Developing the Expanded Food Security Screener and Pilot Testing It for Prioritization of Applicants to the Home-Delivered Meal Program
Bibliographic record
Abstract
Food insecurity is multidimensional and may be an outcome not only of economic need but also of inability to prepare meals and shop for food, especially in older adults. As the prevalence of waiting lists for the Older Americans Act home-delivered meal program is increasing, we expanded the 6-item US Department of Agriculture Household Food Security Survey Module, named it the Expanded Food Security Screener , and used it to develop a 5-level prioritization system to assess need for a meal based on economic access and ability to shop and cook, with or without help. We pilot-tested the tool and its prioritization system on older adults who applied for the program. The tool effectively distributes applicants into 5 different levels of need. The priority levels were generally appropriate (75%), based on follow-up assessment by programs. The tool is useful to set priorities for a waiting list and/or to identify need in the community.
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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 | 0.002 | 0.001 |
| 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".