A Method for Estimating the Extent of Regional Food Self-Sufficiency and Dietary Ill Health in the Province of British Columbia, Canada
Bibliographic record
Abstract
We outline in this paper a suite of methods, and illustrate their use, to empirically determine food self-sufficiency at a relatively small (Local Health Areas) level of geography. Further we have, after identifying regions of lowest food self-sufficiency in British Columbia (BC) superimposed these on regions whose populations have relatively poor dietary ill health. Approximately one third of Local Health Areas in BC have both poor local food self-sufficiency and populations suffering from poor dietary health. These are located mainly (but not entirely) in poor under-developed rural regions of the province regions which require attention from health and food planners to improve local food security. Finally, we have demonstrated a methodological way forward to empirically determine regions in the province of BC most at risk for food insecurity. This information should be of interest to health and food planners within the province. These methods may also be useful for researchers and planners in other jurisdictions.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".