Illustrating Child-Specific Linking Issues Using the Child Health Questionnaire
Bibliographic record
Abstract
The publication of the International Classification of Disability, Functioning and Health Children and Youth (ICF-CY) version as a derived classification of the ICF has enabled child health and disability researchers to implement the classification into their work. There is little discussion available in the literature specifically about challenges associated with connecting ICF-CY to child health instruments. The objective of this study was to apply new reflections about linking and previous linking rules to a child-specific instrument using the Child Health Questionnaire as an example. We discovered the importance of knowledge in child health assessment as a linking requisite, issues with linking information about child behavior, the importance of clarifying the vantage point from which one is linking (e.g., child, parent, or family), and the fact that one should carefully consider the true purpose or targets of items before linking them to the ICF-CY, irrespective of the simple language used in the item. Finally, we propose the use of a new not-defined abbreviation to denote items that assess overall child development: not-defined-development (nd-dv).
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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 | 0.033 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".