Bibliographic record
Abstract
In her thought-provoking and well-researched paper, Irene Jansen presents some of the main challenges within the facility-based long-term care (LTC) sector and advocates for three major policy changes and investments. But her aim in writing the paper is to start the conversation. I am happy to oblige Jansen's call to tackle other critical issues and thank the editors of Healthcare Papers for the opportunity to briefly express my views. I concur that the federal government is not adequately fulfilling its stewardship role in helping to ensure - along with the provinces and territories - that the facility-based LTC system has the ways and means to meet the legitimate needs of LTC residents and the people who care for them. A national dialogue should be convened with an emphasis on what quality looks like to the resident, not to LTC ministries or funding authorities. The resident is the nucleus around which all else revolves. The challenges in the areas of supply and demand, the patchwork of services and health human resources are huge. But additional staffing and more beds will not add real value to the system unless they are closely linked to the principles of culture change - the journey to improving living and working conditions in LTC across the Canadian landscape. And it is here where I make my prime contribution to the conversation.
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 | 0.011 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 0.019 |
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; both teacher heads agree on what is shown here.
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".