What can engineers learn from the past? A potential role for history in engineering education.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
At present, in many societies, engineers play a significant role in solving problems of energy, transport, accommodation and production; but similar problems have been solved through technical and non-technical means for thousands of years. Numerous historical examples therefore exist, in which the ends of different approaches to problem-solving are apparent: some tending to produce socially and/or ecologically sustainable outcomes, and some less positive. Historians do not simply narrate the past, they explain and interpret changes and continuities by paying attention to larger issues of, for example, class, gender, polity and economy. Such historical narratives, we argue, may have a useful role to play in efforts to shift the perspective of engineering students away from a narrow focus on complex technical solutions, towards the broader context in which their problem-solving will take place. This ability to assess the relationships between engineering problem-solving and the broader social and environmental context is critical to the development of a more sustainable and socially-just engineering practice.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it