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Record W7009611505

Examining local food procurement, adaptive capacity and resilience to environmental change in Fort Providence, Northwest Territories

2019· article· en· W7009611505 on OpenAlexaboutno aff

Bibliographic record

VenueArca (British Columbia Electronic Library Network) · 2019
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousProcurementPsychological resilienceResilience (materials science)Climate changeFood securityFood systemsAdaptive capacityCommunity resilienceTraditional knowledge
DOInot available

Abstract

fetched live from OpenAlex

Rural Indigenous communities across northern Canada are experiencing high rates of food insecurity as a result of interconnected socio-cultural, economic and environmental challenges. The loss of traditional ecological knowledge, high costs of market foods and lack of infrastructural capacity are creating multifaceted barriers for isolated, northern communities. Climate change is impacting the ability of northern Indigenous communities to acquire, access and utilize food that is culturally relevant and sustainable. This research explores local food procurement activities in the community of Fort Providence, Northwest Territories. The objective of this research was to consult with key community members to understand the detrimental effects of climate change on land-based food procurement, but also to understand the complex socio-cultural, economic and environmental challenges related to food security. This study utilizes Indigenous Methodologies to guide all aspects of the research. Evidence was collected using semi-structured interviews with Elders, land-users, and knowledgeable community members. The benefits and difficulties of engaging in land-based and alternative food procurement were key topics explored. Strategies to manage food insecurity, to promote local food procurement and to create a clear picture of community perspectives in addressing constraints to adaptation, were also considered. The results inform policies that reflect the needs of local residents, address the distinct socio-cultural and economic barriers to procure local food and support overall community resilience and adaptive capacities to environmental changes.

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), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.866
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 communication0.0000.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.022
GPT teacher head0.241
Teacher spread0.219 · 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
Published2019
Admission routes1
Has abstractyes

Explore more

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