Rabies management in the North, a one health problem in a systems theory framework
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
Rabies is a significant public health concern and is often described as the quintessential One Health problem, linking especially animal health to human health.I examine how rabies is managed in the circumpolar North with three cases: Alaska, Northwest Territories, and Svalbard.In this thesis, I describe rabies management in the North using a systems theory framework and explore challenges in this limited application of the One Health paradigm, focusing on animal and human health agencies and their interaction in rabies management in a northern environment.I conducted semi-structured interviews with fifteen key informants.My results indicate that most respondents characterize the working relationships between agencies as positive and that the approach to rabies management is highly collaborative.While rabies is managed at the territorial or state level in the Northwest Territories and Alaska, respectively, the perception of where authority lies in rabies management is less evident in Norway concerning Svalbard, owing to the unusual administrative structure of the archipelago.Some uncertainty also existed among Canadian rabies managers.Respondents generally describe working relationships between agencies as positive; however, coordination remains one of the main challenges to rabies management, along with harsh environmental conditions and the remoteness of the small communities.Rabies managers in Svalbard also face risks associated with hunting, whereas dogs present challenges to rabies management in Alaska and the Northwest Territories, owing to limited veterinary services in dispersed small and remote communities in these two regions.My research shows that poor collaboration between agencies can hinder effective disease management, even for a disease such as rabies, with a long history of control measures in animals (vaccination) to reduce human exposure to this zoonotic virus.These findings could guide the implementation of the full One Health paradigm by highlighting the need for collaborative interagency relationships and consideration of local conditions when developing One Health based approaches.scientist as a graduate student in a social science program.Especially Mary Ehrlander, who stuck with me even into her retirement, has guided me to better understand the intellectual power of social sciences and the importance of telling a story.I appreciate the insight Mary, Elaine Drew, and Brandon Boylan have provided insights and support throughout the last six years of my journey into qualitative research and the social sciences.I have a much better understanding of this branch of science because of their guidance.My colleagues in rabies management and research who participated in the interviews provided the basis for my M.A. thesis; I appreciate their collaborative spirit in indulging me in my pursuit of their insight and in sharing their experiences.My wife Laurie has
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it