Including Organizational Ethics in the Risk Management Process: Towards Improved Practices and Analysis
Bibliographic record
Abstract
Risk management has played an important role in Quebec’s health and social services organizations for several years. This process is based on two guiding principles: the just culture and the no-blame concept and is an integral part of the Act respecting healthcare and social services. However, for all its usefulness, the current risk management process has certain limitations and criticisms. To overcome these weaknesses, the association of organizational ethics with the risk management process represents an interesting option. The use of organizational ethics concepts and tools overcomes the limitations of risk management and even optimizes it. Both are organizational processes with many common objectives and links, and both provide tools for decision-making. The combination of organizational ethics and risk management broadens the scope of risk management. To enable the best possible optimization, an analysis grid is proposed, and recommendations are made for the inclusion of ethics in risk management.
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 | 0.218 | 0.193 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.016 | 0.014 |
| Science and technology studies | 0.013 | 0.032 |
| Scholarly communication | 0.043 | 0.036 |
| Open science | 0.007 | 0.016 |
| Research integrity | 0.007 | 0.012 |
| Insufficient payload (model declined to judge) | 0.002 | 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".