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Record W2765393528 · doi:10.1017/gmh.2017.13

Converging on child mental health – toward shared global action for child development

2017· article· en· W2765393528 on OpenAlexaff
Gary S. Belkin, Lawrence S. Wissow, Crick Lund, J. Lawrence Aber, Zulfiqar A Bhutta, Maureen M. Black, Christian Kieling, Stacey McGregor, Atıf Rahman, Chiara Servili, Susan Walker, Hirokazu Yoshikawa

Bibliographic record

VenueCambridge Prisms Global Mental Health · 2017
Typearticle
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsSickKids FoundationHospital for Sick Children
FundersWorld Health Organization
KeywordsMental healthSummitGlobal mental healthChild developmentAllianceGlobal healthCognitive developmentAction (physics)Sustainable developmentPsychologyPolitical sciencePublic relationsCognitionEconomic growthDevelopmental psychologyPsychiatryHealth careEconomicsGeography

Abstract

fetched live from OpenAlex

We are a group of researchers and clinicians with collective experience in child survival, nutrition, cognitive and social development, and treatment of common mental conditions. We join together to welcome an expanded definition of child development to guide global approaches to child health and overall social development. We call for resolve to integrate maternal and child mental health with child health, nutrition, and development services and policies, and see this as fundamental to the health and sustainable development of societies. We suggest specific steps toward achieving this objective, with associated global organizational and resource commitments. In particular, we call for a Global Planning Summit to establish a much needed Global Alliance for Child Development and Mental Health in all Policies.

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)0.055
metaresearch head score (Gemma)0.035
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: Empirical · Consensus signal: none
Teacher disagreement score0.055
Threshold uncertainty score0.292

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0550.035
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.002
Science and technology studies0.0100.038
Scholarly communication0.0180.020
Open science0.0040.066
Research integrity0.0100.030
Insufficient payload (model declined to judge)0.0150.003

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 head0.042
GPT teacher head0.360
Teacher spread0.318 · 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
GenreEmpirical

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

Citations13
Published2017
Admission routes1
Has abstractyes

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