Bibliographic record
Abstract
[Extract] There are several aboriginal-owned whale-watching ventures in Canada, Australia and New Zealand. These include viewing orca (killer whale) with Village Island Tours (Telegraph Cove, BC), operated since 1989 by Tom Sewid, a Kwakwak'awakw First Nations man. His boat, painted with a First Nations Orca design, is named Gla-Lis (finning whale). The Kwakwak'awakw people believe that chiefs are reborn as killer whales. On the west coast of Vancouver Island, other First Nation groups operate boat tours viewing orca and grey whales. In Quebec, eastern Canada, the Essipit-Montagnais First Nation have run whale-watching boat tours on the St Lawrence River estuary since 1994; they use zodiac boats to view common and blue finback whales. The company employs six full-time staff and purchased a new whale watch vessel in 1999 with funds from Aboriginal Business Canada. Whale watching provides 60% of their income. In Nunavut, an Inuit territory in Arctic Canada, some Inuit people run kayak trips at Kugaarak (Pelly Bay) and Pond Inlet to watch narwhals, beluga whales and bowhead whales (all still hunted by the Inuit).
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.084 | 0.016 |
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".