Environmental and Economic Impact Assessments of Environmental Regulations for the Agriculture Sector: A Case Study of Hog Farming
Bibliographic record
Abstract
A multi-year research study was established under the environmental pillar of the Agriculture Policy Framework (APF) to evaluate the role and impact of existing farm level environmental regulations administered by local, provincial, federal governments. The Phase 1 study entitled "Inventory and Methodology for Assessing the Impacts of Environmental Regulations in the Agricultural Sector" was released in March 2006 on AAFC online. There is a growing concern about the impact and effectiveness of environmental regulations, specifically impact on the competitiveness of primary agriculture. Empirical analysis is required to better understand the exact role that agri-environmental regulations play in determining a farm's cost structure and to compare difference between provinces within Canada. With this purpose in mind, in Phase 2, Agriculture and Agri-Food Canada (AAFC), has commissioned hog case study to increase the policy makers' and industry's understanding of the impact and role of environmental regulations in the farming sector. The study estimated the compliance costs of existing agri-environmental regulations for a newly established -600 sow farrow to finish-hog facility in 2006. It was also assumed that the facility would follow good farming practices (i.e. sufficient land available to absorb the manure from the operation). The results show that environmental regulation compliance costs were generally less than 1% of total annual production cost.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".