Addressing climate change from a social development approach: Small cities and rural communities’ adaptation and response to climate change in British Columbia, Canada
Bibliographic record
Abstract
Climate change is having a very real impact, affecting not only ecosystems but also the socio-economic systems of small cities and rural communities. Globally, climate change is a consequential concern, since it is contributing to an increase in global temperatures, changing precipitation patterns, raising sea levels, and natural hazards. Locally, the effects of climate change vary, depending upon the region, with communities experiencing the impacts of climate change differently and at various degrees. This article presents research findings from a study on climate change, disasters, and sustainable development that provide insight into the diverse perspectives of community members on climate change in six communities in the Interior and Northern regions of British Columbia, Western Canada. A common denominator between these six communities is how social development is being applied to address climate change. The concept of social development encompasses social and economic well-being. The social development approach involves processes, activities, and institutions working together to develop the social and economic capacities of individuals and communities. In particular, for social workers working with individuals, families, and communities impacted by climate change, the social development approach is effective in addressing social and economic needs. This article will examine the differing perspectives and attitudes of affected community members and the role of social development with respect to climate change adaptation and response. It will also provide suggestions on how social workers can support and apply the social development approach in communities experiencing the impacts of climate change.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.020 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".