Caring for Caregivers: Facing up to Tough Challenges
Bibliographic record
Abstract
This paper, the first in a series of three, sets the stage for two accompanying papers detailing a pair of groundbreaking initiatives to support "at risk" caregivers of high-needs older persons and children in Toronto. Although caregiver burden and stress are often conceptualized primarily as a function of the needs of cared-for persons and the capacity of caregivers, fragmented formal care systems also play a key role. Solutions must take individual-level and system-level factors into account; clarify expectations about what we expect unpaid caregivers to do; redefine the unit of care to include caregivers; and think beyond short-term fixes to mechanisms, such as interdisciplinary teams and integrated care plans, that promote forward planning, accountability, best practices and crisis avoidance.
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 | 0.025 | 0.043 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.034 | 0.019 |
| Scholarly communication | 0.019 | 0.022 |
| Open science | 0.004 | 0.033 |
| Research integrity | 0.017 | 0.029 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".