034 Palliative care and end of life: for shared reflections and decision-making at all levels
Bibliographic record
Abstract
More than any other area, end of life needs shared reflection and decision-making, at both individual (shared decision-making, SDM) and collective (deliberative democracy, social approach to death taboo) levels. In oncology, in particular, continuing treatments must be put into perspective with end of life quality.In this context, this symposium aims to discuss two experiences and two projects in France and Canada:At Gustave Roussy Institute, two focus groups of the patients-informal caregivers Committee identified SDM as a key issue in terminal cancer situations, just as much or even more so than at the beginning of the disease. Several areas emerged: chemotherapy completion; return to home or home care; clinical trial proposition. Equipoise and ’non-choice’ questions were raised.At a national level, the involvement of the National Center for Palliative and End of Life Care in the citizens’ convention on the end of life helped French citizens to adopt a common language and develop a relationship of trust, enabling them to make informed decisions that respect values and preferences of all concerned. This major participatory mechanism encouraged citizens to get involved, to co- construct common proposals and to respect dissensus, by putting them back at the heart of public debate.The model of compassionate communities developed in Quebec highlights the importance of partnership with citizens to promote and ensure the best possible health until the end of life, and to socially address death taboo. A project to implement compassionate communities in France will be presented.Finally, a participatory workshop aimed at questioning through a qualitative survey among oncologists and patients, the prescription of specific treatments with unproven efficacy in advanced phases of cancer, during and after COVID crisis, will be presented. The goal would be to co-construct a decision aid to promote SDM in these complex situations.
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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 | 0.024 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.023 |
| Scholarly communication | 0.022 | 0.017 |
| Open science | 0.003 | 0.020 |
| Research integrity | 0.014 | 0.020 |
| Insufficient payload (model declined to judge) | 0.041 | 0.014 |
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".