An overview of the consortia, non‐profit groups and other organizations in the Alzheimer's advocacy space over the past quarter century
Bibliographic record
Abstract
An Overview of the Consortia and Collaborative Initiatives, the Alzheimer's Research and Advocacy Space Over the Past Quarter Century BACKGROUND: 25 years ago, the number of organizations focusing on Alzheimer's research and advocacy was few and were often operating in geographic and functional silos. The Alzheimer's Association (founded in 1980), Alzheimer's Disease International (1984), the Alzheimer's Disease Research Centers (1984), the Consortium to Establish a Registry for Alzheimer's Disease (1986), the Alzheimer's Disease Cooperative Study (1991), and the National Alzheimer's Coordinating Center (1999) were the most prominent U.S. organizations, with a heavy focus on research. In Europe, organizations had a focus on policy, research funding, and care advocacy. Alzheimer's Europe (1990) drew member organizations together in Brussels to discuss pan-EU policy needs. Alzheimer's Research UK (1992) and Alzheimer's Society UK (1979), though both located in the UK, had outsized impact across Europe. In Japan, a super-aging society, the Health and Global Policy Institute, one of the largest international think tanks, has provided policy recommendations to the Japanese government since 2004. METHODS: Not only have the number and types of organizations expanded substantially, the silos have also begun to break down as groups have combined together on pre-competitive projects that span geographies and function to move the field forward faster and more collaboratively. We reviewed major consortia and summarized the projects by type and goals. Additionaly, we provide concept and network maps to show interconnectivity and influence between organizations, key stakeholders and funders. RESULTS: Dozens of consortia have been working collaboratively to improve the lives of individuals with Alzheimer's disease and related dementias. Public, private and philanthropic entities provide funding and other support for projects with a priority for data sharing and collective action. Advocacy organizations use the output to effect policy and clinical practice change and increase awareness and support to move the field forward faster for patients and their loved ones. CONCLUSIONS: Awareness of other organizations and their goals and efforts will reduce redundant efforts and will facilitate collaboration and progress. This awareness sets the stage for accelerated benefits for those impacted by ADRD over the next 25 years.
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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 | 0.020 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.021 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.014 | 0.012 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".