The creation of the Global Scales for Early Development (GSED) for children aged 0–3 years: combining subject matter expert judgements with big data
Bibliographic record
Abstract
With the ratification of the Sustainable Development Goals, there is an increased emphasis on early childhood development (ECD) and well-being. The WHO led Global Scales for Early Development (GSED) project aims to provide population and programmatic level measures of ECD for 0-3 years that are valid, reliable and have psychometrically stable performance across geographical, cultural and language contexts. This paper reports on the creation of two measures: (1) the GSED Short Form (GSED-SF)-a caregiver reported measure for population-evaluation-self-administered with no training required and (2) the GSED Long Form (GSED-LF)-a directly administered/observed measure for programmatic evaluation-administered by a trained professional.We selected 807 psychometrically best-performing items using a Rasch measurement model from an ECD measurement databank which comprised 66 075 children assessed on 2211 items from 18 ECD measures in 32 countries. From 766 of these items, in-depth subject matter expert judgements were gathered to inform final item selection. Specifically collected were data on (1) conceptual matches between pairs of items originating from different measures, (2) developmental domain(s) measured by each item and (3) perceptions of feasibility of administration of each item in diverse contexts. Prototypes were finalised through a combination of psychometric performance evaluation and expert consensus to optimally identify items.We created the GSED-SF (139 items) and GSED-LF (157 items) for tablet-based and paper-based assessments, with an optimal set of items that fit the Rasch model, met subject matter expert criteria, avoided conceptual overlap, covered multiple domains of child development and were feasible to implement across diverse settings.State-of-the-art quantitative and qualitative procedures were used to select of theoretically relevant and globally feasible items representing child development for children aged 0-3 years. GSED-SF and GSED-LF will be piloted and validated in children across diverse cultural, demographic, social and language contexts for global use.
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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 | 0.187 | 0.265 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".