Sustainable Development Goals within Canadian Universities
Bibliographic record
Abstract
The 17 Sustainable Development Goals (SDGs) were created for all countries by the United Nations in 2015 with the aim of transforming the world for the better. Each country is responsible for working towards achieving these SDGs. Within Canada, fifteen research universities known as the U-15 make up the majority of private-sector research and innovation. About 65% of these U-15 institutions have developed their own SDG report/plan, illustrating a high level of initiative and involvement when it comes to the SDGs. Research indicates that as countries continue to improve their efforts towards the SDGs, there will be a need for a deeper understanding on how these efforts are being implemented. Therefore, understanding how these U-15 institutions are working towards the SDGs is valuable because they are teaching the coming generations of researchers and innovators. The findings from this research indicate that efforts towards the SDGs is not the same for each U-15 institution and that some of the top universities in Canada should put more energy into achieving the SDGs. Overall this research could be utilized to provide future best-practice recommendations for universities wanting to implement the SDGs in their strategic plans.
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 | 0.002 | 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 | 0.005 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".