Where Does Research Occur in Geriatrics and Gerontology?
Bibliographic record
Abstract
The International Plan of Action on Aging 2002 emphasized the need to promote and develop research on aging, especially in underdeveloped countries. This article aims at describing the current situation with regard to the international scientific production in the field of geriatrics and gerontology. All articles published in journals included in the categories "Geriatrics and Gerontology" of the Science Citation Index or "Gerontology" of the Social Science Citation Index in 2002 were analyzed. There is unquestionable predomination by the United States, which participates in 53.8% of the articles analyzed, followed by the United Kingdom (9.66%) and Canada (6.66%). The production of the 15 European Union countries together is 31.2%. When adjustments are made for economic or population factors, other countries show their importance: Israel and Sweden, for example. Authors from richer countries participate in more than 95% of the articles, whereas those in less-developed countries tend to publish less, and when they do so, it is through collaboration with more-developed countries. In general, only 10.5% of the articles are written in collaboration with institutions from different countries. One of the keys to stimulating research in less wealthy countries would seem to be precisely through collaboration. This would aid the transfer of knowledge and experience, allowing researchers in these countries to obtain autonomy to perform their own studies independently and to provide them with the ability to gain access for their publications at the international level.
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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 | 0.252 | 0.329 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.016 | 0.029 |
| Science and technology studies | 0.012 | 0.050 |
| Scholarly communication | 0.060 | 0.076 |
| Open science | 0.004 | 0.019 |
| Research integrity | 0.022 | 0.014 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".