Understanding Newcomer Challenges and Opportunities to Accessing Nature and Greenspace in Riverdale, Hamilton, Ontario: A Neighborhood-Centered Photovoice Study
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
BackgroundAccess to and engagement with greenspace is related to improved health benefits. We sought to collaborate with community members as partners in research and co-creators in knowledge to better understand which components within a newcomer-dense community help or hinder individual and community efforts to access greenspace and nature-based activities.MethodsWe used photovoice methodology to engage with local residents in focus groups, photowalks, and photo-elicitation interviews. Themes were developed using direct content analysis.ResultsA total of 39 participants (ages 11-70 years; median years in Canada of 3.25 years) were engaged in this program of research. From the analysis, we developed four themes: (a) peace and beauty; (b) memories of home; (c) safety and cleanliness; and (d) welcoming strengthened and new opportunities. Participants associated nature with peace, citing it as "under-rated" but "vital" to the neighborhood. Via photographs and stories, participants also shared a multitude of safety concerns that prevent their access to green/outdoor spaces for healthy active living programs or activities (e.g., woodchip-covered playgrounds, ample amounts of garbage littering the park and school grounds, lack of timely ice removal on sidewalks, limited safe biking paths, and unsafe motor vehicle practices at the crosswalks surrounding local parks).ConclusionTo translate the key ideas and themes into an informed discussion with policy and decision-makers, we held an in-person exhibition and guided tour where community members, the lead photovoice researcher, and SCORE! principal investigator shared information about each theme in the form of a pseudo-narrative peppered with prepared discussion questions.
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 | 0.002 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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