Identifying the foundation: Connecting codes of ethics, accreditation, values, and social justice to the engineering curriculum
Bibliographic record
Abstract
Canadian Engineering Accreditation Board (CEAB) graduate attributes are at the foundation of engineering curricular change in Canada. While CEAB graduate attributes require an understanding of ethics, professionalism, and impact, outcomes explicitly associated with equity, diversity, inclusion, indigeneity (EDI-I) and social justice broadly construed are absent. At present, the CEAB ethics criteria imply that understanding and valuing the code of ethics adequately addresses the issue, which leaves a gap in guidance for educators and curriculum designers. This paper reports on a thematic analysis of the 12 Canadian engineering codes of ethics and associated guidelines to discover the values overtly addressed or implied in the documents. We then map these findings onto the values of EDI-I and social justice as outlined by engineering scholars, and we offer recommendations for using the results to guide engineering instructors who want to make appropriate curriculum modifications that will support the CEAB efforts to address these movements.
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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 | 0.027 | 0.081 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.020 | 0.041 |
| Scholarly communication | 0.019 | 0.008 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.005 |
| 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".