Popular education and learning as the bridge between activism and knowledge production
Bibliographic record
Abstract
Academic research can make significant contributions to policymakers and other researchers interested in building evidence-based knowledge. However, it is difficult for students to imagine how their research can effectively contribute to social change while respecting curriculum requirements, especially with regard to maintaining methodological and scientific rigour and the validity demanded by academic standards. The rich work and experience of Aziz Choudry contribute directly to overcoming these obstacles and challenges, as he conceptualised research and knowledge production as an activity not exclusive to academia or research institutes, but widely present within social organisations and social movements.In this paper, we reflect on our experiences of conducting research within community organisations as graduate scholars. Building on our respective research experience, including popular education in our research practice, we highlight how popular education spaces offer opportunities for scholars to disseminate their research results and contribute to raising awareness, but also to achieve the standards of intellectual rigour expected by academia. The main goal of this paper is to position the field of social movement learning and knowledge production as key for students who want to develop engaged and relevant research.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".