Bibliographic record
Abstract
Despite the wealth of data that suggests climate change will disrupt our ecosystems, key political actors have declined to take action to mitigate the anticipated effects. Further, we have seen deeper investment into the fossil fuel industry, an industry that has been a substantial contributor to climate change. Community-led movements have proven more successful in engaging with these issues on the ground. Creative legal strategies could aid in this movement and allow for strengthened enforcement of rights that are closely dependent on the health of the environment.\nThe Salish Sea is a body of water that reaches from Western Canada down into the Northwestern United States. The ecosystem faces a number of threats, but one in particular is the Trans Mountain Pipeline expansion in Canada. This is just one of many recent projects that seeks to increase fossil fuel reliance in the midst of protests for climate change action. First Nations tribes have been resisting the expansion but given the potential impact to Native tribes in the United States, it seems that all of the Coast Salish tribes should be able to participate in this resistance. \nAlthough the pipeline expansion will infringe on treaty rights, it is unclear how they might be enforced against the Canadian government. U.S. Courts have held that the government has a responsibility to protect treaty rights, but this may not be recognized by Canadian courts\nRecent developments in the Rights of Nature movement have created private rights of action for individuals to act on behalf of bodies of water and other natural resources. By securing rights for the Salish Sea, Coast Salish tribes could enhance their treaty rights and protect this ecosystem in an international context. To succeed, this movement must utilize creative legal strategies while centering indigenous interests to achieve environmental justice.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.008 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.026 | 0.003 |
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".