How pluralistic is the research field on adult education? Dominating bibliometrical trends, 2005-2012
Bibliographic record
Abstract
What the field of adult education research is and how it can be described has been a debated issue over the decades. Several scholars argue that the field today is heterogeneous, borrowing theories and methods from a range of disciplines. In this article, we take such statements as a starting point for empirical analysis. In what ways could it be argued that the field is pluralistic rather than monolithic; heterogeneous rather than homogenous? Drawing on bibliographic data of the top cited articles in three main adult education journals between 2005 and 2012, we illustrate how the citation patterns have tendencies of homogeneity when it comes to the geographical country of authorship, since the USA, UK, Australia and Canada dominate, as well as the research methods adopted, since qualitative approaches have near total dominance. Furthermore, there is a tendency to adopt similar theoretical approaches, since sociocultural perspectives, critical pedagogy and post-structuralism represent more than half of the articles in our sample. At the same time, the results of our analysis indicate signs of scholarly pluralism, for instance, in terms of authorship, since both early career researchers and established researchers are represented among the top cited publications. We conclude the article by arguing that empirical analysis of publication and citation patterns is important to further the development of reflexivity within the field, not least for early career researchers, who might benefit from knowledge about what has been recognized among peers as worth citing in recent times. (DIPF/Orig.)
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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 | 0.019 | 0.074 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.041 | 0.101 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".