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2012· article· en· W2318812122 on OpenAlexaffabout
John S. Phillips, Jowan Lee, Dawn H. Currie, Richard Parker, Brian D. Westerberg

Bibliographic record

VenueThe Hearing Journal · 2012
Typearticle
Languageen
FieldNeuroscience
TopicHearing Loss and Rehabilitation
Canadian institutionsSt. Paul's Hospital
Fundersnot available
KeywordsConversePhrasePsychologyWord (group theory)AudiologyLinguisticsMedicineMathematics

Abstract

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Figure: Histograms for the Number of Correctly Identified Words in Each Word Group and by SexWithout question, men and women differ physically, which makes it surprising that so little attention has been paid to the great number of anatomical and physiological differences that exist between their auditory systems. The majority of work in this field has relied on electrophysiological evidence for sex differences in auditory function, but gender-specific speech perception studies are far and few between.Figure: John S. PhillipsLanguage isn't a consistent vehicle for communication, and we all have firsthand experience how difficulties arise because of the different ways in which men and women converse. Men and women selectively understand language based on content, so we decided to examine whether word lists used in speech audiometry testing had a gender-specific bias. We created male- and female-specific word lists, and used speech audiometry testing to determine whether men and women identified words with that bias.Table: Median Scores and Interquartile Ranges for the Absolute Number of Words Correctly IdentifiedTwo word lists were created, each comprising words shown to be more socially relevant to men and women. The lists were validated by faculty members in the sociology department and the Centre for Women's and Gender Studies at the University of British Columbia in Vancouver. The lists were combined, yielding 53 male- and female-biased words arranged in alphabetical order. They were then recorded by a male speaker according to standard audiometric tests. Each word was preceded by the phrase, “Say the word,” and was independently levelled on a standard VU meter, with the stimulus word peaking the VU meter at 0 dB, plus or minus 1 dB. The list was then transferred alongside a 1,000-Hz sinus calibration tone for burning on a CD. AUDIOLOGIC TESTING Eighty volunteers (40 men and 40 women) were enrolled from St. Paul's Hospital in Vancouver following specific criteria: Age 19 or older with a confirmed absence of hearing loss and no reported hearing complaints. Normal tympanometric measures (=0.3 ml static compliance and tympanometric peak pressure <-100 daPa). (Contemporary Perspectives in Hearing Assessment, 2nd ed., Boston: Allyn & Bacon, 1999.) Pure tone threshold audiogram (air conduction) within the normal range (25 dBHL or better) at 250 Hz, 500 Hz, 1,000 Hz, 2,000 Hz, 4,000 Hz, and 8,000 Hz bilaterally. Symmetrical speech reception thresholds consistent with the corresponding ear's pure tone average (500 Hz, 1,000 Hz, and 2,000 Hz). The expected percentage of speech discrimination scores for normal hearing should not exceed 50 percent at a sensation level of 10 dB of speech reception thresholds. (Handbook of Clinical Audiology, 2nd ed., Baltimore: Williams and Wilkins, 2009.) Participants were presented the word list in the binaural condition at 5 dBSL to avoid ceiling effects. A total percentage of the correct score was calculated offline for the male- and female-biased words. MEN VS. WOMEN On average, men correctly identified a significantly higher proportion of male words than female words, and the women correctly identified a significantly higher proportion of female words than male words. These findings were statistically significant. (See table.) Histograms also showed the number of correctly identified words in each word group and sex. (Figure.) Women correctly identified a significantly higher proportion of female words compared to the men. However, there was no significant difference found between men and women in terms of the proportion of male words correctly identified. After adjusting for age, a significant difference remained between the male and female groups in the quantity of female words correctly identified. The anatomical and physiological differences between adult male and female auditory systems are numerous (Develop Neurophysiol 1998;14[2/3]:261), and these differences extend outside the classical definitions of gender, with variations in physiologic characteristics also being demonstrated among heterosexual, homosexual, and bisexual men and women. (J Acoust Soc Am 1999;105[4]:2403; J