Increasing diversity in peer-to-peer education: A case study of manager experiences with student paraprofessionals in learning development in the Canadian context
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 autoethnographic case study examines the experience of managers with hiring student paraprofessionals into various roles within peer-to-peer education models and programmes as a method to increase the diversity in learning development services in the Canadian context. Tailoring learning development through peer-to-peer education models for diverse student groups is an important aspect of how learning development supports students in higher education. Including the knowledge and perspectives of student paraprofessionals who better reflect the diversity of the population we serve has been an important aspect of our practice. Our purpose for this case study is to better understand how our experiences with paraprofessional staff diversity, over a seven-year period (2010-2017), have influenced our practice of learning development in an institutional context focussed on creating a more inclusive and welcoming environment on campus to better support the needs of diverse learners. The knowledge that we gained through this analysis of diversity and peer learning as an approach to learning development may serve as an example of the value of autoethnography as a method to provide useful insight to professionals and leaders in the field.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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