PROFESSIONAL PRACTICE AND ENGINEERING INTERNS: THREE CASES FOR DISCUSSION
Bibliographic record
Abstract
A key phrase in discipline findings of professional misconduct is "The engineer knew or ought to have known". By virtue of being members of the engineering profession, Engineers are expected to demonstrate both technical competence and professionalism. The three cases in this paper look at professionalism from the standpoint of trust from the perspective of the regulator, the client, and peers.When that trust is broken, complaints against the engineer can ensue and unless the member has worked with the investigation committee or been investigated before, it is unlikely that they would know the disciplinary process and the scope within which they operate.This paper is aimed at fostering classroom discussions about the ethical situations Engineering Interns could find themselves in and offers ideas on how the investigation/discipline process can be brought to the classroom.
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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 | 0.013 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.020 | 0.012 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.010 | 0.009 |
| Insufficient payload (model declined to judge) | 0.005 | 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".