(HOW) SHOULD I BE DOING THIS? PARTNERING IN RESEARCH WITH A CONSUMER SURVIVOR INITIATIVE AS AN OUTSIDER MASTER'S STUDENT
Bibliographic record
Abstract
Participatory action research (PAR) methodologies attract researchers both because they open up space to apply the values and principles associated with social justice and because they have the potential to deepen our understanding of an issue by giving us the opportunity to explore contexts and processes through people's experiences. This allows for new insights to emerge and relevant solutions to be discovered and implemented through emancipatory practices. However, choosing to do this type of research for a thesis as a master's of social work student without lived or research experience complicates an already complex endeavor and raises many dilemmas, questions and challenges. Reflecting on my experience of working with a peer-led community organization in Southern Ontario that provides services for people who have experienced mental health or substance use challenges and have interacted with the mental health system, this thesis will explore my journey of joining a research team that set out to use PAR to better understand peer support. Using a narrative inquiry approach, I will explore the tensions that occurred throughout the process of attempting PAR with a community agency within the university framework of completing a thesis. In the spirit of PAR and its intention to disrupt dominant approaches to research processes, I will use an alternative, storytelling format in order to best illustrate my circumstances, perspectives and the difficulties I faced as an outsider, student, university researcher trying to follow PAR principles. The lessons I learned will also be provided in an effort to make this type of undertaking easier for future students. Overall, I learned that we need to find ways to bridge and support the two cultures of graduate students and community groups in working together in PAR.
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.
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 | 0.015 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.016 |
| Scholarly communication | 0.016 | 0.012 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.006 | 0.013 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".