(Almost) everything you always wanted to know about activist research but were afraid to ask: what activist researchers say about theory and methodology
Bibliographic record
Abstract
This article seeks to explore the work of activist researchers located in social movements, non-governmental organisations (NGOs) and people's organisations with close relations to contemporary progressive grassroots struggles in a number of countries, mainly in the global South.Drawing from extensive interviews with these researchers on their processes and practice of research and knowledge production, located outside of academic institutions and partnerships, it documents their understandings about the theoretical frameworks and methodologies they employ.This article thus foregrounds articulations of actual research practices from the perspectives of activist researchers themselves.In doing so, it suggests that social movement scholars can learn more about the intellectual work within movements, including the relations between theoretical and methodological approaches and action, from a deeper engagement with the work of activist researchers outside of academia.
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 | 0.093 | 0.123 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.014 | 0.067 |
| Scholarly communication | 0.030 | 0.023 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.014 | 0.015 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".