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Record W4400479270 · doi:10.2139/ssrn.4888122

The Decline of Child Stunting in 122 Countries: A Systematic Review of Child Growth Studies Since the Nineteenth Century

2024· review· en· W4400479270 on OpenAlexaff
Eric Schneider, Juliana Jaramillo‐Echeverri, Matthew Purcell, Brian A’Hearn, Vellore Arthi, Matthias Blum, Elizabeth Brainerd, Joseph J. Capuno, Alexandra L. Cermeño, Amílcar E. Challú, Young-Jun Cho, Tim Cole, Jose Corpuz, Ewout Depauw, Federico Droller, Dieter von Fintel, Joël Floris, Gregori Galofré‐Vilà, Bernard Harris, Timothy J. Hatton, Laurent Heyberger, Tuuli Hurme, Kris Inwood, Hannaliis Jaadla, J.Y. Kok, Michal Kopczynski, Samuel Lordemus, Brian Marein, Adolfo Meisel-Roca, Stephen L. Morgan, Stefan Öberg, Kota Ogasawara, José Antonio Ortega, Nuno Palma, Anastasios Papadimitriou, Renato Pistola, Björn Quanjer, Helena Rother, Sakari Saaritsa, Ricardo D. Salvatore, Kaspar Staub, Pierre van der Eng, Evan Roberts

Bibliographic record

VenueSSRN Electronic Journal · 2024
Typereview
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsDevelopment economicsPolitical scienceEconomics

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.012
metaresearch head score (Gemma)0.041
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.995
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.041
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.005
Bibliometrics0.0160.024
Science and technology studies0.0010.002
Scholarly communication0.0030.002
Open science0.0010.003
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.016
GPT teacher head0.324
Teacher spread0.308 · 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.

Study designSystematic review
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
Published2024
Admission routes1
Has abstractno

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