Assoc Res Otolaryngol 2000;1[1]:89.) The majority of work in this field has relied on electrophysiological evidence for gender differences in auditory function, but gender-specific speech perception has not been well studied. Anecdotally, gender differences in how men and women comprehend language are often remarked upon in popular culture, and the literature has found these differences in written language as well. (Hum Commun Res 2001;27[1]:121; Discourse Processes 2008;45:211.) Men score more poorly in word recognition than women, but no evidence points to whether this is because of the words or women's overall higher ability to comprehend language despite the context of the words being presented. (J Amer Acad Audiol 1998;9[3]:191.) SOCIETY AND EVOLUTION Historically, male and female behavior differences have been considered the result of social and cultural processes, but more recent research points to different cognitive abilities and psychological dispositions between the sexes resulting from biologically directed evolutionary process. (Applied Linguistic 2009;31[2]:173.) Advances in genetics and neuroscience support the role of biologism as a more appropriate approach to gender. (Applied Linguistics 2009;31[2]:173; The Blank Slate: The Modern Denial of Human Nature, New York: Viking, 2002.) Many have believed that the mind at birth is a blank slate, but evolutionary psychologists now say humans have adapted minds that are predisposed to develop in a particular way. It's this predisposition that may have equipped our ancestors with an advantage for survival. (Applied Linguistics 2009;31[2]:173; The Adapted Mind: Evolutionary Psychology and the Generation of Culture, New York: Oxford University Press, 1992.) Current evolutionary theory attempts to depart from the traditional dichotomy of nature vs. nurture. Adaptations that produce certain human characteristics may result from physical and social aspects of the early human experience interacting with biological mechanisms. (Applied Linguistics 2009;31[2]:173.) Debate is ongoing between supporters and nonsupporters of biologism. Those opposed point out flawed, unsupported generalizations or assumptions that are linguistically ill-founded. (Applied Linguistics 2009;31[2]:173.) They also argue that biologism proponents ignored cross-cultural and historical evidence and failed to acknowledge competing interpretations of data. (Applied Linguistics 2009;31[2]:173.) BIOLOGIC CONSIDERATIONS Many physiological and biochemical mechanisms may be responsible for the findings of our study, particularly the role of hormones in humans. (Obstet Gynecol 2002;99[5 Pt 1]:726; Hear Res 2009;252[1-2]:71) The auditory cortex is a particularly important focus for plasticity and this may reflect its significance for retaining the memory of particular sounds, or to functionally improve their processing. (Hear Res 2009;252[1-2]:21.) An increasing amount of evidence also supports the concept of the adult auditory system being dynamic in its ability to encode sound to accentuate behaviorally relevant signals. (Prog Neurobiol 1987;29[1]:1; J Neurophysiol 2007;98[4]:2337; Hear Res 2007;229[1-2]:54; J Neurophysiol 2008;100[3]:1160.) Studies in animals have shown that an animal's reproductive status can influence auditory neural responses and improve the processing of species-specific mating calls. (Hear Res 2009;252[1-2]:71; J Comp Physiol A Neuroethol Sens Neural Behav Physiol 2009;195[4]:341, 2002;188[11-12]:981, and 2007;193[2]:201; J Neurosci 2003;23[3]:1049; J Neurobiol 2005;65[1]:22.) DIFFERENCES IN COMPREHENSION The differences in language comprehension between men and women have immense implications for our understanding in science, from social theory and psychology to linguistics and neuroscience. The evolution of language and changes in society and culture alter which words are considered male and female. It's unclear how often or when these changes occur. It is premature to recommend altering current audiology testing based on our study alone, but speech tests partly completed at low presentation levels (threshold testing) or those where materials aren't presented optimally (monaural low redundancy testing and speech-in-noise testing) may warrant review to gauge the effects of gender-biased test materials and the participants' sex.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.843
Threshold uncertainty score0.319

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.093
GPT teacher head0.323
Teacher spread0.230 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

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Citations0
Published2012
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