Editorial: Nutrition and Sustainable Development Goal 1: no poverty
Bibliographic record
Abstract
Poverty and nutritional insecurity disproportionately impact the most vulnerable people including women and children. A major problem is 'hidden hunger' (Chakona & Shackleton, 2019;Lowe, 2021) characterized by inadequate nutritional intake or nutritional deficiency affects children and adolescents disproportionately with serious implications for their development and cognitive abilities. Huansong et al's longitudinal study of nutritional deficiencies in countries with low sociodemographic index (SDI). The study aimed to provide a comprehensive estimate of the incidence of nutritional deficiency and its main subcategories at the global level, and at the national level in low-SDI countries. This study also identified high-risk populations through sex and age stratification. The findings indicated high vitamin A deficiency, and that protein-energy malnutrition contributed to the largest age-standardized DALY rate in 2019. Children ages 1-4 had the highest overall nutritional deficiency and dietary iron deficiency.The research highlighted in this Research Topic, is a timely look at an issue that demands ongoing attention. Global gains in the fight to eradicate extreme poverty, were wiped away by the Covid-19 pandemic and the economic shocks it precipitated around the world (United Nations Economic and Social Council [UNESC] 2024). During the pandemic, extreme poverty rose after many years of sustained decline and although poverty rates are generally back to pre-pandemic levels, lowincome countries continue to lag in terms of recovery. At the same time almost two and a half billion people experienced moderate to severe food insecurity in 2022 and over 60 percent of countries experienced rising food prices in the same year. Research about poverty and nutrition is therefore critical and this collection makes an important contribution to the literature in this regard. Research within an SDG framework is also important. The 2024 SDG progress assessment indicates that we are way off course in achieving the 2023 Agenda. Stagnation is rampant on many of the 135 targets and more alarmingly, there has been serious regression to below 2015 levels on seventeen percent of them (UNESC, 2024). The current trajectory is therefore, less than desirable. More research is needed to highlight this and galvanize action to turn things around in the next five and a half years.
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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 | 0.005 | 0.023 |
| Meta-epidemiology (narrow) | 0.005 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.020 | 0.028 |
| Insufficient payload (model declined to judge) | 0.028 | 0.025 |
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".