Bibliographic record
Abstract
Long-term care (LTC) for older persons is based on the wrong foundations. It is too wedded to protection and not directed enough to maximizing personal goals. Tinkering at the margins will not suffice. Bigger, bolder steps are needed. A first step is to re-examine the goals of such care and the tools we have at hand to meet them. We need to re-examine the major elements of what we have taken for granted. A number of forces must be harnessed, and in some cases effort must be redistributed. Effective collaboration will depend on shared goals. Unless LTC is viewed as something that is desired, we will never receive more than reluctant support from any quarter. Good care must be seen as making a difference; that difference can be in function or in quality of life; it may be as subtle as slowing decline, but it must be made apparent to be appreciated.
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 | 0.019 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.026 |
| Scholarly communication | 0.018 | 0.021 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.024 | 0.035 |
| Insufficient payload (model declined to judge) | 0.021 | 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".