Public pedagogues of change: advocacy networks, civil society organisations, and self-help authors in Mexico
Bibliographic record
Abstract
This article explores informal adult education for change in Mexico through the conceptual lens of social movement learning and public pedagogy. It adopts a multiple case design featuring two advocacy networks, two civil society organisations, and two self-help authors. It analyses how they position themselves as change agents addressing issues of food sovereignty, violence against women, social justice, environmental justice, financial insecurity, and emotional health. The article deconstructs how such agents diagnose problems and prescribe solutions that share a common logic: the unlearning of hegemonic knowledges and the learning of alternatives. It presents a continuum of pedagogical strategies, ranging from the most public (spectacular protests and social media work) to most private (targeted lobbying and workshopping). It contributes, methodologically and analytically, to literature at the intersection of social movement learning and public pedagogy. Methodologically, in a field dominated by stand-alone case studies from North America, it offers a comparative study of three domains of informal adult education in Mexico. Analytically, it unpacks public pedagogical messaging common to these domains and explain the strategies, interests and political implications that differentiate them. We encourage educators to assess the range of public pedagogical work that may be mobilised in the pursuit of change.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.011 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".