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Record W4408366215 · doi:10.1177/27538699251324727

Possibilities for decolonizing food planning: Addressing ontological dominance, affective and relational dispositions, and (re)imagining just food futures

2025· article· en· W4408366215 on OpenAlexaff
Colin Dring, Stephanie Lin, Robert Newell, Erin MacLachlan, Dana James, Tabitha Robin

Bibliographic record

VenuePossibility Studies & Society · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicOrganic Food and Agriculture
Canadian institutionsUniversity of British ColumbiaRoyal Roads University
Fundersnot available
KeywordsFutures contractDominance (genetics)PsychologySociologySocial psychologyEconomicsFinancial economics

Abstract

fetched live from OpenAlex

In this paper, we invite readers to engage with different possibilities for relating to the world and to food by imagining and enacting future food systems rooted in relational ontologies and interrupting the ontological dominance of settler-colonial food systems. We outline a framework that supports individuals, communities, and organizations to unlearn and disinvest from a Eurocentric agrifood paradigm that requires violence and oppression, and employs neoliberal, racist, patriarchal, capitalist logics. The framework is intended to provide language and concepts that may support food system actors to engage with critiques of colonialism, and their own complicities in maintaining contemporary food systems and structures. We advance promising pathways to creating relational communities of respect, care, accountability, and reciprocity These pathways are vital to healing intergenerational trauma, embodying reciprocal forms of mutual aid, unlearning dominant ontological and epistemological foundations, and imagining and enacting alternative food system configurations and relationships to food, nature, and other-than human beings in pursuit of just food futures and food sovereignties.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.283
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.076
GPT teacher head0.319
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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