Bibliographic record
Abstract
Williams and colleagues make a valuable contribution to the home care policy literature, however, their arguments are not always convincing. Missing is a more nuanced discussion of research showing that even when governments provide more supportive services for older adults, families continue to provide care, and a discussion of alternative forms of caring that may arise in the future such as care from siblings and non-married older adults helping one another. Drawing on research pointing to several countries that offer caregivers a range of services would also have been helpful. Furthermore, it is not clear, as the authors argue, that the reason policy makers have moved toward providing for higher needs patients with fewer and fewer services for lower needs patients is a 'wait and see' attitude. Alternative reasoning is just as plausible. The benefits of providing supports to caregivers of children are well articulated but this does not negate the need among caregivers to older adults where some of the issues differ from caring for sick and disabled minors. Finally, action items for government are not offered but could have been helpful. Examples are provided.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.049 | 0.124 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.010 | 0.013 |
| Scholarly communication | 0.014 | 0.040 |
| Open science | 0.008 | 0.013 |
| Research integrity | 0.037 | 0.040 |
| Insufficient payload (model declined to judge) | 0.046 | 0.014 |
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 source (direct Gemma or distilled Codex), 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".