Picturing the researcher: Using photovoice to document the research assistant experience during the COVID-19 pandemic
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
The article is a reflection by two graduate research assistants (GRAs) who experienced the effects of the COVID-19 pandemic on the in-person interactions through which qualitative researchers usually learn about human experiences. With in-person research curtailed, the authors were compelled to think creatively and find other ways to continue their research and develop meaning. The researchers reflected on their experiences as GRAs for the study ‘Thriving in Canada: Learning from the (photo) voices of women living on a low income engaged in action research to improve access to health and social services’. Taking advantage of pandemic-related study delays, the researchers explored the photovoice method in more depth and used photovoice to document their own lived experience as GRAs, and their learning. They practised self-reflexivity and worked to improve their visual-based photovoice facilitation skills. This illustrated essay is the story of the authors’ experiences over the past year working as GRAs during the COVID-19 global pandemic.
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 | 0.046 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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