Risk for Speech Disorder Associated With Early Recurrent Otitis Media With Effusion
Bibliographic record
Abstract
The goals of this two-part series on children with histories of early recurrent otitis media with effusion (OME) were to assess the risk for speech disorder with and without hearing loss and to develop a preliminary descriptive-explanatory model for the findings. Recently available speech analysis programs, lifespan reference data, and statistical techniques were implemented with three cohorts of children with OME and their controls originally assessed in the 1980s: 35 typically developing 3-year-old children followed since infancy in a university-affiliated pediatrics clinic, 50 typically developing children of Native American background followed since infancy in a tribal health clinic, and (in the second paper) 70 children followed prospectively from 2 months of age to 3 years of age and older. Dependent variables included information from a suite of 10 metrics of speech production (Shriberg, Austin, Lewis, McSweeny, & Wilson, 1997a, 1 997b). Constraints on available sociodemographic and hearing status information limit generalizations from the comparative findings for each database, particularly data from the two retrospective studies. The present paper reports findings from risk analysis of conversational speech data from the first two cohorts, each of which included retrospective study of children for whom data on hearing loss were not available. Early recurrent OME was not associated with increased risk for speech disorder in the pediatrics sample but was associated with approximately 4.6 (CI = 1.10-20.20) increased risk for subclinical or clinical speech disorder in the children of Native American background. Discussion underscores the appropriateness of multifactorial risk models for this subtype of child speech disorder.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 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".