Bibliographic record
Abstract
In the past few years, food security survey modules have been widely used to assess Inuit food access. However, these modules were not originally designed for use in mixed economies where both purchased and country (hunted, fished, and gathered) foods contribute to peoples’ diets. These methods have been extensively tested and modified for use in Alaska, but research conducted in the Canadian Arctic has not been rigorously evaluated. This paper examines the validity of a modified version of the commonly used USDA Household Food Security Survey Module for assessing the food security of Inuit households in Kangiqsujuaq, Nunavik. The data come from 110 household surveys that were collected as part of an extended ethnographic project in the community. Rasch modeling of the food security module results indicates that, even with modifications that make reference to country food, the module assesses only the dimension of food security related to material wealth. Household income is a contributing factor for country food access, because it is important for access to harvesting equipment; however, other factors related to country food harvesting may affect the reliability of some food security module questions. Consequently, studies that assess Inuit food access using only standard survey modules may misrepresent how Inuit experience food insecurity, which is a serious concern given the current food crisis among Inuit in Canada. Assessment tools that provide reliable and valid assessments of country food access, specifically including traditional knowledge and social support networks, need to be developed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".