Listening Levels of Teenage iPod Users: Does Measurement Approach Matter?
Bibliographic record
Abstract
The main objective of this study was to determine the influence of background noise levels and measurement approach on user-selected listening levels (USLLs) chosen by teenaged MP3 player users. It was hypothesized that the presence of background noise would (i) increase the USLL across all measurement approaches, (ii) result in no significant USLL differences between survey reports, objective lab measures or calibrated self-report field measures, and (iii) cause no interaction effect between level of background noise and measurement approach. There were two independent variables in this study: the level of background noise and measurement approach. The first independent variable, level of background noise, had two levels: quiet and transportation noise. The second independent variable, measurement approach, had three levels: survey, objective in-ear lab measurement and calibrated self-report field measurement. The dependent variable was ear canal A-weighted sound pressure level (dBA SPL). A 2 × 3 repeated-measures ANOVA was used to determine the significance of the main and interaction effects. USLLs increased in the presence of background noise, regardless of the measurement approach used. However, the listening levels estimated by the participants using the survey and self-report field measure were significantly lower than those recorded using in-ear laboratory measurements by 9.6 and 3.3 dBA respectively. In-ear laboratory measures yielded the highest listening levels. Higher listening levels were observed in the presence of background noise for all measurement approaches. It appears that subjects' survey responses underestimate true listening levels in comparison to self-report calibrated field measures, and that both underestimate listening levels measured in the laboratory setting. More research in this area is warranted to determine whether measurement techniques can be refined and adjusted to accurately reflect real-world listening preferences.
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How this classification was reachedexpand
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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".