“It Really Put a Change on Me”: Visualizing (Dis)connections within a Photovoice Project in Peterborough/Nogojiwanong, Ontario
Bibliographic record
Abstract
Photovoice is an arts-based participatory action research method that uses photography as a means for individuals, usually those facing marginalization, to document and foster group dialogue around the stories of their valuable lived experiences. This paper details a photovoice project run under the participatory planning project NeighbourPLAN, in Peterborough, Ontario, with the residents of the Downtown Jackson Creek group. The focus of the photovoice project was working with residents facing various forms of marginalization and barriers to reflect on what (dis)connections look like in their community. The findings conclude that photovoice generated new subjectivities, as residents reported feeling more connected to their community after taking photos. The process was generative in that it reminded residents of other creative outlets that they enjoyed doing and inspired them to engage with creative reflection in other ways. The findings also determined that green spaces, non-judgmental institutions, accessible amenities, safe housing, and well-maintained streets were critical for resident researchers’ feelings of connectedness. I conclude with recommendations from the residents’ feedback on the method and project, along with highlighting the promising potential of arts-based and storytelling methods when conducting research with marginalized groups.
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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.025 | 0.014 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".