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Record W4224312305 · doi:10.3390/nu14091737

Relationality, Responsibility and Reciprocity: Cultivating Indigenous Food Sovereignty within Urban Environments

2022· article· en· W4224312305 on OpenAlexafffundabout
Elisabeth Miltenburg, Hannah Tait Neufeld, Kim Anderson

Bibliographic record

VenueNutrients · 2022
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsUniversity of GuelphUniversity of Waterloo
FundersCanadian Institutes of Health Research
KeywordsFood sovereigntyIndigenousReciprocity (cultural anthropology)Urban agricultureParticipatory action researchCitizen journalismSociologyFood systemsThematic analysisTraditional knowledgePublic relationsFood securityAgricultureQualitative researchGeographyPolitical scienceSocial scienceEcology

Abstract

fetched live from OpenAlex

There are collective movements of Indigenous food sovereignty (IFS) initiatives taking up place and space within urban environments across the Grand River Territory, within southern Ontario, Canada. Indigenous Peoples living within urban centres are often displaced from their home territories and are seeking opportunities to reconnect with culture and identity through Land and food. This research was guided by Indigenous research methodologies and applied community-based participatory research to highlight experiences from seven Indigenous community members engaged in IFS programming and practice. Thematic analysis revealed four inter-related themes illustrated by a conceptual model: Land-based knowledge and relationships; Land and food-based practices; relational principles; and place. Participants engaged in five Land and food-based practices (seed saving; growing and gathering food; hunting and fishing; processing and preserving food; and sharing and distributing), guided by three relational principles (responsibility, relationality, and reciprocity), framed by the social and physical environments of the place. Key findings revealed that employing self-determined processes to grow, harvest, and share food among the Indigenous community provide pathways towards IFS. This study is the first to explore urban IFS initiatives within this region, offering a novel understanding of how these initiatives are taking shape within urban environments.

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)0.002
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 score0.119
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0120.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.045
GPT teacher head0.335
Teacher spread0.290 · 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

Citations33
Published2022
Admission routes3
Has abstractyes

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