Zoonoses and social determinants of health: A consultation of Canadian experts
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
This study aimed to identify priorities for transdisciplinary research on zoonotic diseases (ZDs) using a One Health perspective. In 2017, 69 Canadian experts from various disciplines participated in a three-round Delphi prioritization exercise. Round 1 started with three ZD-related research axes: the convergence between zoonoses and chronic diseases, social determinants of zoonoses, and health system effectiveness in zoonosis prevention and control. Each included a list of potential research questions, and respondents were invited to propose additional topics for each axis. The next two rounds reduced the number of topics. Three priority research questions were ultimately selected: 1) What is the evidence that zoonoses contribute to the burden of chronic disease? 2) What do we know about the populations most vulnerable to zoonoses? 3) What do we know about the effectiveness of zoonosis prevention and control strategies? The results provide a unique view of important research needs in three ZD-related areas.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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