Advancing Radical Food Geographies Praxis through Participatory Film
Bibliographic record
Abstract
The academic field of geography is deeply embedded within capitalist and settler colonial logics and has played a major role in suppressing and concealing Indigenous histories along with rights claims, cultures, and practices. While geography’s origins are deeply problematic, over the past decades, many scholars and practitioners have offered counter theoretical and practical perspectives and approaches. Radical food geographies praxis is one such example that is rooted in engaged and socially relevant theory, practice, and reflection. In this article, we present reflections from our experience with radical food geographies research praxis through a collaborative food sovereignty, action-oriented project co-developed and co-led by two settler academics, a documentary filmmaker, and the Chief of Batchewana First Nation. From 2018-2022, we embarked on an effort to share stories of Batchewana First Nation’s historical and current fishing practices, culture, and governance through the co-creation of a feature length documentary film titled, Lake Superior Our Helper: Stories from Batchewanaung Anishinabek Fisheries (https://www.batchewanaungfish.ca). To write this paper, we engaged in a process of collective autoethnography that involved documenting our individual reflections on the project and then bringing these perspectives into dialogue. Emerging from this process, we share our insights for an engaged research praxis, focusing on meaningful and authentic relationships and partnership building, participatory film as a tool for collaborative research, and radical food geographies. We present these insights with the aim of improving our own individual and collaborative practice and to share our learnings with other scholars, activists, and community practitioners engaged in similar partnership-based and praxis-oriented geographic research.
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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 | 0.015 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.022 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 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".