Challenging power relations in food systems governance: A conversation about moving from inclusion to decolonization
Bibliographic record
Abstract
This reflective essay explores power relations, with a particular focus on racialization, that flow through dominant forms of food systems governance, with an aim to create more participatory governance models. Four of the authors asked a group of five scholars, activists, and practitioners (also authors) who identify as Black, Indigenous or People of Color (BIPOC) to discuss during a conference session issues of Indigenous food sovereignty, decolonization, Whiteness, and inclusivity in food systems governance. This paper presents and analyzes the content of the session, part of the 2021 Global Food Governance Conference. We reflect on common themes from the session and put forth recommendations: encouraging greater inclusion in existing forms of food systems governance, achieving decolonization through creating diverse new governance models, and addressing the deeper power structures that underpin the dominant food system itself. We also suggest a research agenda, with the “what” of the agenda unfolding from a process of agenda development that centers BIPOC scholarship. The frameworks offered by the panelists are a starting point, as more work is needed to move towards decolonizing food systems governance research. Finally, a collaborative agenda must attend to the inextricable links of food systems governance to other fundamental issues, such as the emerging field of planetary health.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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".