Municipal urban rat management policies and programming in seven cities in the United States of America
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
While literature indicates that municipal rat management approaches are often unsuccessful, a lack of research comparing strategies makes the breadth of opportunities and challenges associated with different approaches uncertain. Here, we explored the municipal rat management policies and programs in seven cities in the United States of America. Rat policies were attained by collecting rat management-related municipal codes in each city. Information on rat programs was obtained through interviewing program stakeholders. Analysis followed a qualitative framework method to identify and describe themes associated with the structure and function of management approaches. Municipal codes served as a foundation for municipalities by outlining when, where, how, and by whom rat problems should be addressed. Programs employed the primary people responsible for performing on-the-ground management and they acted as a municipal “brain,” organizing the city’s strategy. We identify opportunities and barriers for other municipalities to consider in the design of their own rat management strategies.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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