Reducing Human Disturbance to Atlantic Flyway Shorebirds Using Social Science Methods
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
Human disturbance is a significant threat to shorebirds in North America. Disturbance can result in direct mortality or have long-term impacts on the survival of shorebirds. Land managers employ a variety of management techniques to minimize anthropogenic impacts on shorebirds, but because the Atlantic Flyway is ecologically and recreationally diverse, management can vary among sites. This thesis used social science methods to understand the extent to which human disturbance is managed and how human disturbance is managed. Specifically, we surveyed land managers and biologists in the U.S. and Canada portions of the Atlantic Flyway to examine potential disturbances, types of activities that are restricted, when restrictions occur, the perceived effectiveness of management techniques, public compliance with restrictions, and resource needs of managers. With the findings from this research, agencies and organizations that manage shorebirds can assess where to invest time, effort, and resources to reduce disturbance. We also used a survey of dog walkers to ascertain the benefits and constraints to leashing dogs near shorebirds because dog walking is one of the top-rated potential disturbances to shorebirds. Additionally, we sought to understand the personal and social norms related to dog walking and evaluated if a community-based social marketing (CBSM) approach would be enhanced by the addition of norms. Using a CBSM approach, we provided insights on strategies to promote voluntarily leashing of dogs near shorebirds. Through this thesis, we aimed to bridge the needs of people and the needs of shorebirds, in an effort to produce effective conservation outcomes.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| 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 it