MétaCan
Menu
Back to cohort
Record W1973300850 · doi:10.3917/riges.341.0059

Positions des organisations face à la gestion et à la communication environnementales

2009· article· fr· W1973300850 on OpenAlexaffvenue
Marie‐Andrée Caron, Charles H. Cho

Bibliographic record

VenueGestion · 2009
Typearticle
Languagefr
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsConcordia UniversityUniversité du Québec à Montréal
Fundersnot available
KeywordsPolitical scienceHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Résumé La gestion et la communication environnementales ont fait l’objet de développements notables avec l’émergence de lignes directrices en matière de divulgation, de normes comptables, d’une réglementation dans certains cas plus sévère, d’attentes plus précises de la part des parties prenantes et de pressions médiatiques plus importantes. Or, malgré ces développements, beaucoup d’organisations ne communiquent pas d’information ou en communiquent très peu en matière de gestion environnementale. Les dirigeants sont concernés par cette carence informationnelle, mais aussi les experts, et parmi eux les experts-comptables, spécialistes de la divulgation de l’information sur la performance. À partir des outils proposés par ces experts, qui demeurent à ce jour largement sous-utilisés, l’organisation peut envisager trois positions à l’égard de la question environnementale, soit le respect des lois et des règlements, l’amélioration de sa compétitivité et la réduction des effets négatifs de ses activités sur l’environnement. Partant de là, nous précisons en terminant les difficultés et les limites de la communication environnementale.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.006
Scholarly communication0.0130.005
Open science0.0010.007
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.0260.004

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.

Opus teacher head0.026
GPT teacher head0.279
Teacher spread0.253 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations9
Published2009
Admission routes2
Has abstractyes

Explore more

Same venueGestionSame topicCorporate Social Responsibility ReportingFrench-language works237,207