How an entry-level, interdisciplinary sustainability course revealed the benefits and challenges of a university-wide initiative for sustainability education
Bibliographic record
Abstract
Purpose – Delivery of sustainability-related curriculum to undergraduate students can be problematic due to the traditional “siloing” of curriculum by faculties along disciplinary lines. In addition, while there is often a ready availability of courses focused on sustainability issues in the later years of students’ programs, few early entry-level courses focused on sustainability, broad enough to apply to all disciplines, are available to students in the first year of their program. Design/methodology/approach – In this paper, we describe the development, and preliminary implementation, of an entry-level, interdisciplinary sustainability course. To do so, the authors describe the development of a university-wide initiative designed to bridge units on campus working and teaching in sustainability areas, and to promote and support sustainability curriculum development. Findings – The authors describe the conceptual framework for organising course content and delivery. The authors conclude with an informal assessment of the successes and challenges, and offer learning activities, student assessments and course administration recommendations for consideration when developing courses with similar learning goals. Originality/value – The positive and negative experiences gained through developing and offering a course of this nature, in a large research-focused university, offers knew insights into potential barriers for implementing first-year cross-cutting sustainability curriculum.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".