Dynamics of Gender Bias within Computer Science.

This article explores the issue of gender bias in computer science, specifically focusing on women's participation in research authorship within the ACM Special Interest Groups (SIGs). The data reveals that while there has been progress since 2009, women's participation still lags behind levels seen...

Full description

Bibliographic Details
Published in:Information & Culture Vol. 59; no. 2; pp. 161 - 182
Main Author: Misa, Thomas J.
Format: Article
Published: University of Texas Press 2024
Subjects:
Online Access:View this record in EBSCOhost
fields @attributes:
  recordID: 1
pdfLink:
plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=178282416&site=ehost-live
header:
  @attributes:
    shortDbName: hlh
    uiTerm: 178282416
    longDbName: Humanities International Complete
    uiTag: AN
  controlInfo:
    bkinfo:
    jinfo:
      jid:
        21648034
        FB2C
      jtl: Information & Culture
      issn: 21648034
      maglogo: N
    pubinfo:
      dt: 2024
      vid: 59
      iid: 2
      pid: 519
      pub: University of Texas Press
    artinfo:
      ui:
        178282416
        10.7560/ic59203
      ppf: 161
      ppct: 21
      formats:
        fmt:
          – @attributes:
              type: T
          – @attributes:
              type: P
              size: 616KB
      tig:
        atl: Dynamics of Gender Bias within Computer Science.
      aug:
        au: Misa, Thomas J.
      su:
        Gender stereotypes
        Computer science
        Sex discrimination
        Occupational segregation
        Scientific computing
        Women's empowerment
        Abstraction (Computer science)
        Computer science conferences
        Computer vision
      sug:
        subj:
          Gender stereotypes
          Computer science
          Sex discrimination
          Occupational segregation
          Scientific computing
          Women's empowerment
          Abstraction (Computer science)
          Computer science conferences
          Computer vision
      ab: This article explores the issue of gender bias in computer science, specifically focusing on women's participation in research authorship within the ACM Special Interest Groups (SIGs). The data reveals that while there has been progress since 2009, women's participation still lags behind levels seen in the mid-1980s. The article emphasizes the importance of understanding the nuances of gender bias within different subfields of computer science. It also highlights the limitations of using gender-identification software and the challenges of determining gender for non-American authors. The article suggests that efforts should be directed towards retaining women in SIGs with higher levels of women's authorship and promoting culture change in SIGs with lower levels. Further research is needed to gain a deeper understanding of gender bias and the specific cultures within different SIGs.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
    refInfo:
    copyright:
      @attributes:
        flag: Y
      custom: Copyright of Information & Culture is the property of University of Texas Press and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use.
      item: Information & Culture
      holder: University of Texas Press
      dt:
        @attributes:
          year: 2024
    holdings:
      @attributes:
        islocal: N