Evaluating the protective effect of public open space on social connectedness: evidence from a natural experiment cohort study in three Canadian cities
Bibliographic record
Abstract
Community design has the potential to address urban isolation and loneliness at a population level, but limited research on the causal effects of the built environment constrains evidence-based action in cities. This study examined the effect of public open space on changes in social connectedness among adults (n = 665) during the COVID-19 pandemic, using geospatial data from OpenStreetMap and health survey data from three cities (Montréal, Saskatoon, and Vancouver). Treating the pandemic as a natural experiment, we used multilevel models to analyze whether public open space exposure (defined as the ratio of land area within 500m of home) modified changes in community belonging, loneliness, and neighbouring from 2018 to 2020/2021. First, we found little evidence of changes in social connectedness in our cohort overall and within subgroups. On average, loneliness increased slightly, and belonging and neighbouring remained stable. Second, we found that higher public open space exposure (≥10 % neighbourhood land area) had a modest protective effect on community belonging only (0.14, 95 % CI = 0.01 to 0.27). These findings add to a limited but growing evidence base on the role of the built environment in shaping social connectedness, while highlighting challenges involved in examining causal impacts. As cities invest in public open space to support policy goals around sustainability and livability, evaluating co-benefits for social connectedness are critical opportunities for strengthening the evidence on built environment solutions to social isolation and loneliness. • Cities need evidence on environmental solutions to social isolation and loneliness. • We used the pandemic as a natural experiment on the effects of public open space. • Mean loneliness in our cohort (n = 665 adults) increased by 5 % from 2018 to 2020. • Public open space was protective for belonging but not loneliness or neighbouring.
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 | 0.024 | 0.034 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".