Using the Language ENvironment Analysis (LENA) System to Investigate Cultural Differences in Conversational Turn Count
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose: This study investigates how the variables of culture and hearing status might influence the amount of parent-child talk families engage in throughout an average day. Method: Seventeen Vietnamese and 8 Canadian families of children with hearing loss and 17 Vietnamese and 13 Canadian families with typically hearing children between the ages of 18 and 48 months old participated in this cross-comparison design study. Each child wore a Language ENvironment Analysis system digital language processor for 3 days. An automated vocal analysis then calculated an average conversational turn count (CTC) for each participant as the variable of investigation. The CTCs for the 4 groups were compared using a Kruskal-Wallis test and a set of planned pairwise comparisons. Results: The Canadian families participated in significantly more conversational turns than the Vietnamese families. No significant difference was found between the Vietnamese or the Canadian cohorts as a function of hearing status. Conclusions: Culture, but not hearing status, influences CTCs as derived by the Language ENvironment Analysis system. Clinicians should consider how cultural communication practices might influence their suggestions for language stimulation.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it