Leading Multi‐level Change to Build a Better System to Support Family Caregivers
Bibliographic record
Abstract
Abstract Background Worldwide the care economy is in crisis.[1] The care economy includes both paid and unpaid services provided to populations who are unable to independently support themselves. Family caregivers (FCGs) make up the largest proportion of the care workforce, providing over 90% of care for people with dementia,[2 3] yet they remain marginalized in the existing healthcare systems.[4] While some caregiving scholars call for education to enhance the competencies of health and social care providers to partner effectively with caregivers,[3 4] other stakeholders advocate for broader systemic and policy change. Objectives Report on how an academic‐community partnership co‐design group focused on educating about person‐centered supports for FCGs is advocating for systemic change. Project description Advocacy is a critical population health strategy that emphasizes collective action to effect systemic change. The essential elements of advocacy includes: clear policy goals, solid evidence‐base, values linked to equity, broad coalition support, framing in mass media, and use of policy for change.[5] Methods Drawing on learning health systems and collective impact approaches, we are weaving together the actions of FCGs, researchers, health and social care providers, leaders, and management to build a No Wrong Door, seamless health & social care support system to enable FCGs to maintain their wellbeing & sustain care. Results Our goal is for formal recognition of the FCG role within health and social care policy. Broad consultations with stakeholders, then co‐design of the Caregiver‐Centered Care education built a robust collaborative of Caregiver Champions. While educating the health workforce is a population health approach to address known gaps in supporting and working with FCGs across the care trajectory, [3 4 6] such education is also developing FCG champions who can advocate across settings and communities. Within Alberta, this collective voice has resulted in recognition of FCGs in the new Continuing Care Act, Bill 11. Discussion An integrated FCG system is still a work in progress. Many FCGs do not connect with services they need until they are in a crisis. Conclusion Now we are working on strategy mapping to shift the collective focus from reactive problem solving to co‐creating the future.
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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 | 0.032 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.008 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.003 | 0.026 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.019 | 0.002 |
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".