Bibliographic record
Abstract
The increasing rates of homelessness in the United States and Canada have been a growing social and health concern for several decades. On any given night, it is estimated that over 500,000 individuals in the United States and 35,000 individuals in Canada experience homelessness. It is well documented that individuals experiencing homelessness have higher morbidity and mortality rates than the general population. The social and health disparities that individuals experiencing homelessness encounter are known to many in the homeless-serving sectors. However, these extant disparities have increased, and become exposed because of the COVID-19 pandemic. The COVID-19 pandemic has increased the risk of individuals becoming homeless due to the economic instability it has created and, once homeless, there is an increased risk of contracting COVID-19. If individuals do contract the virus, the risk of severe outcomes is heightened due to the higher rate of underlying medical conditions such as cardiovascular disease and diabetes in homeless populations. Currently, the primary public health measures to help curb the spread of COVID-19 are to mandate stay-at-home orders and social distancing. When stay-at-home orders are announced, there is an underlying assumption that individuals have a home. This is not the case for the hundreds of thousands of individuals experiencing homelessness in Canada and the US. These individuals use various spaces to stay safe, such as overnight emergency shelters, daytime drop-in centers, or sleeping in tent encampments. Many of these environments increase the risk of contracting and transmitting COVID-19.
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 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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".