The Four Domain Food Insecurity Scale (4D-FIS): development and evaluation of a complementary food insecurity measure
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The U.S. Department of Agriculture (USDA) Food Security Survey Module (FSSM) is a valuable tool for measuring food insecurity, but it has limitations for capturing experiences of less severe food insecurity. To develop and test the Four Domain Food Insecurity Scale (4D-FIS), a complementary measure designed to assess all four domains of the food access dimension of food insecurity (quantitative, qualitative, psychological, and social).Low-income Black, Latina, and White women (n = 109) completed semi-structured (qualitative) and structured (quantitative) interviews. Interviewers separately administered two food insecurity scales, including the 4D-FIS and the USDA FSSM adult scale. A scoring protocol was developed to determine food insecurity status with the 4D-FIS. Analyses included a confirmatory factor analysis to examine the hypothesized structure of the 4D-FIS and an initial evaluation of reliability and validity. A four-factor model fit the data reasonably well as judged with fit indices. Results showed relatively high factor loadings and inter-factor correlations indicated that factors were distinct. Cronbach's alpha (ɑ) for the overall scale was 0.90 (subscale ɑ ranged from 0.69 to 0.91) and provided support for the scale's internal consistency reliability. There was fair overall agreement between the 4D-FIS and USDA FSSM adult scale, but agreement varied by category. Findings provide preliminary support for the 4D-FIS as a complementary measure of food insecurity, with implications for researchers, practitioners, and policymakers working in U.S. communities.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 it