CREATING A SPACE FOR INNOVATIVE TEACHING, LEARNING AND SERVICE DELIVERY
Bibliographic record
Abstract
The School of Social Work Community Clinic opened its doors in June, 2014 in a donated space in a local parish hall. With very few resources initially the clinic now has its own rented space, serves a caseload of over 200 marginalized community members and has provided field placement experiences for over 75 BSW/MSW, pharmacy, psychology, nutrition, nursing, and occupational therapy students. In this article, we will highlight the steps we took to create and develop the Clinic with a social justice/anti-oppressive foundation, and the practice-teaching approaches we use with our students. We will also describe how we are integrating an interprofessional and community-university partnership culture in our day-to-day work with marginalized populations. This process will be described and discussed in relation to both interprofessional health education and the provision of relevant and meaningful services to clients. The community development techniques we used to develop our clinic and how we have been able to grow and expand will be highlighted. The partners we have established in government, the university, and the community that have contributed to a more sustainable future are also described.
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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 | 0.010 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.010 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.005 | 0.016 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".