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Record W3161024779 · doi:10.15173/a.v1i2.2824

A HUMAN RIGHTS APPROACH TO FOOD INSECURITY IN INUIT NUNANGAT

2021· article· en· W3161024779 on OpenAlexaboutno aff
Hannah Feldman

Bibliographic record

VenueAletheia · 2021
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsHuman rightsMandateIndigenousGovernment (linguistics)Political scienceRight to foodIndigenous rightsFood insecurityEconomic growthHomelandFood securityPublic administrationDevelopment economicsGeographyPoliticsLawAgricultureEconomics

Abstract

fetched live from OpenAlex

The Inuit Tapiriit Kanatami, the national organization for Inuit in Canada, has voiced serious concern about the food insecurity crisis in Inuit Nunangat, the Inuit homeland comprising Nunavut, Nunavik, Nunatsiavut, and the Northwest Territories (Inuit Tapiriit Kanatami, 2019). The widespread and disproportionate experiences of food insecurity in Inuit Nunangat requires critical examination, especially when access to adequate food has been identified as a human right (OHCHR, 2010). My research paper aims to explore this topic of food insecurity as a human rights concern in Inuit Nunangat. A human rights approach acts as both a pathway to investigate, and a tool to inform, policy development. Such an investigation is especially relevant given Canada’s international reputation and constitutional mandate to grant equal protection of rights to all citizens. In this essay, I review international and domestic human rights frameworks that intersect with Inuit food insecurity, in addition to evaluating Canada’s current interventions. I ultimately argue that, based on Canada’s commitments to uphold rights to food, health, and Indigenous self-determination, the government must increase the enforceability of food rights in domestic policy and, second, there must be strengthened collaboration between the government and Inuit partners to more appropriately conceptualize, and respond to, food needs in Inuit Nunangat.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.717
Threshold uncertainty score0.999

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.067
GPT teacher head0.370
Teacher spread0.302 · 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
Published2021
Admission routes1
Has abstractyes

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