Teacher leadership during COVID-19 in Africa and Latin America: an exploratory qualitative study in six countries
Bibliographic record
Abstract
There is limited evidence about teacher leadership during education emergencies. Drawing on interviews with 70 teachers and education stakeholders in parts of Africa and Latin America, this exploratory study investigates grassroots examples of teacher leadership during early COVID-19 school closures. The findings indicate that teachers worked individually and collectively to find high-tech and low- or no-tech solutions to ensure learning continuity. In addition, teacher-led efforts often prioritized student and community well-being by building and maintaining social connections with students and families, supporting student mental health and physical health, and protecting students from heightened risk factors during COVID-19 school closures, such as early marriage, adolescent pregnancy, and child labor. Teachers also acted by taking the lead as community mobilizers by engaging with local communities to educate about COVID-19 risks and prevention. The paper discusses barriers and facilitators to teacher leadership in low-income settings. It concludes by identifying emerging lessons to strengthen teacher leadership and proposing recommendations to activate teachers as a central pillar of resilience in education systems during crises.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".