Paper submitted to the Manitoba Clean Environment Commission with respect to its Investigation into Hog Production in Manitoba.
Bibliographic record
Abstract
with respect to its investigation into hog production in Manitoba. My thesis, based on more than five years of research into the growth of Manitoba’s intensive livestock industry, is that it is no longer sustainable. Manitoba’s emergence as a pork powerhouse has polarized many of our rural communities around social and environmental issues, with no obvious solutions in sight. I am concerned that this investigation of the hog industry, similar to previous investigations of the same industry, will stress harm reduction and mitigation of negative effects, rather than question the benefits of tolerating intensive hog production on such an enormous scale. It is the latter question that this Commission, and Manitoba’s citizens, should address. There is a history of public inquiries examining the environmental impact of Manitoba’s hog industry. As early as 1979, the Manitoba Clean Environment Commission, after conducting hearings at a number of sites in the province, issued a report on intensive livestock operations (ILO’s).i At that time, odour problems were the main driver of public debate. In 1994, the Manitoba Pork Study Committee investigated the industry, but the report largely subordinated environmental problems to economic development priorities.ii By the twenty-first century, however, a tectonic shift had occurred in public perceptions of the ecological effects of ILO’s. The Walkerton tragedy had made us forcefully aware that water contamination, and human health concerns generally, trumped odour as an overriding issue. There was a growing focus on the fact that livestock production contributes heavily to land and water degradation, greenhouse gas emissions, and, ultimately, global warming.iii Words like “sustainability ” and “sustainable development ” had become established in the official lexicon, and were liberally sprinkled in
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.
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.007 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.010 | 0.006 |
| Insufficient payload (model declined to judge) | 0.035 | 0.008 |
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".