Naming and Categorization in Healthy Participants: Crowded Domains and Blurred Effects of Gender

Author:

Moreno-Martínez Francisco Javier,Moratilla-Pérez Iván

Abstract

AbstractThe study of category-specific effects has produced compelling insights into the structure, organization and functioning of cognitive processes. According to some accounts, the greater intra-category structural similarity for living things (LT) contributes to faster access to superordinate pictorial information, making LT easier to classify than structurally dissimilar items (i.e., nonliving things: NLT). Conversely, LT would be harder to name than NLT, as they must compete with within-domain structurally similar items in order to be properly discriminated. Additionally, it has been reported that men perform better with NLT than women, whereas women surpass men with LT but the reasons for this remain unclear. In the current study, we explored both the visual crowding hypothesis and the effects of gender by testing the performance of 40 healthy participants in classification and naming tasks. Analyses revealed that LT were classified significantly faster than NLT (ηp2= .11), but named significantly slower (ηp2= .25). Interestingly, the same results persisted after removing atypical categories that are known to distort the interpretation of data from the analyses. Moreover, we did not find the expected effects of gender. Men were more accurate than women naming NLT (ηp2= .13), and women did not surpass men in any task.

Publisher

Cambridge University Press (CUP)

Subject

Linguistics and Language,General Psychology,Language and Linguistics

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3