Bibliographic record
Abstract
In developing an understanding of the Salish Sea as a shared ecosystem and waterway it is essential to remember that the Salish Sea has been shared by Indigenous peoples since time immemorial. Losing sight of such long-established relationships in the development of scientific and public policies risks an erasure of Indigenous presence and sovereignty. My paper argues for a rethinking of the ways in which we discuss the Salish Sea's history and ecology with the general public. Public interpretation at parks and recreation sites is a front-line tool that policy makers can use to educate the public about the Salish Sea. While public interpretation may convey a message of ecological diversity, historic significance, or Indigenous presence, I argue that these public educational opportunities must be developed in relationship with Indigenous peoples in order to convey a message of Indigenous relationships and jurisdiction over the territories surrounding and within the Salish Sea. My approach is de-colonial and seeks to remind policy makers and the general public that the history of non-Indigenous presence within the Salish Sea ecosystem is one of colonization. Through an exploration of public interpretation at sites located in communities on Vancouver Island I provide tangible examples of how inattentive public interpretation can re-colonize and dismiss the Indigenous presence. I will also provide examples of what de-colonial public interpretation can look like with the hope that decision makers will be able to rethink public education about local sites located on and within the Salish Sea.
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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 | 0.020 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.036 | 0.088 |
| Scholarly communication | 0.021 | 0.016 |
| Open science | 0.002 | 0.019 |
| Research integrity | 0.009 | 0.019 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".