Passion, persistence and pennies
Bibliographic record
Abstract
This interactive session will highlight the work of Fraser Healthy Authority (FHA) in British Columbia, Canada over the past 7 years to champion the development, implementation, and dissemination of its Advance Care Planning work for 1.5 million people throughout our system of care – 12 acute cares sites, 7500+ residential/long term care beds, and community programs. The FHALet's Talkprogram, with a passionate commitment to system level change and education, has developed user-friendly, culturally sensitive and easily accessible tools and resources which have been adapted by health and community organizations across Canada, USA and New Zealand for use in their jurisdictions. Our vision has led to a provincial Community of Practice with representatives from government, all BC regional health authorities, disease specific agencies, first responders, as well as the Canadian Hospice Palliative Care Association (CHPCA) ACP Project Task Group to continuously share resources and experiences. We have also been able to influence policy and uptake at a provincial level with a recent decision to adapt the My Voice Workbook and to place FHA'sLet's TalkDVD in all community libraries. Advocacy has resulted in new Advance Directive legislation which broadens options for documentation and choice at end of life. In partnership with Calgary Health Region, Health Canada and the CHPCA, we have been an important leader to support a National Symposium, Consensus and framework documents, and other initiatives that have promoted a Canadian approach to ACP implementation and a national framework and research agenda.
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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 | 0.005 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.010 |
| Scholarly communication | 0.018 | 0.011 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.004 | 0.014 |
| Insufficient payload (model declined to judge) | 0.073 | 0.027 |
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".