A BIBLIOMETRIC ANALYSIS OF RESEARCH ON CLIMATE CHANGE AND PHYSICAL ACTIVITY: KNOWLEDGE VISUALIZATION AND REVIEW
Bibliographic record
Abstract
Climate change and physical activity have emerged as focal points of contemporary research.This study adopts a scientometric approach to review 1,268 bibliographic records and 70,522 citation records from the WoS Core Collection database, aiming to outline the research domains of climate change and physical activity through co-authorship, co-citation, and keyword co-occurrence analyses.Our findings highlight that: firstly, the research landscape is predominantly shaped by developed nations in Europe and North America, with the USA, Canada, and England being key contributors; secondly, the top ten authors in this field are spotlighted based on co-citation frequency, burst intensity, and centrality.Additionally, we identified four primary research themes and further unveiled the evolving research hotspots, delineating two promising research trajectories.In conclusion, potential future directions for research in climate change and physical activity are proposed.Furthermore, the study's principal contributions and limitations are elaborated upon, acknowledging the constraints imposed by utilized tools and data sources, and the influence of the researchers' expertise on result interpretation.
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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 | 0.017 | 0.075 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.173 | 0.181 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".