scholarly journals Child Poverty, Demographic Transition and Gender Bias in Education in India: Household Data Analysis (1993-94 and 2004-05)

2011 ◽  
Author(s):  
Dharam Pal Chaudhri ◽  
Raghbendra Jha
Keyword(s):  
Data Analysis ◽  
Gender Bias ◽  
Demographic Transition ◽  
Child Poverty ◽  
Household Data ◽  
Education In India ◽  
And Gender

scholarly journals Representasi Relasi Jender dalam Pemakaian Diksi pada Novel “Perempuan Berkalung Sorban” Karya Abidah El Khalieki

2017 ◽  
Vol 12 (1) ◽  
pp. 55
Author(s):  
Suyanto Suyanto ◽  
Mujid F Amin
Keyword(s):  
Data Analysis ◽  
Gender Bias ◽  
Gender Inequality ◽  
Public Spaces ◽  
Material Object ◽  
The Novel ◽  
Data Display ◽  
Gender Relation ◽  
Women And Gender ◽  
And Gender

This study aims to explain the use of diction which reflects gender relation in four aspects namely leniency, authority, mobility, and attitude. The material object of this research is Abidah El-Khalieki's novel Women to Wear headdress. Data collection using the method refer and note technique. Data analysis was used data reduction, data display, data verification, interpretation and theoretical meanings, and result conclusions. In the aspect of leniency shows the existence of allowances or the opportunity of women to indicate its existence in public spaces. Gender inequality is demonstrated by diction that States that in the wedding were not involved to define himself. Diction in the form of metaphor is dominated by metaphor symbolic stating that the woman just jewelry for her husband. Diction in attitude more widely used to describe the nature of stereotypes of women and gender bias. In general the diction in the novel more gender-equitable tend to PBS. Usage of diction are generally gender bias for comparison that finally found the gender-sensitive nature of the resolution. As for the use in the novel PBS dominated by symbolic figurative.

scholarly journals Questioning Racial and Gender Bias in AI-based Recommendations: Do Espoused National Cultural Values Matter?

2021 ◽  
Author(s):  
Manjul Gupta ◽  
Carlos M. Parra ◽  
Denis Dennehy
Keyword(s):  
United States ◽  
Cultural Values ◽  
Gender Bias ◽  
The United States ◽  
Compelling Evidence ◽  
Research Attention ◽  
Academic Literature ◽  
Gender Biases ◽  
Significant Research ◽  
And Gender

AbstractOne realm of AI, recommender systems have attracted significant research attention due to concerns about its devastating effects to society’s most vulnerable and marginalised communities. Both media press and academic literature provide compelling evidence that AI-based recommendations help to perpetuate and exacerbate racial and gender biases. Yet, there is limited knowledge about the extent to which individuals might question AI-based recommendations when perceived as biased. To address this gap in knowledge, we investigate the effects of espoused national cultural values on AI questionability, by examining how individuals might question AI-based recommendations due to perceived racial or gender bias. Data collected from 387 survey respondents in the United States indicate that individuals with espoused national cultural values associated to collectivism, masculinity and uncertainty avoidance are more likely to question biased AI-based recommendations. This study advances understanding of how cultural values affect AI questionability due to perceived bias and it contributes to current academic discourse about the need to hold AI accountable.

scholarly journals Peer review and gender bias: A study on 145 scholarly journals

2021 ◽  
Vol 7 (2) ◽  
pp. eabd0299
Author(s):  
Flaminio Squazzoni ◽  
Giangiacomo Bravo ◽  
Mike Farjam ◽  
Ana Marusic ◽  
Bahar Mehmani ◽  
...  
Keyword(s):  
Peer Review ◽  
Gender Bias ◽  
Gender Gap ◽  
Gender Diversity ◽  
Scholarly Journals ◽  
Publication Rates ◽  
And Gender ◽  
Editorial Decisions ◽  
Selection Of

Scholarly journals are often blamed for a gender gap in publication rates, but it is unclear whether peer review and editorial processes contribute to it. This article examines gender bias in peer review with data for 145 journals in various fields of research, including about 1.7 million authors and 740,000 referees. We reconstructed three possible sources of bias, i.e., the editorial selection of referees, referee recommendations, and editorial decisions, and examined all their possible relationships. Results showed that manuscripts written by women as solo authors or coauthored by women were treated even more favorably by referees and editors. Although there were some differences between fields of research, our findings suggest that peer review and editorial processes do not penalize manuscripts by women. However, increasing gender diversity in editorial teams and referee pools could help journals inform potential authors about their attention to these factors and so stimulate participation by women.

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