Towards community‐based monitoring in Manitoba's hog industry
Bibliographic record
Abstract
Abstract: Rapid changes in the hog industry in Manitoba have resulted in a gap in the province's resource and environmental policy regime. Concerns about potential, uncertain environmental impacts and an outdated regulatory framework led to a moratorium on new hog industry operations and a provincial hearing. Based on extensive literature, documentary and legislative reviews, this article explores the role of monitoring, and the potential for community‐based monitoring specifically, to address these policy issues. Given the non‐point nature of the pollution in question, the social and economic conditions in southern Manitoba and the strengths of community‐based monitoring initiatives, this approach is a promising solution. Furthermore, the existing legal framework provides an existing grounding through which the program could be vested with authority. Sommaire: Des changements rapides dans l'industrie porcine au Manitoba ont entraîné un fossé entre la politique des ressources et celle de l'environnement de la province. Les inquiétudes au sujet d'éventuelles conséquences environnementales et d'un cadre de réglementation dépassé ont conduit à un moratoire sur les nouvelles opérations dans l'industrie porcine et à une audience provinciale. En s'appuyant sur une importante documentation et sur des études documentaires et législatives, cet article approfondit le rôle de la surveillance, et plus particulièrement le rôle possible de la surveillance communautaire, pour s'attaquer à ces questions de politiques. Étant donné la nature non ponctuelle de la pollution en question, les conditions sociales et économiques dans le sud du Manitoba et la force des initiatives communautaires, cette approche est une solution prometteuse. En outre, le cadre juridique actuel fournit une base existante qui permettrait au programme d'être investi d'une certaine autorité.
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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 | 0.013 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".