Using corporate compliance principles to centralize compliance processes in an ISO 14001 environmental management system: case study of the Manitoba Hydro environmental management system
Bibliographic record
Abstract
There is an increasing expectation for organizations to operate in compliance, i.e. in adherence with applicable laws, regulations and other commitments. To meet these requirements and to manage their environmental activities, Manitoba Hydro uses an environmental management system (EMS) registered to the ISO 14001 Standard. The history of the EMS being amalgamated from three separate systems, coupled with the culture of Business Unit independence, has resulted in inconsistencies in compliance processes. The purpose of this research is to explore how the application of corporate compliance principles can centralize compliance processes in an ISO 14001 EMS. 15 principles were selected with a consideration(s) provided for how the principle could centralize a process. The considerations were organized into three centralization approaches, which can promote centralization by 1) strengthening CEM’s corporate compliance function; 2) developing a new corporate EMS process or modifying an existing corporate EMS process; and 3) creating conditions that promote centralization.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".