Escaping the disciplinary straitjacket
Bibliographic record
Abstract
Purpose Curriculum design is often a challenge. It is particularly so when the subject is sustainability, which is an aspirational but contested concept, draws on a range of disciplinary insights and is relatively new to university curricula. There is no single “right way”, or even agreement across the disciplines that inform the collective enterprise about general approaches to sustainability curricula. The likely content is ill‐defined and spans departmental units and budget areas in most traditional universities. Like other societal and institutional attempts at realising sustainability, curriculum design for sustainability is beset by difficulty, yet an essential intellectual activity. This paper aims to focus on these issues. Design/methodology/approach The paper compares actual curriculum development processes for “sustainability” in two very different Australian universities, as studied using participant observation and qualitative interviews. Findings The paper draws out some of the common challenges of interdisciplinary curriculum design for sustainability, and identifies four principles transferrable to other institutional adaptation settings. It argues that curriculum design is an opportunity to develop collegiality, and further advance the problem area under discussion. Originality/value Case study research is often difficult to generalise to other settings. The opportunity to observe two sustainability curriculum design processes, operating in parallel, provides transferrable insights.
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 | 0.104 | 0.115 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.015 | 0.037 |
| Scholarly communication | 0.019 | 0.012 |
| Open science | 0.005 | 0.022 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".