Engaged in Research/Achieving Balance: A Case Example of Teaching Research to Masters of Social Work Students
Bibliographic record
Abstract
This article considers the use of participatory action research and Photovoice as a tool for engaging graduate level social work students in research education. Photovoice is an investigative tool that assists people in critically reflecting on the everyday social and political realities of their lives, enriching their understanding of their communities and the issues pertinent to them, while at the same time, giving them a voice from which to educate others on these issues. In the context of a group assignment, 26 social work students, enrolled in an introductory graduate research course, were asked to reflect upon the question, “What does balance look like for you in the MSW program?” Thirty-two photographs with captions were submitted and analyzed by class members for relevant themes. Balance was described as existing along a continuum from balanced to unbalanced and was comprised of four major themes: connection, nurturance, keeping perspective, and disengagement. Although this teaching strategy was not formally assessed, preliminary impressions are that students benefited from participating in the Photovoice activity.
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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 | 0.018 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.024 | 0.021 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.006 | 0.008 |
| 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; 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".