Validación de escalas de seguridad alimentaria y de apoyo social en una población afro-colombiana: aplicación en el estudio de prevalencia del estado nutricional en niños de 6 a 18 meses
Bibliographic record
Abstract
We conducted a cross-sectional study on 193 mothers of children 6 to 18 months of age in an African-Colombian community, with the objectives: (1) to adapt and validate the Community Childhood Hunger Identification Project scale, the DUKE-UNC-11 social support scale, and the Quebec Longitudinal Study of Child Development (QLSCD) partner support scale, and (2) to identify any existent relationship between nutritional status in infancy and both food insecurity and social support. We determined construct validity using factor analysis and theoretical models-based non-parametric correlations. Length-for-age and weight-for-length Z-results were calculated. Factor analyses reduced the hunger scale to one factor, the DUKE-UNC-11 scale to two factors, and the QLSCD scale to one factor. The Cronbach's alpha test ranged between 0.70 and 0.90. Both food insecurity and social support scales were correlated with mother's social conditions, and social support was positively associated with social networks and mother's self-perceived health status. Food insecurity, emotional-social support, and partner's negative support were associated with lower height-to-age and therefore a higher ratio of chronic malnutrition. The study supports the appropriateness of the instruments to measure the expressed concepts.
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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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".