An Action Plan to Face the Challenge of Dementia: INTERNATIONAL STATEMENT ON DEMENTIA from IAP for Health
Bibliographic record
Abstract
An international committee set up through the IAP for Health met to develop an action plan for dementia. Comprehensive international and national initiatives should move forward with calls for action that include increased public awareness regarding brain health and dementia, support for a broad range of dementia research objectives, and investment in national health care systems to ensure timely competent person-centred care for individuals with dementia. The elements of such action plans should include: 1) Development of national plans including assessment of relevant lifecourse risk and protective factors; 2) Increased investments in national research programs on dementia with approximately 1% of the national annual cost of the disease invested; 3) Allocating funds to support a broad range of biomedical, clinical, and health service and systems research; 4) Institution of risk reduction strategies; 5) Building the required trained workforce (health care workers, teachers, and others) to deal with the dementia crisis; 6) Ensuring that it is possible to live well with dementia; and 7) Ensuring that all have access to prevention programs, care, and supportive living environments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.075 | 0.051 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.007 | 0.022 |
| Research integrity | 0.039 | 0.035 |
| Insufficient payload (model declined to judge) | 0.008 | 0.007 |
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".