Promoting Trauma-Informed Practice in Social Work Education Through an Experiential Learning Program
Bibliographic record
Abstract
Experiential learning (EL) as a method of trauma-informed critical learning and transformative learning pedagogies is essential in social work education. EL allows social work students to actively become engaged in community practice and social justice activities while creating a safe learning environment and providing students with an opportunity to reflect on their own values, actions, and behaviors. EL, grounded on the 5Rs approach (respect, reciprocity, relevance, responsibility, and relationships), promotes trauma-informed critical learning for students to learn and grow. EL opportunities were first provided to the undergraduate social work course Social Work with Communities (SOWK 401) in 2019 and again in 2020 and 2021 at the School of Social Work at MacEwan University, Edmonton, Alberta. This chapter explores how EL fosters trauma-informed, critical, and transformative learning for students’ personal and professional growth through their participation in community-based projects and programs in both local and global contexts; it is grounded in the personal narratives of the co-author Rita Dhungel.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".