Concern is in the Eye of the Stakeholder: Heterogeneous Assessments of the Threats to Oyster Survival and Restoration in North Carolina
Bibliographic record
Abstract
Coastal oceans and estuaries face unprecedented threats to sustainability and productivity. The vulnerability of these ecosystems persists in part due to how threats to them are perceived. Understanding the subjectivity in how stakeholders frame and assess threats to coastal ecosystems is critical to management and restoration. This study utilized a participatory risk mapping methodology to assess how stakeholders in oysters (Crassostrea virginica) in North Carolina perceive the threats to oyster survival and efforts to restore oyster populations. The resulting threat maps demonstrate that stakeholders perceived different threats and assessed the same threats with varying levels of concern. Stakeholder groups expressed contradictory views of the threats from harvest and natural disturbances, revealing differences in perceptions of nature and how stakeholders view themselves in relation to the environment—a relationship that reflects history, knowledge, expectations, culture, and economy. Unresolved, these differences can impede management processes and diminish the effectiveness of restoration activities.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".