Mental health is positively associated with biodiversity in Canadian cities
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
Cities concentrate problems that affect human well-being and biodiversity. Exploring the link between mental health and biodiversity can inform more holistic public health and urban planning. Here we examined associations between bird and tree species diversity estimates from eBird community science datasets and national forest inventories with self-rated mental health metrics from the Canadian Community Health Survey. We linked data across 36 Canadian Metropolitan Areas from 2007-2022 at a postal code level. After controlling for covariates, we found that bird and tree species diversity were significantly positively related to good self-reported mental health. Living in a postal code with bird diversity one standard deviation higher than the mean increased reporting of good mental health by 6.64%. Postal codes with tree species richness one standard deviation more than the mean increased reporting of good mental health by 5.36%. Our results suggest that supporting healthy urban ecosystems may also benefit human well-being.
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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 | 0.000 | 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) | 0.002 | 0.001 |
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.
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