Advancing Allyship Through Anti-Oppression Workshops for Public Health Students: A Mixed Methods Pilot Evaluation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This pilot mixed methods evaluation describes the impact of an anti-oppression workshop on allyship development among a group of public health graduate students. After completing a mandatory anti-oppression workshop, a survey including closed- and open-ended questions was administered to 41 public health students specializing in health promotion. Closed-ended questions gathered basic demographic data and Likert-type scale responses to assess changes in participant knowledge, awareness, and attitudes surrounding anti-oppression concepts discussed during the workshop, while open-ended questions asked respondents to reflect on how such changes might influence their development as allies. A response rate of 65.85% (27 respondents) was achieved. The majority of the study group were between the ages of 20 and 24 years (74.07%), self-identified as straight (77.8%), and self-identified as non-White (77.8%), while almost the entire group identified as female (92.59%). Five key themes emerged from a directed content analysis of qualitative data, identifying the importance of anti-oppression workshops for allyship development: conducive environments, positionality, knowledge, active listening and learning, and advocacy. These themes were used to construct a mixed methods joint display for comparative interpretation of quantitative and qualitative data. Mixed methods analysis revealed that anti-oppression workshops can promote allyship development by increasing knowledge of key terms and concepts associated with anti-oppression and facilitating critical reflections on power, privilege, and social location. Our findings demonstrate a profound need for ongoing anti-oppression training among future public health students and professionals.
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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 | 0.034 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it