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Record W4392456612 · doi:10.21203/rs.3.rs-3718721/v1

Feasibility and acceptability of implementing the Global Scales for Early Development (GSED) package for children 0-3 years across three countries.

2024· preprint· en· W4392456612 on OpenAlexaff
Ambreen Nizar Merchant, Raghbir Kaur, Gareth McCray, Vanessa Cavallera, Ann M. Weber, Melissa Gladstone, Magdalana Janus, Muhammad Imran Nisar, Patricia Kariger, Sunil Sazawal, Arup Dutta, Yunting Zhang, Mariana Pacífico Mercadante, Arsène Zongo, Yvonne Schönbeck, Tarun Dua, Iris Eekhout, Fahmida Tofail, Maureen M. Black, Abdullah H Baqui, Dana Charles McCoy, Salahuddin Ahmed, Farzana Begum, Romuald Anago, Alexandra Brentani, Fan Jiang, Symone Detmar, Michelle Perez Maillard, Marcus Waldman, Stef van Buuren, Abbie Raikes, Katelyn Hepworth, Marta Rubio Codina, Shirina Akhtar, Fyezah Jehan, Rasheda Khanum, Hassan Naqvi, Abrarul Haque Asif, Junaid Mehmood, Sidra Afzal, Gillian Lancaster

Bibliographic record

VenueResearch Square · 2024
Typepreprint
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPsychology

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)0.070
metaresearch head score (Gemma)0.099
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.070
Threshold uncertainty score0.369

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0700.099
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.092
GPT teacher head0.473
Teacher spread0.381 · 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 designObservational
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

Citations2
Published2024
Admission routes1
Has abstractno

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