Agriculture's Likely Role in Meeting Canada's Kyoto Commitments*
Bibliographic record
Abstract
Voluntary adoption of beneficial management practices will be the primary means by which farmers cut net greenhouse gas (GHG) emissions. The offset system will not be a major driver due to (a) the relatively low prices likely to be offered by large final emitters facing an emission cap, (b) discounts applied to those prices for temporary sequestration, (c) the transaction costs and risk premiums associated with signing carbon contracts, and (d) the low elasticity of supply of CO 2 abatement. Although Canadian farmers are likely to participate to only a limited extent in the carbon‐offset market, many will find it profitable to adopt one or more of the BMPs for reducing net GHG emissions. Canadian agriculture is likely to contribute significantly to net emission reductions by voluntarily sequestering carbon due to the adoption of zero till in the last decade, and possibly by cutting fertilizer levels in the next decade. The contribution will be mainly a response to meeting personal economic objectives rather than being induced by direct incentives through the offset program.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".