Piecing together the Labrador Inuit food security policy puzzle in Nunatsiavut, Labrador (Canada): a scoping review
Bibliographic record
Abstract
Inuit in Canada experience greater social and economic inequities than the general Canadian population. Food security exemplifies this inequity and is a distinct determinant of Inuit health. This scoping review focuses on food security-related policies implemented in Nunatsiavut, located in Northern Labrador. The primary objective was to identify the range of existing policies that pertain to food security in Nunatsiavut. The secondary objective was to complete a directed content analysis to map each policy against the applicable dimension of food security. This scoping review followed the Johanna Briggs methodology. The search strategy included the databases: Medline (via Ovid), EMBASE (via Ovid), CINAHL, and Scopus, and a hand search of the relevant journals, conference abstracts and grey literature. This search was undertaken from April 2019 – October 2019. A content analysis mapped each policy against the applicable dimension of food security.Results: The results showed that twenty five policies were identified, spanning three levels of government, that explicitly or implicitly addressed at least one dimension of food security. Accessibility was the most frequent food security dimension identified. The Government of Canada developed 60% of policies and the Nunatsiavut Government implemented 48% of policies. Most policies focused on proximal factors for food security. Identifying distal policies for food security and understanding the impact of existing policies in Nunatsiavut remain as areas of further investigation.Ethics and Dissemination: This project was reviewed by the Nunatsiavut Government Research Advisory Committee.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.014 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".