Bibliographic record
Abstract
Abstract The environmental and resource crises that confront human life on earth demand changes to the whole socio‐economic metabolic system. The changes will affect all aspects of life, including the practice of chemical engineering. The historical association of the profession with the fossil carbon economy means that the expertise that makes up chemical engineering must be re‐examined and repurposed urgently if the discipline is to play a full role in the socio‐economic transition. In this article, we review the historical development of chemical engineering to identify its unique features and find ways in which it can change to meet the challenge. A pattern of 30‐year cycles in the development of the discipline is revealed, showing the way it has built up by incorporating approaches from other disciplines and also developing a unique set of skills and knowledge. Chemical engineering as taught needs to prepare graduates to operate under the kind of social contract embodied in declarations by professional bodies. We propose ways in which the expertise comprising chemical engineering can be applied in the ‘just transition’ to a less unsustainable society, including new approaches to plant and process design and also applications ‘outside the pipe’ to environmental modelling and industrial ecology. The unsustainability crisis results from a history of poor public and private decisions, so examination of the different types of decisions is timely. Specific roles for chemical engineers in deliberative decision processes are identified, including enhanced emphasis on risk and precaution.
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.029 | 0.004 |
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".