Research Trend of Socioscientific Issues Based on Scopus Journal Database: A Bibliometric Study from 2011 to 2021
Why this work is in the frame
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Bibliographic record
Abstract
The implementation of socioscientific issues in science learning has increased recently. The purpose of this study is to highlight research trends over the previous ten years by examining the findings of bibliometric papers on socio-scientific issues. A total of 648 articles from the English-language Scopus database were analyzed using the VOS Viewer. The results of the analysis reveal that studies related to socio-scientific issues over the last ten years are still an increasing research trend. Keywords related to socio-scientific issues such as argumentation, decision making, scientific literacy, critical thinking, and climate change. The journal sources that were most cited were the international journal of science education, journal of research in science teaching, research in science education, international journal of science and mathematics education, science and education. Articles that are widely cited by other authors are Sadler T.D, Zeidler, D.L, Osborn, J, Eilks, I, Erduran, S, Lederman, N.G, Simon, S. Leading countries in the field of socio-scientific issues are the United States, Germany, Sweden, Taiwan, Australia, Turkey, United Kingdom, Canada, Spain, Indonesia. Further researchers can conduct scientific studies on socio-scientific issues by using educational technology in the form of digital media and other variables that have not been studied or are still little researched.
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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 | 0.015 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.028 | 0.039 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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 it