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Record W4410436182 · doi:10.3389/fnut.2025.1521800

Unintended consequences: food prices increase in an Arctic indigenous community amidst road infrastructure development and loss of federal freight subsidy

2025· article· en· W4410436182 on OpenAlexafffundabout
Tiff‐Annie Kenny, Teddy Charmaine, Wesche Sonia, MacLean Jullian, Wolki Celina

Bibliographic record

VenueFrontiers in Nutrition · 2025
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsSaint Paul UniversityMakivik CorporationToronto Metropolitan UniversityUniversity of OttawaUniversité LavalThe Quebec Population Health Research Network
FundersFonds de Recherche du Québec - Santé
KeywordsSubsidyFood pricesAgricultural economicsArcticBusinessEconomicsFood securityGeographyAgricultureMarket economy

Abstract

fetched live from OpenAlex

Introduction: Road infrastructure development is often promoted as a strategy to reduce food insecurity in remote Arctic communities. However, the real-world impacts of such investments-particularly when tied to the withdrawal of food access supports such as the Nutrition North Canada (NNC) freight subsidy, which is provided to retailers to offset high transportation costs-remain poorly understood. This study examines the effects of the Inuvik-Tuktoyaktuk Highway opening and the concurrent loss of the NNC freight subsidy on food prices in Tuktoyaktuk, Northwest Territories. Methods: We used a quasi-experimental difference-in-differences design comparing Tuktoyaktuk (intervention community) to Aklavik (control community). Data sources included participatory food costing surveys, Northwest Territories Community Price Index data, and retailer-reported Nutrition North Canada price data. Analyses assessed trends in the Revised Northern Food Basket cost and individual product prices over time, using both aggregate and dynamic difference-in-differences models. Results: Prior to the opening of the Inuvik-Tuktoyaktuk Highway in November 2017, food prices in Tuktoyaktuk and Aklavik were closely aligned. Following the road's construction and the withdrawal of full Nutrition North Canada subsidies for Tuktoyaktuk, prices in the community began to rise. Although prices initially remained stable, a significant divergence emerged over time: by March 2022, food prices in Tuktoyaktuk were nearly 20% higher than in Aklavik. Improved surface access did not reduce the price of non-subsidized goods, as anticipated. Freight savings, if realized, were minimal or not consistently passed on to consumers. The principal driver of food price increases appears to be the loss of ongoing freight supports, particularly as neighboring Aklavik benefitted from new NNC enhancements that Tuktoyaktuk no longer accessed. Conclusion: Infrastructure alone is insufficient to improve food affordability in remote Indigenous communities. Retailer pricing discretion and market dynamics may mediate the impacts of transportation investments. To avoid exacerbating food insecurity, infrastructure projects must be accompanied by dynamic monitoring, community-driven food security strategies, and policy frameworks based on real affordability metrics rather than proxy indicators like road access. Strengthening both market and country food systems is critical to supporting Indigenous food sovereignty and resilience.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.770
Threshold uncertainty score0.457

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.021
GPT teacher head0.312
Teacher spread0.291 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations1
Published2025
Admission routes3
Has abstractyes

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