Understanding community leaders’ and program coordinators’ perceptions of and needs from a community systems map: a qualitative study
Bibliographic record
Abstract
Abstract Objectives A systems map for the Riverdale community in Hamilton, Ontario has documented programs, activities, and spaces for healthy, nature-based activities. A systems map was created to provide an approachable resource for community members. As a means of understanding whether this map would prove useful, interviews with community and organization leaders were conducted. The objectives of this study were to 1) characterize user engagement with recreational and active living programs and services located in and around the Riverdale community, 2) determine existing barriers to and facilitators of accessing recreational and active living programs for those in the Riverdale community, as perceived by those who deliver programs and, 3) improve the functionality and usability of the system map, including any information or services that may be missing.□□ Methods Twenty 60-minute semi-structured interviews were conducted with community leaders and program coordinators who focus on healthy active living and work within the Riverdale community. Results We learned that Riverdale programming is typically gender-specific, women-dominated, and targeted to children and youth. Additionally, cost, transportation and accessibility, and language were the greatest barriers to accessing recreational programming. Conversely, facilitators for program involvement included transportation assistance, compensation, and food provision. Finally, interviews revealed the need for sustainability, clarity, and language options within the systems map. Conclusion This work procured the necessary information to edit the interactive systems map according to community needs. With this map, Riverdale community members are able to access a source of information about activities and services.
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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 | 0.016 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.008 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".