Co-constructing Knowledge to Benefit an Innovative Social Work Practicum: A Participatory Action Research (PAR) and Integrated Knowledge Translation (iKT) Approach
Bibliographic record
Abstract
This participatory action research (PAR) study is of an innovative virtual pilot practicum program developed through a university – school board partnership to provide relevant experiential learning for social work students pursuing their bachelor’s and master’s degrees while delivering social work services to the community. The Support and Aid to Families Electronically (SAFE) program employed technology novel to the School of Social Work, supported a service user population new to its students, engaged students in ground-up policy and protocol development, and instituted in-house practicum supervision for the first time. PAR was incorporated at the outset, along with an integrated knowledge translation (iKT) approach. The principal investigator supported the student-researcher participants to develop and conduct their own research on this learning opportunity, facilitating co-ownership and co-authorship of this work (Lind, 2007). Over 312 pages of data were collected through journaling and a group chat initiated by the social work students out of a need for connection during this novel virtual practicum. Using reflexive thematic analysis (Braun & Clarke, 2021), the students identified four main themes: program development, collaboration and problem-solving, peer support, and the importance of community creation. These themes told a story of a community of learning, as the seven students turned to each other for expertise within the group rather than viewing educators as the only experts able to provide knowledge (Brown & Campione, 2013). This mutual support among the student-researchers facilitated a sense of power and authority while actively engaged in the processes of learning (Groundwater-Smith & Mockler, 2016). This co-constructed research facilitated the co-construction of the practicum to the benefit of both students and service users.
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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 | 0.009 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.033 |
| Science and technology studies | 0.010 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".