International Evidence on the COVID-19 Deaths of People Who Live in Long-Term Care Facilities
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
Abstract The COVID-19 pandemic has had a disproportionate impact, in terms of mortality, on people who live in Long-Term Care Facilities (LTCFs). This study involved compiling data on number of deaths of people who live in LTCFs and analyzing the extent to which differences between countries could be attributed to measures taken to control the spread of COVID-19 to LTCFs or to other factors. The study found that differences in how the data is collected make international comparisons difficult but that there is a clear correlation between number of COVID-19 deaths of residents in LTCFs and number of COVID-19 deaths of people living in the community. The study also found that countries that experienced a particularly high number of deaths in LTCFs during the first COVID-19 wave tended to have lower relative mortality in LTCFs in the subsequent waves, which potentially could be attributed to learning from the initial shock.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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