Are We Happy in Densely Populated Environments? Assessing the Impacts of Density on Subjective Well-Being, Quality of Life, and Perceived Health in Montreal, Canada.
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
Compact city development has been increasingly promoted as a tool to encourage urban sustainability and to reduce humans’ environmental footprint. The impacts of such urban development on subjective well-being (SWB), Quality of Life (QOL), and perceived health—non-monetary metrics of prosperity—have not been extensively explored in the North American context. This paper delves into the relationship between density and happiness by analyzing a travel survey distributed in Montreal, Quebec, Canada (n = 4,148). A cumulative logit model assessed levels of happiness—as measured by SWB, QOL, and perceived health—against confounding variables such as age, gender, household size, marital status, education, income levels, and residential self-selection, while including neighborhood density as our main policy variable. Results do not show that population density affects perceived health or SWB. However, a small inverse relationship between QOL and population density was observed. Analyzing neighborhood characteristics through their effect on SWB, QOL, and perceived health provides further evidence on the links between the urban landscape and happiness, and the study’s results can inform zoning and land-use policymaking.
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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 | 0.001 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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