Bridging the divide: Exploring the disconnect between micro and macro practice and implications for BSW field education
Bibliographic record
Abstract
The social work profession addresses wellbeing at individual levels, or the micro, as well as structural and systemic levels, the macro. By addressing the micro and macro, social workers work towards social justice for individuals and communities to create structural systemic change. Yet, there is an increasing focus on micro and clinical-focused content in social work education. This focus creates various challenges when social work students are placed in macro-focused field education placements. A study into the experiences of Bachelor of Social Work (BSW) students, field instructors, and faculty liaisons considered the experiences of participants in their involvement of macro-level field education. The study found two emerging themes: macro-level practice is undervalued and underrepresented in the BSW curriculum, and yet at the same time there exists a deep desire for more understanding and integration of macro social work in social work education and field education. Implications for social work education, regulation, and the profession are also 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 | 0.021 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.015 | 0.046 |
| Scholarly communication | 0.019 | 0.027 |
| Open science | 0.003 | 0.018 |
| Research integrity | 0.003 | 0.007 |
| 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".