Focusing on Young Children in Pediatric Psychology Research: Introduction to the Special Issue on Young Children
Bibliographic record
Abstract
Abstract This special issue focusing on pediatric psychology research in young children highlights 15 papers that focus on infants through preschoolers. Studies selected for inclusion cover a range of pediatric health conditions such as food allergy, medical trauma, injuries/traumatic brain injury, cancer, inflammatory bowel disease, pain, and sleep. The inherent challenges of researching young children are described, and studies vary in their methods for assessment and intervention; multiple studies include an observational component or developmental evaluation. Six of the studies employ diverse samples of children and/or parents and demonstrate the feasibility as well as importance of increasing our understanding of factors related to health disparities. Taken together, the special issue demonstrates the high quality of research focusing on young children. As the special issue editors, we hope this collection will spark an interest in others to focus on research with young children across pediatric populations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.025 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.009 | 0.005 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.009 | 0.017 |
| Insufficient payload (model declined to judge) | 0.012 | 0.006 |
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".