Our way(s) to action research: Doctoral students’ international and interdisciplinary collective memory work
Bibliographic record
Abstract
This study involved six Swedish and Canadian doctoral students who shared interests in using action research in professional education in different disciplines. We employed Noffke’s three dimensions of action research as a theoretical framework (i.e., the Professional, the Personal, and the Political). Using collective biography as a methodology, we cooperatively examined how our personal and professional agendas and macro-level structures have been shaping our intentions to conduct action research projects in our respective disciplines. The key findings of this international and interdisciplinary collective biography relate our growing awareness of the intimacy between research and life in various professional and geographic contexts. Collectively addressing our shared frustrations, we celebrated action research as a methodology that attends to the dynamic and concrete lived experiences of our participants in various spatio-temporalities. Reflecting upon the hybridity of our own researcher identities, we were also able to see the intimate relation between ourselves as active citizens and critical action researchers who are determined to take up the challenges and engage in critically oriented action research that could nurture more “caring,” “empowering,” and “transforming” public spheres.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.055 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.045 | 0.065 |
| Scholarly communication | 0.035 | 0.013 |
| Open science | 0.003 | 0.032 |
| Research integrity | 0.007 | 0.016 |
| Insufficient payload (model declined to judge) | 0.004 | 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".