Adult education research: exploring an increasingly fragmented map
Bibliographic record
Abstract
Against the background of internal developments of adult education as a field of study, and new external conditions for research, this article examines how the configuration of adult education research has been evolving, particularly over the last decade. Our analysis draws on a two-pronged approach: a reading of four seminal articles written by adult education scholars who have conducted bibliometric analyses of selected adult education journals; as well as our own review of 75 articles, covering a one-year period (2012–2013), in five adult education journals that were chosen to provide a greater variety of the field of adult education in terms of their thematic orientation and geographical scope than has been the case in previous reviews. Our findings suggest that the field is facing two main challenges. First, the fragmentation of the map of the territory that was noticed at the end of the 1990s, has continued and seems to have intensified. Second, not only practitioners, but also the policy community voice their disappointment with adult education research, and we note a disconnect between academic adult education research and policy-related research. We provide a couple of speculations as to the future map of adult education as a field of study and point to the danger of shifting the research agenda away from classical adult education concerns about democracy and social rights.
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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 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.042 | 0.060 |
| Science and technology studies | 0.008 | 0.033 |
| Scholarly communication | 0.033 | 0.041 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".