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Record W7116199636 · doi:10.59876/a-25pq-ynb7

Conclusion au dossier spécial — « Décarboner le management international » : entre transitions environnementales, sociales et digitales

2025· article· fr· W7116199636 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueManagement international · 2025
Typearticle
Languagefr
FieldSocial Sciences
TopicInnovation, Sustainability, Human-Machine Systems
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Climate changeTheme (computing)Global warmingVisibilityGlobal temperature

Abstract

fetched live from OpenAlex

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.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.832
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.020
GPT teacher head0.323
Teacher spread0.303 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it