Bibliographic record
Abstract
Family members of people with dementia often experience a continuous and profound sense of loss and subsequent grief as they live through the progression of the disease. “Dementia creates ambiguous loss. The duality of your loved one’s being absent and present at the same time is confusing, and finding meaning (or making sense of your situation) becomes immensely challenging. Without meaning, it’s hard to cope”. (P.Boss, 2011) Unfortunately, there is a dearth of educational resources and support groups on ambiguous loss and grief related to dementia. The Alzheimer Society of Canada (ASC) conducted thorough research reviews and Pan-Canadian interviews with health-care providers, individuals with dementia and caregivers who have benefited from grief and loss interventions in order to better understand this issue and to inform the development of resources for both health care professionals and caregivers. ASC developed 2 practical evidence-based resources to identify, acknowledge and normalize the feelings of loss and grief experienced by caregivers of people with dementia – from diagnosis to end-of-life and after caregiving- while providing strategies for understanding and responding to grief reactions. The first resource targets healthcare providers in order to help them understand this phenomena and the second is designed for people with dementia, families and their support network. These resources also inform the curriculum of 5-week psycho-education support groups for family caregivers. The goal of this session is to address grief, validate the experience of ambiguous loss and equip family and professional caregivers with practical strategies to help them support people with dementia from the initial onset of symptoms and diagnosis to end-of-life and life after caregiving.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.039 | 0.008 |
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".