Cardiovascular Disease Risk Among the Poor and Homeless – What We Know So Far
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
Homelessness [and poverty] is rapidly escalating across North America and is associated with dire implications for public health and our health care systems. Both are compelling states of existence affecting all ages, ethnicities and both genders. Homelessness frequently evolves through a complex interaction of factors that are both internal and external to the individual themselves. Once homeless, equitable access to both preventative and remedial health care is lacking and is associated with a higher than average burden of cardiovascular disease [CVD] risk factors, morbidity and mortality and is accompanied by disproportionately high health care costs. The emergence of limited, small scale programs aimed at addressing the unique health and social needs of the homeless is encouraging. However, there has been inadequate commitment at the National, State or Provincial and local levels to implement policies and dedicate funding and resources to the expansion of such "individual level" interventions into comprehensive programs that deliver sustainable, integrated prevention and services, especially with regard to CVD. The long-term solutions that address the links between homelessness and CVD lie in preventing homelessness and reversing the trends in our health care system that create disparities for lower socioeconomic status [SES] and homeless individuals.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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