Perspectives of Socio-Scientific Issues in Educational Research: A Bibliometric Analysis
Bibliographic record
Abstract
The intricate nature of socio-scientific issues has gained traction among researchers in recent decades. This study explores educational research focused on socio-scientific issues over the last 21 years (2002-2023) using the bibliometric method. The analysis of 350 Scopus-indexed articles was conducted, examining publication trends, influential contributors, and research trajectories through citation, co-occurrence, and co-citation analyses. Co-citation analysis reveals a complex intellectual structure within the field, with a dominant cluster of influential authors and several smaller, specialized research communities emerging. Analysis revealed that the major themes discussed by the examined articles include the nature of science, climate-change decision-making, and education for sustainability, which are crucial in addressing contemporary challenges in education and society. This study highlights the significance of fostering interdisciplinary cooperation and integration of technological aspects into future research. It also identifies the necessity of addressing gaps in research resources, improving knowledge accessibility, and strengthening international collaborations for the field's advancement.
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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 | 0.016 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.034 | 0.032 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads 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".