Food insecurity and self-reported psycho-social health status in Manitoba First Nation communities: results from the Manitoba First Nations Regional Longitudinal Health Survey 2002/2003
Bibliographic record
Abstract
The purpose of the study is to provide a descriptive analysis of food insecurity within the adult First Nations population in Manitoba. A bivariate analysis is used to determine strength of relationships between food insecurity and socio-demographic variables as well as self-reported general health and psycho-social health. This research study also includes a gender-based analysis (GBA), which allows for possible food insecurity prevalence differences between women and men The data obtained for this research study is from the second wave of the Manitoba First Nations Regional Longitudinal Health Survey (MFNRLHS, 2002/2003). Select socio-demographic variables as well as self-reported general health status, ‘life balance,’ and elements of psycho-social health, including self-reported health, ‘life balance,’ depression, intense anxiety, stress level, and domestic dispute were included. A P-value of 0.05 was used to identify significant differences. Significant results from this study include elevated food insecurity in Manitoba First Nations (37.2%). The bivariate analysis reveals that food insecurity is marginally associated with age group, with the highest food insecurity among young and middle-aged women; middle-aged men, and those with lone-parent status. Food insecurity is also significantly associated with total household income, the number of incomes per household, as well as employment versus government support over a two-year period. Food insecurity is elevated in both southern (29.4%) and northern (51.4%) regions of the province.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".