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Record W3006754301 · doi:10.1016/s0140-6736(19)32540-1

A future for the world's children? A WHO–UNICEF–Lancet Commission

2020· review· en· W3006754301 on OpenAlexaff
Helen Clark, Awa Marie Coll‐Seck, Anshu Banerjee, Stefan Peterson, Sarah L Dalglish, Shanthi Ameratunga, Dina Balabanova, Maharaj Kishan Bhan, Zulfiqar A Bhutta, John Borrazzo, M Claeson, Tanya Doherty, Fadi El‐Jardali, Asha George, Angela Gichaga, Lu Gram, David Hipgrave, Aku Kwamie, Qingyue Meng, Raúl Mercer, Sunita Narain, Jesca Nsungwa‐Sabiiti, Adesola Olumide, David Osrin, Timothy Powell‐Jackson, Kumanan Rasanathan, Imran Rasul, Papaarangi Reid, Jennifer Requejo, Sarah Rohde, Nigel Rollins, Magali Romedenne, Harshpal Singh Sachdev, Rana Saleh, Yusra Ribhi Shawar, Jeremy Shiffman, Jonathon Simon, Peter D. Sly, Karin Stenberg, Mark Tomlinson, Rajani Ved, Anthony Costello

Bibliographic record

VenueThe Lancet · 2020
Typereview
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsSickKids FoundationCentre for Global Health ResearchHospital for Sick Children
FundersUNICEFWorld Health OrganizationBill and Melinda Gates Foundation
KeywordsCommissionPolitical scienceMedicineFamily medicineLaw

Abstract

fetched live from OpenAlex

Despite dramatic improvements in survival, nutrition, and education over recent decades, today's children face an uncertain future. Climate change, ecological degradation, migrating populations, conflict, pervasive inequalities, and predatory commercial practices threaten the health and future of children in every country. In 2015, the world's countries agreed on the Sustainable Development Goals (SDGs), yet nearly 5 years later, few countries have recorded much progress towards achieving them. This Commission presents the case for placing children, aged 0-18 years, at the centre of the SDGs: at the heart of the concept of sustainability and our shared human endeavour. Governments must harness coalitions across sectors to overcome ecological and commercial pressures to ensure children receive their rights and entitlements now and a liveable planet in the years to come.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.012
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0030.004
Open science0.0010.002
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0070.002

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.

Opus teacher head0.065
GPT teacher head0.361
Teacher spread0.296 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations1,081
Published2020
Admission routes1
Has abstractyes

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