An analysis of ISO 14001 and suggested improvements
Bibliographic record
Abstract
Purpose The purpose of this paper is to present concrete recommendations on how the ISO 14001 standard for environmental management systems can be improved. Design/methodology/approach The paper presents the key results of a Canadian colloquium on ISO 14001. The theme of the colloquium was “How can ISO 14001 be improved in its next incarnation?” In total, 22 people from a wide variety of sectors participated in the colloquium. The discussions included a combination of plenary and small group discussions and were led by two professional facilitators. The colloquium was a part of a series of four events that have occurred since 2002. The next colloquium will be held in approximately two years. Findings The improvements suggested by the participants were organized around seven key areas: definitions; purpose; environmental policy; public reporting; monitoring and measurement; management review; and other changes. The changes are presented in detail in the paper. Originality/value The participants in the colloquium believed that the suggested changes will make significant improvements to ISO 14001. The suggestions are timely, given that the standard is up for review in the near future.
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 | 0.034 | 0.088 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.018 | 0.031 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".