Bibliographic record
Abstract
Canada’s polytechnics have long been at the forefront of innovations in sustainability and combatting climate change. These institutions have the capacity to play a critical role in driving the adoption of climate-conscious practices throughout industry and the wider community. As the need to move past sustainability and propel the adoption of regenerative practices is better understood, polytechnics are uniquely positioned to drive this shift. This paper explores the concept of regenerative design and how Canada’s polytechnics have employed on-campus initiatives and infrastructure projects in three broad categories: production of excess energy, recycling and reusing waste or runoff, and ecological (re)integration. Through these endeavours, the institutions are positioning themselves as role models and intermediaries able to introduce and help stakeholders adopt regenerative practices. Maximizing this capacity is an important way the Government of Canada can achieve its climate-related objectives as laid out in the 2022 Federal Sustainable Development Strategy. By harnessing polytechnic regenerative expertise and their deep ties to both industry and their surrounding communities, Canada will be better positioned to meet its ambitious climate targets.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".