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Record W7062407796

THEY FEED ME GOOD Relational Food Systems in Saskatoon

2022· dissertation· en· W7062407796 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity Library (University of Saskatchewan) · 2022
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicParticle Detector Development and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsFoodwaysParticipant observationEthnographyPsychological resilienceNegotiationCorporate governanceFood systemsRelational theoryResilience (materials science)
DOInot available

Abstract

fetched live from OpenAlex

This research study examines the foodways of Saskatoon households, exploring relational food networks as a factor toward fairer health outcomes with a focus on resistance, resilience, and culture. This study uses critical ethnography to glean an accounting for trauma and an accounting for uplifting relational food networks. Data are drawn from interviews, photographs, media (animations), and participant observation. An iterative analysis is informed by intersectional and relational frameworks and follows a hybrid inductive-deductive approach. Findings are presented in representational and creative ways, with participants sharing stories that unveil the problematic of resilience in the face of colonialism and its relationship to food systems and health. The discussion considers socio-cultural factors, systemic racism, and inequality to advance a better understanding of cultural dimensions and political constraints linked to food insecurity. It contributes an accounting of variation in urban households in Saskatoon, their food choices, and their foodways, including models of governance that mitigate system failures to keep families fed. The lives of Saskatoon people in this study come together with separate stories of healing and violence, power and cultural restitutions of health, joy, and food. Participants live in different households but share similar collective histories of colonization and relentless systemic disparity. Their stories are also connected through the negotiation of food related wellbeing in urban spaces that re-dignify connections to culture, restore relational food strategies, and reclaim the land.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.499
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 studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.008
GPT teacher head0.167
Teacher spread0.160 · 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 designQualitative
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
Published2022
Admission routes1
Has abstractyes

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