5. Dealing with Wicked Global Problems: An Inter-Disciplinary Approach
Bibliographic record
Abstract
The world faces a number of complex challenges that are sometimes referred to as ‘wicked problems.’ Universities have been relatively poor at preparing graduates for such challenges, yet it will be the future professionals who need to tackle the problems. This essay looks at two related projects that have attempted to advance the skills training of graduates for a complex world, in the context of educating engineers and scientists in sustainable development.A Delphi study conducted in the UK suggested that systemic, student-centred approaches were vital to the appropriate development of undergraduates to become engineers with skills in sustainable development. A pilot project sponsored by the UK Royal Academy of Engineering developed an inter-disciplinary course unit, using student-centred principles, to embed the principles of sustainable development, in its broadest sense, in the curricula of engineers and scientists. The essay includes an evaluation of this approach.
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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 | 0.015 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.009 | 0.028 |
| Scholarly communication | 0.021 | 0.014 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".