Learning to Sleep without Perching: Reflections by activist-educators on learning in social action in Ghanaian social movements1
Bibliographic record
Abstract
This article conveys results from a participatory action research (PAR) engagement with activist/educators working in Ghanaian social movements. First, this PAR group has articulated two typologies from which to understand Ghanaian social movements based on their processes of organization, communication and learning rather than merely the issues, resources or populations that occupy their focus. Second, expanding on Griff Foley’s (1999) notion of learning in struggle, the PAR group provides three lenses from which to view learning in social movements in Ghana. Both of these contributions help to present a much needed African inflection to ongoing discussions of learning in social movements, especially as these contributions attempt to maintain a complex view of learning based on the shifting characteristics of power and capital.
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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 | 0.013 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.022 | 0.028 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.004 | 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".