Articulating inherent values of action research for newcomers coming from the field of territorial development
Bibliographic record
Abstract
This paper discusses the inherent values of action research for newcomers coming from the field of territorial development. The discussion is framed around three dimensions: 1) inquiring about problematic situations in real-time; 2) contextual-temporal qualities of the process; and 3) reflecting-acting on what we have reasons to value being and doing as researchers, participants, facilitative actors, and citizens. The conceptualisation builds on theoretical influences, most notably the writings of John Dewey and action research for territorial development, and my own practice. Two cases are discussed. One is about a Knowledge Transfer Partnership in Scotland, and the other is with regards to on-going work in the wine-producing territory of British Columbia, Canada.
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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 | 0.362 | 0.219 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.020 | 0.215 |
| Scholarly communication | 0.065 | 0.050 |
| Open science | 0.006 | 0.040 |
| Research integrity | 0.015 | 0.024 |
| Insufficient payload (model declined to judge) | 0.003 | 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".