The Suitability, Readability, and Accuracy of Food Security Resources for Refugees Resettling in Australia
Bibliographic record
Abstract
OBJECTIVE: Refugees are highly susceptible to food insecurity during resettlement, a time when access to quality information is vital. This study's objective was to analyze a national sample of food security information resources' suitability, accuracy, and currency for refugee populations. METHODS: Resources were categorized and then analyzed using Suitability Assessment of Materials; Simple Measure of Gobbledygook; and currency, relevance, accuracy, authority, and purpose. RESULTS: Nearly 70% of resources were developed by government departments or agencies and topic range was limited across the 184 unique resources. Nearly all resources were suitable, accurate, and current. However, 96% were above the readability threshold recommended for refugee populations. CONCLUSIONS AND IMPLICATIONS: Resources rated well but were challenging to access in terms of readability. Extensive work is required to improve refugee food security resources using existing assets, in future resource development, and via further research.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".