A Qualitative Study Exploring Best Practices And Applications Of Green, Eco, And Environmental Social Work In Canadian Social Work Practice
Bibliographic record
Abstract
Humanity and society are deeply connected to nature and the environment at their core. Through processes of colonization, the Industrial Revolution, urbanization, consumerism, and capitalism, people and societies have become increasingly disconnected from the natural environment. Introduced as a helping profession through the Industrial Revolution, social work began rooted in environment but quickly changed to understand human and societal wellbeing through the narrow scope of the social environment through the person-in-environment approach. Modern day issues of climate change, environmental degradation, environmental racism, and environmental justice movements have necessitated social work’s increased understanding of the natural environment. The purpose of this thesis is to help build an understanding of the current climate for green, eco, and environmental social work in Canada, including understanding diverse historical and current perspectives and experiences of the land and environment in connection to societal wellbeing. An exploratory qualitative study employing key informant interviews was utilized to help identify best practices and guidance for the direction of green, eco, and environmental social work in the areas of research, education, and practice at the micro and mezzo levels. In-depth semi-structured interviews were conducted with seven social work educators and practitioners well-versed in green, eco, and environmental social work through semi-structured key informant interviews. Interviewees were based both in the United States and in Canada. Following data transcription and analysis, the following key themes were identified: life purpose and meaning; deep environmental roots; impacts of nature; exploring connection; transforming social work education; emergent practices for green, eco, and environmental social work; and challenges/barriers to education and practice. These findings and implications are shared to strengthen the case for green, eco, and environmental social work integration into social work education, research, 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.
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 | 0.013 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.042 | 0.023 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| 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".