The seasonality of nutrition status in Shawi Indigenous children in the Peruvian Amazon
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
Research on the impact of seasonal and climatic variability on childhood nutritional status in the Amazon is limited. We examined how the nutritional status of Shawi children under five years changed seasonally and explored parental participation in food system activities (fishing, livestock, agriculture, hunting) as a potential influence. Using a community-based research approach with Indigenous Shawi Peoples, we conducted cross-sectional surveys in pre-harvest (July-August 2014) and post-harvest (November-December 2015) seasons. Sociodemographic data, parental participation, weight, height, and hemoglobin concentration were collected for childhood nutritional assessment. We employed bivariable linear regression to analyze associations between seasonal variations in children’s nutrition and parental food system engagement. The study took place across eleven Indigenous Shawi communities in Loreto, Peruvian Amazon. In total, 74 Shawi children and their parents were analyzed. Results indicated a decrease in childhood wasting (4.9% to 0.0%) and persistent anemia (66.2% to 66.2%), while stunting increased (39.2% to 41.9%) from pre-harvest to post-harvest. Parental participation in food activities varied seasonally, but its impact on childhood nutritional status was not statistically significant. Our findings highlight significant levels of undernutrition in Indigenous Shawi children, with slight seasonal variation. Future interventions must consider seasonal dynamics, and further exploration of parental roles in children’s diets is warranted.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it