Bibliographic record
Abstract
Pilier du développement durable, le volet environnemental demeure la préoccupation majeure des PME françaises. Le manque de moyens, notamment financiers, est l’un des freins récurrents à un engagement plus volontariste des PME en la matière. Afin de neutraliser ce facteur, notre étude se focalise sur une population spécifique, à savoir des PME rentables. Cet article analyse les pratiques de management environnemental des PME françaises rentables afin d’en relever les particularités. Une étude quantitative par questionnaire a été menée auprès de 84 PME françaises issues d’un classement publié par un magazine économique en juillet 2006. Globalement, les pratiques de management environnemental des PME rentables se déclinent en forces (pratiques de reporting environnemental, forte réduction des impacts environnementaux) et faiblesses (déficit d’information et de communication en matière environnementale). Ces résultats ouvrent la voie à de futures recherches portant sur la communication environnementale des PME ou soulignent la nécessité de l’évaluation financière des pratiques environnementales. Des efforts de communication sont indispensables afin de convaincre les dirigeants de PME de la nature stratégique du management environnemental.
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 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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".