Salish Sea Survey: Geographic Literacy Enhancing Natural Resource Management
Bibliographic record
Abstract
The Salish Sea is a biodiverse, transboundary inland sea and marine ecosystem stretching from British Columbia, Canada into Washington State, United States. Home to nearly eight million people and charismatic and keystone species, including three populations of orca, the ecosystem crosses multiple jurisdictions, communities, and watersheds, complicating conservation efforts. Geographic literacy, especially place names, is important for managing Salish Sea recovery and further challenged by the newness of the Salish Sea as an officially recognized place name. We conducted a geographic literacy survey showing that residents are largely unfamiliar with the name Salish Sea. Such low geographic literacy has numerous negative implications for communications, advocacy, outreach and the ability to address natural resource management and recovery of the Salish Sea at the level of the ecosystem. We offer potential implications for geographic literacy and other complementary geographic constructs within the wider field of natural resource management.
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How this classification was reachedexpand
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".