Transformative Sea-level Rise Research and Planning: Establishing a University, Tribal, and Community Partnership for a Resilient California North Coast
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Sea-level rise (SLR) is and will continue to be a pressing issue in the rural, North Coast region of California, especially since nearby Wigi (or Humboldt Bay) is experiencing one of the fastest rates of relative SLR on the U.S. West Coast. In this paper, we argue that SLR presents a transformative opportunity to rekindle environmental relationships and reshape the future of the California North Coast and beyond. As the preeminent higher education institution of the region, Cal Poly Humboldt has the responsibility to be a leader in education, research, and planning for climate resilience. We describe efforts of the Cal Poly Humboldt Sea Level Rise Institute to establish a university-Tribal-community partnership that braids together different approaches and ways of knowing to develop research and planning that supports a resilient California North Coast. Since Wigi is projected to experience the effects of SLR sooner than the rest of the state, the North Coast region is poised to act as an incubator for new ideas and solutions, including Indigenous knowledge systems, and to play a role in influencing equitable, resilient, and transformative SLR adaptation processes in other parts of the state and the world. This will require developing programming and expertise in specific disciplinary areas, but, more importantly, will require the development of opportunities and spaces for various disciplines, ways of knowing, and sectors (e.g. Tribal nations, academia, government, NGOs, private companies, and community groups) to converge and bring the best of what they have to address climate-induced challenges and opportunities.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it