Bibliographic record
Abstract
Bereavement represents a significant public health concern as grievers often suffer from co-morbid health problems, increased use of health care resources, periodic hospitalizations, and even mortality in the first 2 years after the death. Furthermore, grievers frequently encounter major obstacles when seeking formal support, including lack of access to specialized grief support due to temporal, financial or geographic constraints. To address these gaps in service, the Canadian Virtual Hospice, in collaboration with pan-Canadian partners developed MyGrief.ca, the world's first evidence-based, online psycho-educational tool to support those who do not or cannot access existing in-person loss and grief supports and as a supplementary resource for those who do. The tool also serves as a rich educative tool for health providers. The content was developed with families and international leaders in the field of bereavement, with attentiveness to issues of cultural diversity. Funding was providing by the Canadian Partnership against Cancer. MyGrief.ca includes nine self-directed modules that cover a diversity of topics across the bereavement trajectory. Embedded within each module is a great variety of video testimonials detailing grief narratives that represent diverse age, cultural, gender, and sexual orientation groups. Attendees will be given an in-depth tour of MyGrief.ca, followed by an interactive conversation on the tool with a bereft family member, health provider and educator on their unique perspectives and the overall impact of using MyGrief.ca. Bereavement represents a significant public health issue with grievers often presenting with concurrent health difficulties in the first 2 years after the death. This workshop will present a novel tool developed by the Canadian Virtual Hospice, specifically an online self-directed bereavement resource to support patients, families and health providers.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.902 | 0.661 |
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".