S&T Revitalization: A New Look
Bibliographic record
Abstract
Labs.These recommendations were revisited in a subsequent edition, Postscript 2010.The fact remains that the total number of students graduating with a bachelor's degree in engineering in the United States continues to drop as a percentage of the total number of bachelor's degrees awarded.With this in mind, we propose to re-examine the issue of workforce revitalization and to focus, explicitly, on the supply of engineers as it is affected by culture, immigration, demographics, and globalization.Our primary purpose in writing this book is to generate a discussion at the national level regarding how best the U.S. can ensure the vitality of the engineering workforce in the coming century.We feel strongly that our engineers need to be well prepared technically, be connected in a meaningful way to the global science and engineering world, and be gender and ethnically diverse and bilingual in order to enhance connectivity with the global S&E community both technically and culturally.The authors wish to acknowledge input from Jim Short on export controls, copy editing done by Eric Hazell, illustrations by Kunal Sakpal, production work by Ania Picard and
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.
How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".