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Proceedings of the First Workshop on Gender Bias in Natural Language Processing
16 references·2 citing·34 second hop
Proceedings of the First Workshop on Gender Bias in Natural Language Processing (2019)Proceedings of the First Workshop on Gend…Word embeddings quantify 100 years of gender and ethnic stereotypes (2018)Word embeddings quantify 100 …Mitigating Unwanted Biases with Adversarial Learning (2018)Mitigating Unwanted Biases wi…Measuring and Mitigating Unintended Bias in Text Classification (2018)Measuring and Mitigating Unin…Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification (2018)Gender Shades: Intersectional…Semantics derived automatically from language corpora contain human-like biases (2017)Semantics derived automatical…Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraints (2017)Men Also Like Shopping: Reduc…Equality of Opportunity in Supervised Learning (2016)Equality of Opportunity in Su…Big Data's Disparate Impact (2014)Big Data's Disparate ImpactDiscrimination in online ad delivery (2013)Discrimination in online ad d…Backlash effects for disconfirming gender stereotypes in organizations (2008)Backlash effects for disconfi…Gender-Stereotypic Images of Occupations Correspond to the Sex Segregation of Employment (1999)Gender-Stereotypic Images of …Measuring individual differences in implicit cognition: The implicit association test. (1998)Measuring individual differen…Measuring individual differences in implicit cognition: The implicit association test. (1998)Measuring individual differen…Contextual correlates of semantic similarity (1991)Contextual correlates of sema…Gender stereotypes stem from the distribution of women and men into social roles. (1984)Gender stereotypes stem from …Distributional Structure (1954)Distributional StructureBeyond rating scales: With targeted evaluation, large language models are poised for psychological assessment (2023)Beyond rating scales: With ta…How to measure gender bias in machine translation: Real-world oriented machine translators, multiple reference points (2021)How to measure gender bias in…Mind, Language and Reality (1975)The role of theories in conceptual coherence. (1985)The meaning of ‘meaning’ (2010)How to do Linguistics with R (2015)CAPTION-ing the situation: A lexically-derived taxonomy of psychological situation characteristics. (2016)“I’m Not Mopping the Floors, I’m Putting a Man on the Moon”: How NASA Leaders Enhanced the Meaningfulness of Work by Changing the Meaning of Work (2017)The Theory of Social and Economic Organization. (1948)Coefficient Alpha and the Internal Structure of Tests (1951)Gender and leadership style: A meta-analysis. (1990)Gender and the evaluation of leaders: A meta-analysis. (1992)Evolutionary origins of stigmatization: The functions of social exclusion. (2001)Exchange and Power in Social Life (2017)Attitudinal effects of mere exposure. (1968)Self-schemata and processing information about the self. (1977)Implicit social cognition: Attitudes, self-esteem, and stereotypes. (1995)Role congruity theory of prejudice toward female leaders. (2002)Understanding and using the Implicit Association Test: I. An improved scoring algorithm. (2003)Understanding and using the Implicit Association Test: III. Meta-analysis of predictive validity. (2009)Fairness through awareness (2012)Fair Prediction with Disparate Impact: A Study of Bias in Recidivism Prediction Instruments (2017)A Survey on Bias and Fairness in Machine Learning (2021)ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope (2023)Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings (2016)Ensuring Fairness in Machine Learning to Advance Health Equity (2018)Language (Technology) is Power: A Critical Survey of “Bias” in NLP (2020)Addressing bias in big data and AI for health care: A call for open science (2021)The Ethics of AI Ethics: An Evaluation of Guidelines (2020)Theories of Lexical Semantics (2009)Diachronic Word Embeddings Reveal Statistical Laws of Semantic Change (2016)Measuring Corporate Culture Using Machine Learning (2020)Dissecting racial bias in an algorithm used to manage the health of populations (2019)How the machine ‘thinks’: Understanding opacity in machine learning algorithms (2016)The ethics of algorithms: Mapping the debate (2016)The benefits of being present: Mindfulness and its role in psychological well-being. (2003)
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References

  • 1998Measuring individual differences in implicit cognition: The implicit association test.9,206 cited
  • 1998Measuring individual differences in implicit cognition: The implicit association test.8,274 cited
  • 1954Distributional Structure4,806 cited
  • 2018Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification3,509 cited
  • 2014Big Data's Disparate Impact3,046 cited
  • 2017Semantics derived automatically from language corpora contain human-like biases2,845 cited
  • 2016Equality of Opportunity in Supervised Learning2,535 cited
  • 1984Gender stereotypes stem from the distribution of women and men into social roles.1,841 cited
  • 1991Contextual correlates of semantic similarity1,599 cited
  • 2018Mitigating Unwanted Biases with Adversarial Learning1,387 cited
  • 2018Word embeddings quantify 100 years of gender and ethnic stereotypes1,064 cited
  • 1999Gender-Stereotypic Images of Occupations Correspond to the Sex Segregation of Employment867 cited
  • 2017Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraints829 cited
  • 2008Backlash effects for disconfirming gender stereotypes in organizations774 cited
  • 2013Discrimination in online ad delivery

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751 cited
  • 2018Measuring and Mitigating Unintended Bias in Text Classification668 cited
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    • 2023Beyond rating scales: With targeted evaluation, large language models are poised for psychological assessment76 cited
    • 2021How to measure gender bias in machine translation: Real-world oriented machine translators, multiple reference points20 cited