Participatory pedagogy online: reflections from a Global Leadership Virtual Field School
Bibliographic record
Abstract
When the COVID-19 pandemic hit, Canadian graduate students in a Global Leadership program were set to travel to India for a field school course hosted by a community-based partner organization. This chapter documents the authors’ efforts to move this course online and create a Global Leadership Virtual Field School, whereby students participated in virtual site visits to community groups working on a range of social issues, including the empowerment of Indian women, youth, and marginalized communities. Drawing from transformative pedagogy in both content and process, lessons shared in this chapter are applicable to educators in one of at least three ways. These include when they are (a) facing travel restrictions preventing a planned field excursion; (b) wishing to engage virtually with community groups from different parts of the world; or (c) wanting to create a more physically and financially accessible learning experience than a typical field school would entail due to the cost of travel and potential for physical barriers. This chapter shares sample classroom activities and assignments, while linking the course to transformative pedagogy.
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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 | 0.001 | 0.004 |
| 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 | 0.003 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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; both teacher heads agree on what is shown here.
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".