Welcome to the first issue of Transformative Social Work: A special issue on the impacts of the COVID-19 pandemic
Bibliographic record
Abstract
Welcome to the inaugural issue of Transformative Social Work, a new journal developed by an international editorial team and hosted by the University of Calgary, Canada. In this Special Issue, we reflect on the COVID-19 pandemic as it relates to social work. We address considerations such as heightened inequities, experiences and recommendations that have emerged at this unique juncture in history across the world. Articles in this issue amplify COVID-19 considerations for practice, professional support, social work education, community development, advocacy, and the importance of addressing ongoing and emerging community and societal inequities, with a focus on nurturing well-being and equity. Articles offer reflection on individual, community and population experiences, including substantial shifts, societal chasms and considerations for social work and society in moving forward. We are grateful to article authors who have provided important reflections, learning and recommendations in moving forward. Amplifying the breadth of experiences and perspectives as we emerge from this local and global experience is important both to document this experience relative to social work, and to critically consider steps for moving forward.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.010 |
| Science and technology studies | 0.010 | 0.001 |
| 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 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".