Perspectives in childhood-onset disabilities: integrating 21st-Century concepts to expand our horizons
Bibliographic record
Abstract
PURPOSE: A powerful aphorism states: "If I hadn't believed it, I wouldn't have seen it!" This challenging notion reminds us how strongly we are influenced by prevailing ideas, and how we interpret things according to current fashions and teachings. MATERIALS AND METHODS: In this paper we present and discuss contemporary perspectives concerning childhood-onset disability and the evolving nature of how people are thinking and acting. We illustrate these ideas by reminding readers of how we have all traditionally been trained and acculturated to think about many dimensions of neurodevelopmental disability ("What?"); reflect on the impact of these ways of thinking in terms of what we have conventionally "seen" and done ("So What?"); and contrast those traditions with contemporary concepts that we believe or know impact the field ("Now What?"). RESULTS: Many of the concepts discussed here will be familiar to readers. In taking this analytically critical perspective we aim to illustrate that by weaving these individual threads together we are able to create a coherent fabric that can serve children with childhood-onset NDD, their families, service providers, the community, and policy-makers. We do not purport to offer a comprehensive view of the whole field. CONCLUSIONS: We encourage readers to consider the integration of these new ways of thinking and acting in our still-evolving field of "childhood-onset disability".
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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 | 0.022 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.011 | 0.102 |
| Scholarly communication | 0.018 | 0.023 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.007 | 0.015 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".