Australian qualitative insights from an international project on environmental practice in social work
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
The environmental crisis continues to create new challenges for social workers and their clients and this has been recognised in the academic literature. For example, authors have highlighted the increasing impact of climate change, a need to advocate for environmental justice, and to reassert a sense of ecological justice. While academic attention has increased, it is more important to understand the practice of social workers in the field. This paper reports on components of an international project, focusing on the qualitative data collected through a national survey of Australian social work and human service professionals that explored their perspectives regarding the natural environment and climate change. The paper focuses on insights gained from a thematic analysis of the qualitative responses using NVivo data management software and reports in relation to the micro, meso and macro levels of practice. It discusses barriers and facilitators to expanding environmental practice in workplaces and provides suggestions for expanding social worker education that will support them to embrace and promote environmental practice. Results confirm ideas already represented in the literature, however also propose new directions in research and practice in the field at local, regional and global levels.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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