ARTICLE Adaptive Capacity for Climate Change in Canadian Rural Communities
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
ABSTRACT It is widely acknowledged that promoting the long-term sustainability of rural areas requires an assessment of their capacity to handle stress from a host of external and internal factors such as resource depletion, global trading agreements, service reductions and changing demographics, to name but some. The sustainability literature includes a number of approaches for conducting capacity evaluations but is sparse regarding effective methods and empirical examples. This article provides one approach for assessing community capacity and gives results from its application to a specific Canadian rural community. The authors use general capacity variables and indicators to focus on a particular stress, namely impacts from climate change, and on one type of capacity, namely the capacity to adapt (to such climatic change). A basic framework and profiling tool (‘amoeba’) for describing the resources underlying community adaptive capacity are offered. The researchers provide a set of indicators reflecting social, human, institutional, natural and economic resources and relate them to climate change adaptation at the community level. Although the indicators cannot be replicated exactly for other rural communities, the essentials of the framework and the profiling tool can. In fact it is hoped that the ideas and example found in this article will encourage researchers to enhance and improve on the methods and results for work on community capacity.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it