Engineering Ethics from a Justice Perspective: A Critical Repositioning of What It Means To Be an Engineer
Bibliographic record
Abstract
We expect engineers, much as we expect doctors, teachers, plumbers, bankers and even our politicians to be honest. Minimally this means that they should not cheat, falsify documents or reports, keep promises and adhere to contractual obligations. But more can be said about the relation between engineering and ethics. Enlarging what it means to be an engineer is to understand the responsibility of a professional to see beyond what ethics means within the boundaries of contemporary pressures and measures of success, and to know what the available choices are before deciding on any new direction. Some ethical problems are internal to engineering itself. In this paper we use a social justice perspective to critique current ideas about engineering ethics and consider the enlarging which needs to occur to break through the dominant paradigms of the profession.
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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 | 0.045 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.018 | 0.139 |
| Scholarly communication | 0.021 | 0.024 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.017 | 0.030 |
| 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".