémique de management des stratégies BoP proposé dans des articles antérieurs. La recherche-intervention est la méthode la plus appropriée pour valider de tels frameworks . Une recherche-intervention de deux mois a ainsi été conduite chez Nestlé-Cameroun. Après avoir explicité la définition des stratégies BoP, et synthétisé la modélisation de type dialogique (stratégie/anthropologie), l’article présente l’étude de cas via les deux usages (compréhensif et heuristique) attendus du framework , et enfin discute des apprentissages croisés obtenus: l’apport de la recherche-intervention pour Nestlé-Cameroun, l’apport de la recherche-intervention pour la modélisation.
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.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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; both teacher heads agree on what is shown here.
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".