Bibliographic record
Abstract
In Ontario, we are currently dealing with a profound public policy void in the area of retirement home regulation. Ret1ecting the neo-liberal political context, much of this industry's growth has occurred with limited or no legal regulation and minimal, if any, involvement from the government. This paper discusses various possible options for addressing the issue of unregulated retirement homes, with a special emphasis on voluntary accreditation. This study sought the unique perspectives of retirement home administrators from both accredited and non-accredited homes. Conversations with participants converged around a number of key issues, including affirming the importance of regulation, affirming the need to compete and succeed in the retirement home market, emphasizing the negative aspects of accreditation, and the responsibility of being accountable to various stakeholders. Administrators also offered their perspectives on policy issues and the role of government. This study provides insight into the question of "In whose interest is the current retirement home system?" It became evident throughout this study that there is value in creating some level of government regulation beyond what currently exists. It is argued that future policy in this area must hold the interests of seniors as primary, and not the interests of the business community.
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.014 | 0.006 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".