Understanding Engineers’ Ethical Environmental Responsibility
Bibliographic record
Abstract
Engineers Canada states that engineers must, “Hold paramount the safety, health and welfare of the public and the protection of the environment and promote health and safety within the workplace” [1]. This is frequently the only guideline directly related to the environment included in Canadian provincial and territorial Professional Engineering Codes of Ethics (PECoE) which are a primary resource for teaching engineering ethics [1]; notably, Ontario’s PECoE currently does not explicitly mention the environment [2]. Minimal formal ethical guidelines indicate interpretations of engineers’ professional responsibility with respect to the environment may vary in both industry and engineering education. With the growing focus on sustainable development alongside escalating environmental crises, a thorough investigation of engineers’ professional ethical responsibility to the environment is time-sensitive and necessary [3]. The purpose of this study is to improve understanding of how engineers and engineering students view and interpret their professional ethical responsibility to the environment and PECoE in a Canadian context. The ultimate goal of this research will be to aid the development of engineering ethics and sustainability curricula, as well as Professional Engineering Codes of Ethics. A key result from preliminary findings, is that participants feel there may be a need to explicitly include more guidelines on the environment in the Ontario PECoE.
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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 | 0.014 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.017 | 0.032 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".