The global health initiative and ACCESS Uganda partnership program: Developing health seminars for community health workers and evaluating nutritional knowledge and education practices in rural Uganda
Bibliographic record
Abstract
The median (IQR) journal impact factor was 3 (1.9-4.7), and publications were cited 8 (3-19) times, even though many were published so recently that there have been few citation opportunities to date.Alumni who were postdoctoral Fellows (p < 0.001), from LMICs (p < 0.001), and were supported in earlier Program years (p¼0.003)had higher publication outputs, compared to doctoral Scholars, Americans, and later Program trainees.Other demographic factors (e.g., sex), duration of support (1 vs. 2 years), and research topics (e.g., infectious vs. non-communicable diseases) had little association with publication output except for trainees with research topics involving children, who had on average fewer publications (p¼0.003).Going Forward: The concentrated, mentored clinical research training in global health settings provided by the FICRS-F Program produced significant research productivity from its alumni.Program output grows each year, as alumni develop mature research careers and continue to publish.Publications of doctoral Scholars are likely to increase as they complete additional training and enter career positions.In 2012, FICRS-F was decentralized among 20 institutions in five consortia (Fogarty Global Health Program for Fellows and Scholars), emphasizing postdoctoral trainees from the US.Our results, particularly the finding that LMIC citizens had higher publication numbers than did US trainees, may inform the future evolution of the Program.
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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 | 0.013 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".