The Co-construction of Agricultural Policies as a Bottom-up Adaptation Strategy to Climate Change and Variability (CCV) in the Regional County Municipality (RCM) of Haut-Richelieu, Québec
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The overall objective of this article is to improve the understanding of the adaptation process to climate change and variability at the farm and the farming community levels through a mostly bottom-up process, while using the approach of co-construction in the Regional County Municipality (RCM) of Haut-Richelieu. To achieve this, the grounded theory approach is used. The results show that all participants recognized the fact that climate change is happening. According to the farmers, climate change is the main determinant of adaptive capacity, followed by institutional support. Most farmers recognized that extremes (or variability) are associated with climate change. To a lesser extent, some farmers concluded that one should not separate climatic factors from non-climatic factors. The results also show that while some farmers recognized the positive and the negative side of climate change and variability (CCV), the others are very optimistic about it as if they only see the positive side; there is nonetheless a need to see both sides of CCV. Moreover, there is still some uncertainty related to CCV, which comes from disinformation and desensitization of the farmers mainly in relation to the causes of CCV along with the nature of climatic events. Despite the latter, the results show that agriculture in the RCM of Haut-Richelieu is well adapted to cope with climate change and variability. Farmers have already adopted measures to cope with CCV; however, they adapt spontaneously. Furthermore, nearly all farmers need help mainly from the agricultural public and private institutions to better adapt to CCV.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 it