Bibliographic record
Abstract
À partir de l’analyse de dizaines d’exemples d’engagement d’entreprises internationales ou canadiennes en matière de responsabilité sociale, nous avons fait les constats suivants : (1) les politiques de RSE ne sont trop souvent que l’expression de vœux pieux; (2) elles ne sont assujetties à aucune obligation d’applications concrètes ; (3) elles peuvent être démenties par des pratiques contraires à la politique ; (4) elles sont rentables car le public croit davantage l’expression de générosité que les mensonges qui les entourent. Dès lors, les entreprises ne se gênent aucunement pour projeter d’elles-mêmes une image d’entreprise responsable tout en ayant des pratiques condamnables, car en général la sanction de l’opinion publique n’est pas au rendez-vous. L’exemple des Prix Pinocchio en France en témoigne. Having analysed dozens of examples of the commitment of international and Canadian businesses in the area of social responsibility, we arrive at the following observations: (1) CSR policies are all too often merely a matter of lip service; (2) they do not involve any obligation to apply concrete measures; (3) they may be contradicted by practices that are contrary to the policy; (4) they are profitable because public belief is more strongly influenced by the expression of generosity than by the fact of the lies surrounding them. As a result, businesses do not hesitate to project the image of a responsible enterprise while engaging in reprehensible practices, because in general public opinion does not cast blame upon them for doing so. The example of the Pinocchio Awards in France is a reflection of this.
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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 | 0.021 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.010 |
| Science and technology studies | 0.009 | 0.015 |
| Scholarly communication | 0.016 | 0.022 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.026 | 0.005 |
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".