Capacity building in dementia research: insights from the World Young Leaders in Dementia
Bibliographic record
Abstract
Early-career researchers from low- and middle-income countries face systemic barriers to professional development and leadership growth. This article presents results from an initiative led by the World Young Leaders in Dementia (WYLD), including a leadership-focused session at the Alzheimer's Association International Conference 2024 and a global survey completed by 130 dementia researchers from 17 countries. The survey explored five capacity-building domains critical for leadership development. Over half of the survey respondents stated that scientific research in their country was not prioritized in public policy. Additionally, only 39% report holding full-time academic positions. The most cited challenges included lack of funding sources, training opportunities, and physical workspace. These findings highlight the urgent need to invest in research, training, and infrastructure to support future scientific leaders. As dementia incidence rises, prioritizing capacity building is essential to ensure global equity in research. HIGHLIGHTS: Early-career dementia researchers face major barriers, especially in LMICs. A networking session and a global survey explored capacity-building needs in dementia research. Key obstacles: lack of funding, training, workspace, and protected research time. Leadership development is a critical component of sustainable research capacity.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".