Practice-Based Research Policy in the Light of Indigenous Methodologies: The EU and Swedish Education
Bibliographic record
Abstract
Abstract Participatory research methods in education, such as action research, have been around for some time. Recently, not only researchers but also research policy makers have highlighted the importance of participation between society and research. Citizen science, science with and for society, and practice-based educational research are examples of approaches that aim to bring society and research more closely together. In this paper, we explore underlying premises behind practice-based research policies in the EU and in Swedish educational research policy. In order to understand how participation can be understood, we have analysed them closely through a lens of Indigenous methodologies. Results reveal an underlying understanding of participation as nonreciprocal where expertise is a key concept, researchers hold this expertise, and where the main responsibilities for research lie with the researchers. However, the results also indicate a sense of respect for practice and a willingness to form relationships between research and practice. Keywords: practice-based research, school-based research, participatory research, Indigenous methodologies, Citizen science, research policy
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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 | 0.070 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.009 | 0.028 |
| Scholarly communication | 0.021 | 0.008 |
| Open science | 0.001 | 0.017 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".