The unique contribution of a local response group in the field investigation and management of a trichinellosis outbreak in Nunavik (Québec, Canada)
Bibliographic record
Abstract
Setting : Consumption of raw game meats is important for Inuit health and well-being but may sometimes increase risk of exposure to parasites. In Nunavik, following trichinellosis outbreaks in the 1980s caused by raw walrus consumption, a diagnostic test was developed for the region and offered to all Inuit communities by 1997. Despite this prevention program, an important trichinellosis outbreak occurred in 2013, affecting 18 inhabitants of Inukjuak. \n \nIntervention : Because the classical outbreak investigation did not rapidly converge toward a common food source or specific event, a local response group, composed of four community members appointed by the Municipal Council as well as the regional public health physician, nurse and wildlife parasitologist, was created. Their objective was to investigate potential sources of infection related to the outbreak, hence the investigation of the types of meats consumed, the movement of meats between and within the community, and the local practices of processing game meat. \n \nOutcomes : Though the source of infection was not fully confirmed, this local investigation identified the distribution of transformed polar bear meat as the most probable source of infection. The creation of this unique, intersectoral and intercultural local response group fostered the use of local knowledge to better understand aspects of the modern food system, and is one of the most innovative outcomes of this investigation. \n \nImplications : Integrating multiple ways of knowing was critical for the management of this important public health issue and contributed to community members’ mobilization and empowerment with respect to local food safety issues.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".