Eco-social work and community resilience: Insights from water activism in Canada
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
Summary Only recently has social work begun to grapple with its place in relation to environmental issues. While considerable progress has been made in bringing environmental considerations into the centre of our profession's scholarship and practice, this project is far from complete. Drawing on environmental literature and based on findings of a qualitative case study of water activism in one Canadian city, this paper argues that the concept of “community resilience” provides both a practical and a conceptual framework for advancing social work's engagement with issues of the natural environment and environmental justice through community praxis. Findings In Guelph, Ontario, Canada, water issues are the focal point of considerable community activism. The case study research reveals, however, that while water is the focus, much of this activism is driven by three broad social priorities that reflect ideas of community resilience and which suggest entry points for social work participation in community-based environmental initiatives: self-reliance and sustainability, localization and direct citizen participation, and community. Applications “Community resilience” is increasingly popular in environmental and community development fields as a conceptual framework for assessing and building the capacity of communities to support wellbeing in the face of environmental change, adversity and risk. While the concept of “resilience” is well established in social work, “community resilience” remains under-examined in social work literature. In this paper, the author draws attention to this arena of resilience thinking, highlighting its potential for the integration of considerations of the natural environment into social work scholarship, education, and practice.
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 it