Sex-Linked Biology and Gender-Related Research Is Essential to Advancing Hearing Health
Bibliographic record
Abstract
There is robust evidence that sex (biological) and gender (behavioral/social) differences influence hearing loss risk and outcomes. These differences are noted for animals and humans-in the occurrence of hearing loss, hearing loss progression, and response to interventions. Nevertheless, many studies have not reported or disaggregated data by sex or gender. This article describes the influence of sex-linked biology (specifically sex-linked hormones) and gender on hearing and hearing interventions, including the role of sex-linked biology and gender in modifying the association between risk factors and hearing loss, and the effects of hearing loss on quality of life and functioning. Most prevalence studies indicate that hearing loss begins earlier and is more common and severe among men than women. Intrinsic sex-linked biological differences in the auditory system may account, in part, for the predominance of hearing loss in males. Sex- and gender-related differences in the effects of noise exposure or cardiovascular disease on the auditory system may help explain some of these differences in the prevalence of hearing loss. Further still, differences in hearing aid use and uptake, and the effects of hearing loss on health may also vary by sex and gender. Recognizing that sex-linked biology and gender are key determinants of hearing health, the present review concludes by emphasizing the importance of a well-developed research platform that proactively measures and assesses sex- and gender-related differences in hearing, including in understudied populations. Such research focus is necessary to advance the field of hearing science and benefit all members of society.
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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 | 0.018 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 0.003 |
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".