Taproot, rhizome, disappointment, possibility: action research with(in) sociomaterial perspectives
Bibliographic record
Abstract
Inspired by the question ‘how might we do Action Research differently?’, this article provides an introductory diffractive mapping of the concepts and empirical studies intersecting Action Research and sociomaterial theories. After tracing the roots of Action Research, I zigzag to describing how Action Research has grown differently in prior studies informed by sociomaterial theories. I use these theories to disrupt everyday assumptions about Action Research in education and to make thinking visible and unfamiliar. I offer up a series of short vignettes based on a recently completed Action Research project with French as a Second Language (FSL) teachers in Ontario, Canada. I collide these data events with various sociomaterial concepts to open new opportunities for analysis when engaging in Action Research. Specifically, I engage the phases of the Action Research cycle and more-than-human collaboration in a research project to highlight the ways in which these processes are created and unfold uniquely, and how rhizomatic thinking can further open trajectories for transformation within this work.
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 | 0.023 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.013 | 0.159 |
| Scholarly communication | 0.024 | 0.022 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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; 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".