FINDING RABBIT HOLES WITHOUT FALLING IN: NAVIGATING PALLIATIVE CARE POLICY IN CANADIAN LONG-TERM CARE
Bibliographic record
Abstract
Canada has one of the most regulated policy-laden long-term care (LTC) systems in the world. While there is noble intent, the high volume of policies creates ambiguity for knowledge users on how to provide quality end of life care for residents. More importantly, the desires of residents and/or their families for quality of life often get lost in the jungle of rules and regulations. Our research team titled SALTY (Seniors: Adding Life to Years) is assessing the complex interplay of LTC policies that influence palliative care. To date, we have collected 275 LTC related policies and influencing documents in four Canadian provinces and by using a policy analysis framework from NCCHPP (National Collaborating Centre for Healthy Public Policy), we plot each in a logic model (NCCHPP) according policy function, sphere of influence (e.g., health authority, provincial, federal) and geography. Using a hermeneutics content analysis approach, each policy is examined using Kane’s (2006) 11 domains for measuring quality of life. This iterative process reveals both the extent to which policies have resident’s quality of life at the forefront and its intended and unintended effects on other factors in the logic model. In this poster, we describe the duel framework used to structure the policy analysis aimed at adding ‘life to years’ within a palliative approach. We present our preliminary results of palliative care exemplary policies, gaps, and tensions between what should be done (system) and what is preferred (resident choice) depending on the circumstances and geography.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".