Therapaws: A partnership between students, staff, and therapy dogs on a university campus
Bibliographic record
Abstract
Partnering with students in action research and asking them how and why they would like to work with staff and other students to improve campus culture and student wellbeing is the cornerstone of this case study. Investment in student mental health and wellbeing is increasingly recognised as a priority in higher education, with novel approaches such as dog therapy programs being introduced in universities around the world. This case study highlights a project where staff and students partner to co-design, co-implement, and co-investigate a mental health and wellbeing program that combines dog therapy with students-as-partners principles. The student-led dog therapy program (Therapaws) provides a practical, evidence-based example of how the principles of SaP can be employed to create an effective intervention into student mental health and wellbeing. This multi-authored case study is also an example of a collaborative writing process—a true partnership.
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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 | 0.001 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".