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Record W7161946517 · doi:10.82308/44574

Towards a transdisciplinary characterisation of the Indigenous food systems of Inuit Nunangat and Eeyou Istchee

2023· dissertation· en· W7161946517 on OpenAlexaboutno aff
Duncan Warltier

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousFood systemsFoodwaysFood securityAgricultural biodiversityFood processingFood insecurity

Abstract

fetched live from OpenAlex

Indigenous foodways are unique and contemporary economies that people rely on to feed themselves that have existed since time immemorial. These food systems are social-ecological phenomena situated at the intersection of economy and environment, food and wildlife, biodiversity and well-being, and Indigenous culture and identity. Harvesting wildlife for food is a constitutionally protected right of Indigenous Peoples within Canada. Indigenous food systems are a key contributor to the food security, nutrient intake, and the social economy in Inuit Nunangat and Eeyou Istchee. Chapter 2 combines harvest data reported in support of the James Bay and Northern Quebec Agreement (JBNQA) and food recall information from independent health surveys in the Cree region of Eeyou Istchee and the Inuit region of Nunavik to characterize the social-ecological and biocultural foundations of local Indigenous food systems across two regions and two time periods. Multivariate redundancy analysis of local food use in relation to region and survey reveals distinct regional use patterns that have remained consistent over two surveys spanning a 30-year period of accelerating socio-ecological change. Limited access and availability of healthy country and store-bought food have led to high rates of food insecurity across northern Canada, especially in Nunavut, where food insecurity affects 50 to 80% of households, which is ten times higher than the Canadian average. Because food is a fundamental need that must be replaced and cannot be exchanged, in Chapter 3, I adopt a replacement value approach, estimating what it would cost to purchase enough store-bought food to replace the protein and energy offered by reported country food harvest in Nunavut. This methodology of valuing the nutritional content of local country food harvests relative to the local cost of store-bought nutrients arrives at a $140-200 million replacement value estimate, eclipsing both the $3.5 million reported for “hunting, fishing, and trapping” activities by the Nunavut Bureau of Statistics and the Government of Nunavut’s estimated replacement value of $35 million for the country food economy. Chapter 4 applies approaches developed in the previous two chapters to harvest and food recall data from Eeyou Istchee and Nunavik to assess the numeric, value, and nutritional gaps between guaranteed levels of harvest established in the 1970’s and reported food use in the 2000’s. Estimated total use declined by nearly 50% in both regions between the 1970’s and the 2000’s. Given substantial population growth in both regions during the same period, this reduction in total use translates to a 85% decrease in reported per capita use in Nunavik and a 74% decrease in reported per capita use in Eeyou Istchee. I estimate a $20 million annual value gap between guaranteed levels of harvest established in the 1970’s and food use reported in the 2000’s. I also estimate that reported use was sufficient to satisfy 100% of the population’s protein requirements in the 1970’s but in the 2000’s provided for only 51% of recommended dietary allowances in Nunavik and 40% in Eeyou Istchee. By combining publicly available data on harvest, community population/demographics, food consumption, food prices, income, and nutritional content, this thesis offers improved methodologies for describing community and regional differences in use, based on ecological niche metrics, and for estimating the value of local foods, based on a local cost of nutrient replacement. Thesis results also emphasize that the Indigenous food systems of Inuit Nunangat and Eeyou Istchee remain a high value economy and that regional use niches remain distinct over time, despite rapid socio-ecological change

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.192
Threshold uncertainty score0.387

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0050.002
Scholarly communication0.0040.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.039
GPT teacher head0.356
Teacher spread0.317 · 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 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
Published2023
Admission routes1
Has abstractyes

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