Bilingualism measures in children: A critical review of content overlap, development, and pragmatic quality
Bibliographic record
Abstract
PURPOSE: A variety of assessment tools (e.g. questionnaires) measure the type and degree of bilingualism in children in both research and clinical settings. Although these tools are often assumed to evaluate the same constructs and be interchangeable, this may not be the case, as indicated by other recent reviews. This review critically evaluated existing measures of child bilingualism, focusing on item-content overlap, measure development, and pragmatic quality. METHOD: A database and manual search identified studies on child bilingualism measure development, which were then appraised using the Psychometric and Pragmatic Evidence Rating Scale and the Consensus-based Standards for the Selection of Health Measurement Instruments. RESULT: Analysis across the six identified measures showed weak between-measure content overlap, with less than one quarter of items shared on average, suggesting they assess different constructs. Ratings indicated varied pragmatic quality, especially in assessor burden (training, interpretation). Consensus-based Standards for the Selection of Health Measurement Instruments evaluations also highlighted shortcomings in measure design and development. CONCLUSION: The findings underscore the need for improved content validity and better pragmatic criteria for the clinical use of these tools. We offer recommendations for measure selection dependent on use case (e.g. setting-specific needs) and suggestions for future bilingualism measure development, prioritising a pragmatic approach.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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 teacher head, 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".