Background Matching hearing aid output levels to prescribed targets is a component of preferred practice, yet recent normative data on appropriateness of fittings are lacking. Verification measures that assess closeness of fit-to-target include raw deviations from target, root-mean-squared-error (RMSE) deviations from target, and aided Speech Intelligibility Index (SII) values. Establishing normative ranges for these measures may help hearing professionals determine whether a patient's fit-to-targets and/or aided speech audibility is typical for his or her degree of hearing loss.
Purpose This article aims to characterize the range of fit-to-target and the range of aided SII associated with hearing aid fittings using the Desired Sensation Level version 5.0 (DSL v5-adult) prescription with adults, considering also hearing aid style, venting, and audiometric characteristics.
Research design A descriptive and correlational study of data collected from a retrospective chart review.
Results Hearing aid fittings to 281 ears were compiled. The four-frequency average deviation from target (RMSE) was within ± 5 dB of target in 77% of fittings for mid-level speech. Deviation from targets increased with hearing loss, particularly when the loss is greater than 85 dB hearing level or if the loss was steeply sloping. Venting increased the deviation from targets in the low frequencies. Aided SII values strongly correlated with the participants' hearing thresholds. Clinical ranges for RMSE and aided SII were developed for characterization of fitting outcomes.
Conclusion Fitting to DSL v5-adult targets was observed within ± 5 dB absolute deviation, or within 5 dB RMSE, on average for typical adult hearing aid fittings. Confidence intervals for deviation from target and aided SII are proposed.
This article examines the requirements of the right to a fair trial in the context of the use of machine-learning algorithms (MLAs) in judicial proceedings, with a focus on a core component of this right, the right to be heard. Though NGOs and scholars have begun to note that the right to a fair trial may be the best framework to address the challenges raised by MLAs, the actual requirements of the right in this novel context are underdeveloped. This article evaluates two normative approaches to filling this gap. The first approach, the argument from fairness, produces three broad categories of measures for ensuring fairness: measures for increasing the transparency and accountability of MLAs, measures for ensuring the participation of litigants, and measures for securing the impartiality of the human judge. However, this article argues that the argument from fairness cannot provide the necessary normative grounding for the right to a fair trial in the context of MLAs, as it collapses into the concept of ‘algorithmic fairness’. The second approach is based on the concept of human dignity as a status. The primary argument of this article is that the concept of human dignity as a status can provide better normative grounding for the right to a fair trial because it offers an account of human personhood that resists the de-humanization of data subjectification. That richer account of human personhood allows us to think of the trial not only as a vehicle for accurate outcomes, but also as a forum for the expression of human dignity.
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