GLOBAL TRENDS IN AGEISM RESEARCH: A SYSTEMATIC BIBLIOMETRIC REVIEW
Bibliographic record
Abstract
This study aims to conduct a bibliometric analysis of academic publications on ageism and age discrimination between 2000 and 2024. A total of 3,932 articles indexed in the Web of Science (WoS) database were systematically analyzed to identify publication trends, citation networks, thematic clusters, and interdisciplinary collaborations. The findings reveal a significant increase in research output post-2010, with the COVID-19 pandemic further accelerating scholarly interest in this field. The majority of publications fall under the "Gerontology" category (30.74%), with the United States, the United Kingdom, and Canada leading in academic productivity. Keyword analysis highlights dominant themes such as "older workers," "healthcare inequalities," and "social stereotypes." The study underscores the critical role of academic research in combating ageism and calls for enhanced interdisciplinary collaborations and policy-oriented interventions in future studies.
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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 | 0.032 | 0.125 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.171 | 0.175 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".