An International Asset Map of Clinicians, Educators, and Researchers Pursuing Better Medicine Use in Children: Initial Findings
Bibliographic record
Abstract
The world's 1.89 billion children (age 0-14) too frequently receive treatments that have not been validated through clinical pharmacology research, especially in low- and middle-income countries. Initial findings from an international asset map of professionals and clinician scientists available to address the needs for education, research, and treatment support suggest a critical shortage of clinical pharmacologists, clinical pharmacists, and other professionals with advanced training in the evaluation of therapies for childhood conditions and illnesses. A total of 497 individuals responded to a survey conducted between May 2015 and February 2016. An alarming signal is apparent showing that, while the overall resource pool is unquestionably limited, 87% of relevant qualified personnel are located in high-income countries. The data suggest an urgent need for targeted training in pediatric clinical pharmacology, with particular focus on the needs in Africa, Latin America, and most of Asia.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".