Ear health, binaural processing, and phonological awareness in urban Australian First Nations and non-First Nations primary-school children
Bibliographic record
Abstract
While early poor ear health is known to affect later overall health and educational outcomes for children, little is known about the simultaneous influence of ear health, binaural processing, and phonological awareness. There is also limited research into the ear health of urban-residing First Nations children of primary school age. This study extends the work of [Sharma, M., Darke, A., Wigglesworth, G., & Demuth, K. (2020) Dichotic listening is associated with phonological awareness in Australian aboriginal children with otitis media: A remote community-based study. International Journal of Pediatric Otorhinolaryngology, https://doi.org/10.1016/j.ijporl.2020.110398], collecting ear health, binaural processing, and phonological awareness data from 182 urban-residing children aged 4–7 years. Children attended one of eight urban government primary schools in lower quintile socio-economic areas. Analysis investigated differences in middle ear health on the day between First Nations and non-First Nations children, and compared binaural processing with phonological awareness scores. Significant differences were found, with First Nations children experiencing a higher prevalence of middle ear disorder and poorer phonological awareness performance on the day of testing. Although binaural processing scores were similar between groups, a moderate but significant correlation between binaural processing and phonological awareness was shown for First Nations children. Results are discussed in relation to the use of aggregated geographical-based measures of socio-economic status (SES). It is suggested that the social determinants that influence social disadvantage at an individual or community level, may better explain disparities in ear health and phonological awareness. Our findings underscore the importance of targeted interventions aimed at improving First Nations children’s ear health and phonological awareness skills.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".