Bibliographic record
Abstract
Climate change is generally perceived as being unimportant by Canadian farmers who view the topic as not having significant implications for them. This insignificance to climate change in agriculture relates to the way in which the issue has been communicated. This paper reviewed the reasons for this perception and showed ways in which the agri-food sector is sensitive to climate change. Some opportunities for improving communication about climate change and agriculture were also presented. The following three main questions were raised: (1) do studies that focus on change in average temperature over several decades capture the pertinent conditions with which farmers will have to deal? (2) are discussions of crop yield and production impacts the best way to understand the potential implications of climate change for agriculture and for farmers? and (3) is it reasonable to assume that agriculture will efficiently and effectively adapt to climate change. It was concluded that in order to affect change, it is necessary to show that climate change is not just about mean temperature several decades away, but rather involves changes in risks associated with variability. It was emphasized that the assumption that agriculture will adapt to climate change must be corrected. 43 tabs., 1 tab., 1 fig.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".