Sustainable Developmental Goals interrupted: Overcoming challenges to global child and adolescent health
Bibliographic record
Abstract
Few predicted, in September 2015, when the millennium development goals (MDGs) closed and the Sustainable Development Goals (SDGs) were signed into a global compact, that we might soon face the largest global public health challenge in over a century.Not only has COVID-19 killed nearly five million people to date [1], and upended global economies, but it has also seriously impacted child health and development across the world, especially in lowand lower middle-income countries (LLMICs) [2].For the first time in living memory, over 1.6 billion children are out of school [3] and efforts on reopening schools have sparked rancorous and divisive debates.There are legitimate concerns that COVID-19 has negatively impacted progress in achieving the SDGs globally, and that urgent redirective strategies are needed before hard-earned gains from the 2000-2015 MDG period are reversed [4].In October 2020, we announced a Special Issue of PLOS Medicine devoted to themes of child and adolescent health in the context of the SDGs [5].At the time of our call for papers, the world was consumed by efforts to counter the COVID-19 pandemic, and has remained so; however, we set out to solicit papers on topics and problems that were left unaddressed at the end of the MDG period in 2015, issues that preceded the current pandemic and that are likely to persist after the current crisis abates.Our objectives were to encourage submissions pertaining to specific areas related to child development, adolescent health, and the social determinants of health.The depth and breadth of submitted articles, now reflected in the accompanying research papers, remarkably demonstrates the global significance of these issues and the multi-faceted approaches used to address them.The Special Issue represents a kaleidoscope of papers that span a range of topics and areas including child health and its drivers, including newborn health, and immunizations and other strategies to combat treatable and preventable infections; nutrition support and innovative interventions to improve infant and child survival and growth; adolescent health and outcomes, in areas such as gender equity, HIV, injuries, peer/school-based violence, and mental health; and the socio-contextual determinants of health relevant for all stages of childhood and adolescent development, including, for example, those related to conflict, environmental conditions, and the family and parenting environment.This Special Issue has contextual relevance in light of the broad spectrum of direct and collateral effects wrought by the COVID-19 pandemic on social, economic, and health-related conditions [6].These effects, direct and indirect, can be grouped broadly in relation to current
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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 | 0.009 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.042 | 0.047 |
| Insufficient payload (model declined to judge) | 0.018 | 0.009 |
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".