Synthesizing the links between secure housing tenure and health for more equitable 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
Millions of households in rich and poor countries alike are at risk of being unwilfully displaced from their homes or the land on which they live (i.e., lack secure tenure), and the urban poor are most vulnerable. Improving housing tenure security may be an intervention to improve housing and environmental conditions and reduce urban health inequalities. Building on stakeholder workshops and a narrative review of the literature, we developed a conceptual model that infers the mechanisms through which more secure housing tenure can improve housing, environmental quality, and health. Empirical studies show that more secure urban housing tenure can boost economic mobility, improve housing and environmental conditions including reduced exposure to pollution, create safer and more resourced communities, and improve physical and mental health. These links are shared across tenure renters and owners and different economic settings. Broader support is needed for context-appropriate policies and actions to improve tenure security as a catalyst for cultivating healthier homes and neighbourhoods and reducing urban health inequalities in cities.
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 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 | 0.020 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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