A multidimensional approach to measuring household food security in Taraba State, Nigeria: comparing key indicators
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
This study used household data from Taraba State, Nigeria, to explore the advantages of using a multidimensional approach to measure food and nutrition insecurity. Adaptations of three popular food security indicators were combined in a single household questionnaire to test how well the Household Food Insecurity Access Scale (HFIAS), the Dietary Diversity Score (DDS), and the Coping Strategies Index (CSI) complement each other. Sixty-nine per cent of households in the sample were classified as extremely food insecure, which means they are likely to resort to intensive but erosive coping strategies and lower dietary diversity. The three indicators powerfully complemented each other. This multidimensional food security measurement framework provided a more nuanced picture of the depth and breadth of food insecurity for local government areas in Taraba State. This approach can help Nigerian policy authorities overcome the information deficits that impede effective food and nutrition assistance interventions.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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 it