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Grep-BiasIR: A Dataset for Investigating Gender Representation Bias in Information Retrieval Results
6 references·1 citing·35 second hop
Grep-BiasIR: A Dataset for Investigating Gender Representation Bias in Information Retrieval Results (2023)Grep-BiasIR: A Dataset for Investigating …Gender stereotype reinforcement: Measuring the gender bias conveyed by ranking algorithms (2020)Gender stereotype reinforceme…The future of sex and gender in psychology: Five challenges to the gender binary. (2018)The future of sex and gender …Investigating the Impact of Gender on Rank in Resume Search Engines (2018)Investigating the Impact of G…Competent Men and Warm Women (2017)Competent Men and Warm WomenUnequal Representation and Gender Stereotypes in Image Search Results for Occupations (2015)Unequal Representation and Ge…Bias in computer systems (1996)Bias in computer systemsTrapped in the search box: An examination of algorithmic bias in search engine autocomplete predictions (2023)Trapped in the search box: An…The Evolution of the Labor Market for Medical Interns and Residents: A Case Study in Game Theory (1984)Data Statements for Natural Language Processing: Toward Mitigating System Bias and Enabling Better Science (2018)Improving Fairness in Machine Learning Systems (2019)Algorithmic Bias in Education (2021)Stereotype Threat and Women's Math Performance (1999)Gender and the Career Choice Process: The Role of Biased Self‐Assessments (2001)Balanced Datasets Are Not Enough: Estimating and Mitigating Gender Bias in Deep Image Representations (2019)Fairness-Aware Ranking in Search & Recommendation Systems with Application to LinkedIn Talent Search (2019)Ethics and discrimination in artificial intelligence-enabled recruitment practices (2023)A model of (often mixed) stereotype content: Competence and warmth respectively follow from perceived status and competition. (2002)Role congruity theory of prejudice toward female leaders. (2002)Trust in Automation: Designing for Appropriate Reliance (2004)Female librarians and male computer programmers? Gender bias in occupational images on digital media platforms (2020)I agree with the decision, but they didn't deserve this (2021)Social Biases through the Text-to-Image Generation Lens (2023)Are Emily and Greg More Employable Than Lakisha and Jamal? A Field Experiment on Labor Market Discrimination (2004)Fairness through awareness (2012)Big Data's Disparate Impact (2014)The fallacy of inscrutability (2018)Measuring Misinformation in Video Search Platforms: An Audit Study on YouTube (2020)Building and Auditing Fair Algorithms (2021)Sex differences in human mate preferences: Evolutionary hypotheses tested in 37 cultures (1989)Gender Trouble: Feminism and the Subversion of Identity (1991)Masculine defaults: Identifying and mitigating hidden cultural biases. (2020)What is gender, anyway: a review of the options for operationalising gender (2020)Introduction to Meta‐Analysis (2021)On the Opportunities and Risks of Foundation Models (2021)Availability: A heuristic for judging frequency and probability (1973)Measuring individual differences in implicit cognition: The implicit association test. (1998)Measuring individual differences in implicit cognition: The implicit association test. (1998)Measuring Fairness Under Unawareness of Sensitive Attributes: A Quantification-Based Approach (2023)Utilizing data driven methods to identify gender bias in LinkedIn profiles (2023)The Relevance of Algorithms (2014)Algorithms of Oppression (2018)A Survey on Bias and Fairness in Machine Learning (2021)
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References

  • 1996Bias in computer systems1,203 cited
  • 2018The future of sex and gender in psychology: Five challenges to the gender binary.993 cited
  • 2015Unequal Representation and Gender Stereotypes in Image Search Results for Occupations509 cited
  • 2018Investigating the Impact of Gender on Rank in Resume Search Engines155 cited
  • 2017Competent Men and Warm Women127 cited
  • 2020Gender stereotype reinforcement: Measuring the gender bias conveyed by ranking algorithms52 cited

Cited by

  • 2023Trapped in the search box: An examination of algorithmic bias in search engine autocomplete predictions18 cited

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