Ain’t gonna study war no more: Teaching and learning cooperation in a graduate course in resource and environmental management
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract: Humans are the primary causes of increases in biosphere-scale toxicity, climatic variation, and risk. Despite several generations of intensive and scientifically astute environmental advocacy, research, and training it is unclear whether these trends will provoke self-perpetuating and out-spiraling conflicts or unprecedented levels of effective cooperation. For educators, a pivotal question is whether our schools, classrooms and curricula will produce the problem solvers required to meet escalating challenges in resource and environmental management. One of our responses to this question is a course that uses groupwork to simulate aspects of ‘real world’ complexity in resource management. The course, taught to over 300 graduate students in Simon Fraser University’s School of Resource and Environmental Management, effectively trains learners in the acquisition and application of conceptual and practical knowledge and skills centered on cooperation among individuals and groups with diverse values and interests.
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.
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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it