Indigenous Knowledge and Salmon-Safe Certification at Vancouver International Airport
Bibliographic record
Abstract
Located on more than 3,300 acres on Sea Island in BC, the ancestral and unceded territory of the Musqueam people, and servicing more than 26.4 million passengers in 2019, YVR is one of Canada’s largest and busiest airports. In 2016, YVR was certified for a 5-year period as Salmon-Safe, a designation that serves to weave together the environmental stewardship of Sea Island to ensure the protection of the Fraser River, one of the most important salmon-bearing rivers in the world. In 2017, YVR and the Musqueam Indian Band signed a Sustainability & Friendship Agreement a 30-year agreement based on friendship and respect to achieve a sustainable and mutually beneficial future. With the Salmon-Safe certification up for reassessment, YVR, the Fraser Basin Council and the Musqueam community sought to enhance the recertification process by including indigenous knowledge. In this session, learn more about how the three parties worked to bring together western science and indigenous knowledge to better understand the our relationships with the land and the water and explore what is possible in the next 5-year certification period.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".