Contestable professional academic identity of those who teach research methodology
Bibliographic record
Abstract
A professional academic identity is important because it supports a sense of belonging and contributes to the scholarly advancement of a discipline. However, a professional academic identity for those involved in teaching research methodology is particularly complex and diverse. This research surveyed 144 academics from 139 universities in 9 countries, who are involved in teaching research methodology, and examined the extent to which participants construct their professional academic identity around research methodology. The study also sought to examine whether participants view research methodology as a distinct discipline. Findings show that academics teaching research methods inhabit multiple identities. Some identified as expert researchers, while others associated with particular research methods, along with a clear epistemic attachment, within a particular area of scholarly inquiry. Furthermore, few participants described themselves as research methodologists, and stressed the significance of teaching research methodology as a distinct discipline. Findings also revealed that the majority of the institutions involved in the study approach research methodology as ‘a service course’ and predominantly taught by volunteer academics. This study contributes to our understanding of how research methodology courses are organized, and the broader implications of the different approaches to the scholarly advancement of research methodology as a distinct subject.
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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 | 0.028 | 0.051 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.008 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".