‘Walking the talk’ of environmental social work practice: Lessons learned from social workers committed to land-based practice in the Northwest Territories
Bibliographic record
Abstract
The research presented in this thesis explored environmental social work; in particular, it responds to a gap in the literature regarding the lack of a clear practice model for social workers to follow, by focusing on how environmental social work is done. In order to offer an in-depth, qualitative look at what environmental social work can look like in practice and in specific places, I looked to self-identified social workers living and working in the Northwest Territories (NWT), Canada. The six social workers who responded to this call are all working in ways that integrate land, place, and the physical environment into their social work practice. Due to the impacts of the Covid-19 pandemic, the research was conducted entirely via distance using telephone, e-mail, and Zoom. Using a critical place inquiry approach and framed by theories of ecosystem approaches to health, grounded normativity, and relational validity, six in-depth interviews were conducted with social workers who shared their experiences of land-based practice in their personal and professional lives. Findings took the shape of five themes: ‘Lessons from the Land’, ‘Lessons in Ways of Being for Social Workers’, ‘Lessons from Being in Relationship’, ‘Lessons for our Workplaces and Profession’, and ‘Lessons in Practice’. The findings offer insight and practical examples for social workers seeking to connect their practice to the land; they also contribute practice wisdom to emerging discussions regarding both what can be done in environmental social work practice and how.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.006 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".