Successful Structural Social Work: Strategies for Modern Day Practice
Bibliographic record
Abstract
Social workers often report challenges associated with trying to maintain structural social work (SSW) amid conventional settings. Although there is some literature on practical applications of SSW, the literature is outdated. Consequently, this research was inspired by, and derived from, Bachelor of Social Work students who consistently sought practical wisdom and stories to gain insight into how to successfully maintain and practice SSW in modern conventional settings. Qualitative interviews were conducted with 28 structural social workers. Five key themes were identified regarding how one might successfully embody SSW: (a) adopting a strategic approach; (b) gaining credibility and competency; (c) building relationships and rapport; (d) navigating risk, and (e) recognizing barriers and being inventive. The findings are explored, implications for practice and knowledge dissemination discussed, and future research considered.
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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 | 0.019 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.016 | 0.028 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.004 | 0.020 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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; 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".