Conclusion au dossier spécial — « Décarboner le management international » : entre transitions environnementales, sociales et digitales
Bibliographic record
Abstract
The 13th Atlas-AFMI Conference was held at the IAE in Bordeaux in July 2023. Its central theme was “the decarbonization of international management.” This choice of theme reflects a context marked by the growing visibility of the effects of climate change and collective recognition of the urgent need for systemic action. Global warming is mainly the result of the massive use of fossil fuels, on which the global economic model has been based for two centuries. At the same time, international trade, historically associated with economic growth, has intensified significantly since 1950, particularly through the fragmentation of value chains. Recent research shows that these global chains generate more CO₂ emissions than domestic production, making international trade a significant contributor to climate change. The conference discussions highlighted two major issues : the economic, environmental and social impacts of digitalization, and the responsibility of international companies in addressing climate challenges and inequalities.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.006 | 0.013 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".