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Promoting children’s health through community-led street interventions: analyzing sustained voluntarism in Canadian School Streets

2024· other· en· W6958687646 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueFigshare · 2024
Typeother
Languageen
FieldSocial Sciences
TopicComputational and Text Analysis Methods
Canadian institutionsUniversité de MontréalQueen's University
Fundersnot available
KeywordsVoluntarism (philosophy)Status quoCharterAction (physics)Public healthCommunity organizationSustainability

Abstract

fetched live from OpenAlex

Abstract Background Active School Travel (AST) initiatives align with the Ottawa Charter for Health Promotion, which calls for ‘creating supportive environments’ and ‘strengthening community action.’ However, their reliance on volunteers poses sustainability challenges. The main objectives of this study were to document the motivations, satisfaction, and experiences of volunteers involved in sustaining two AST initiatives in Ontario for an entire school year. Methods Two volunteer-led School Street initiatives in Kingston, Ontario successfully operated during pick-up and drop-off times of each school day. The first initiative operated for the entire 2021-2022 school year, and the second operated for the entire 2022-2023 school year. These initiatives were the first of their kind in the province of Ontario, Canada. Volunteers from both sites (n = 56) participated in online surveys and their motivations, satisfaction, and experiences of their role were compared using the 2-sided Fisher’s Exact Test. Results Over 80% of volunteers were highly motivated to promote safety and over 70% of volunteers were highly motivated to disrupt the status quo of unsupportive, car-centric urban environments by reimagining how streets can be used. By taking collective action to re-shape the environment around these public schools to support healthy, active living, our findings reveal that over 90% of volunteers were highly satisfied. Of the volunteers, 87% felt they contributed to child safety and 85% felt they had developed stronger community connections. They appreciated the short (i.e., 40 minute) time commitment of each shift, weekly email communications by the community organization leading the initiative, and the volunteer schedule. They also appreciated the positive social interactions during volunteer shifts, which they felt outweighed the minimal resistance they experienced. Conclusions This research demonstrates the importance of logistical, motivational, and social factors in recruiting and retaining volunteers for community-led School Streets. Our findings support appealing to prospective volunteers’ influence in achieving School Street objectives (e.g., improved safety) in recruitment efforts, as well as highlighting School Streets’ innovative approach. Communicating with volunteers throughout School Street planning and implementation processes and limiting traffic in the closed street zone (i.e., by excluding the school staff parking lot and private driveways from the scope) are additional recommendations based on the findings of this study.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.241
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.1670.001

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.

Opus teacher head0.066
GPT teacher head0.407
Teacher spread0.341 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it