mlsanityData to 7 Oct 2026

Theories of "Gender" in NLP Bias Research

arXiv 2205.02526 ↗First posted 5 May 2022cs.CLcited by 62

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Abstract (arXiv)

The rise of concern around Natural Language Processing (NLP) technologies containing and perpetuating social biases has led to a rich and rapidly growing area of research. Gender bias is one of the central biases being analyzed, but to date there is no comprehensive analysis of how "gender" is theorized in the field. We survey nearly 200 articles concerning gender bias in NLP to discover how the field conceptualizes gender both explicitly (e.g. through definitions of terms) and implicitly (e.g. through how gender is operationalized in practice). In order to get a better idea of emerging trajectories of thought, we split these articles into two sections by time. We find that the majority of the articles do not make their theorization of gender explicit, even if they clearly define "bias." Almost none use a model of gender that is intersectional or inclusive of nonbinary genders; and many conflate sex characteristics, social gender, and linguistic gender in ways that disregard the existence and experience of trans, nonbinary, and intersex people. There is an increase between the two time-sections in statements acknowledging that gender is a complicated reality, however, very few articles manage to put this acknowledgment into practice. In addition to analyzing these findings, we provide specific recommendations to facilitate interdisciplinary work, and to incorporate theory and methodology from Gender Studies. Our hope is that this will produce more inclusive gender bias research in NLP.

Key facts. Cited by 62 papers in the map (data through 7 Oct 2026). Builds on 119 of its 211 references that are in the map. First posted on arXiv 5 May 2022.

Builds on

119 of 211 references.

References · 119

  1. 2019A Survey on Bias and Fairness in Machine Learningcited by 1,911
  2. 2016Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddingscited by 1,304
  3. 2020Language (Technology) is Power: A Critical Survey of "Bias" in NLPcited by 951
  4. 2020StereoSet: Measuring stereotypical bias in pretrained language modelscited by 911
  5. 2016Semantics derived automatically from language corpora contain human-like biasescited by 894
  6. 2018Mitigating Unwanted Biases with Adversarial Learningcited by 663
  7. 2018Gender Bias in Coreference Resolution: Evaluation and Debiasing Methodscited by 657
  8. 2019The Woman Worked as a Babysitter: On Biases in Language Generationcited by 540
  9. 2020Null It Out: Guarding Protected Attributes by Iterative Nullspace Projectioncited by 442
  10. 2018Gender Bias in Coreference Resolutioncited by 438
  11. 2017Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraintscited by 420
  12. 2019On Measuring Social Biases in Sentence Encoderscited by 397
38 more
  1. 2019Social Bias Frames: Reasoning about Social and Power Implications of Languagecited by 377
  2. 2019Bias in Bios: A Case Study of Semantic Representation Bias in a High-Stakes Settingcited by 346
  3. 2019Mitigating Gender Bias in Natural Language Processing: Literature Reviewcited by 287
  4. 2019Measuring Bias in Contextualized Word Representationscited by 275
  5. 2019Lipstick on a Pig: Debiasing Methods Cover up Systematic Gender Biases in Word Embeddings But do not Remove Themcited by 268
  6. 2017Word Embeddings Quantify 100 Years of Gender and Ethnic Stereotypescited by 251
  7. 2019Evaluating Gender Bias in Machine Translationcited by 247
  8. 2018Women also Snowboard: Overcoming Bias in Captioning Modelscited by 236
  9. 2018Examining Gender and Race Bias in Two Hundred Sentiment Analysis Systemscited by 234
  10. 2019Identifying and Reducing Gender Bias in Word-Level Language Modelscited by 214
  11. 2018Gender Bias in Neural Natural Language Processingcited by 210
  12. 2019Gender Bias in Contextualized Word Embeddingscited by 203
  13. 2019Counterfactual Data Augmentation for Mitigating Gender Stereotypes in Languages with Rich Morphologycited by 200
  14. 2020Causal Mediation Analysis for Interpreting Neural NLP: The Case of Gender Biascited by 183
  15. 2020Towards Debiasing Sentence Representationscited by 170
  16. 2018Learning Gender-Neutral Word Embeddingscited by 169
  17. 2018Reducing Gender Bias in Abusive Language Detectioncited by 152
  18. 2019Queens are Powerful too: Mitigating Gender Bias in Dialogue Generationcited by 152
  19. 2019Reducing Sentiment Bias in Language Models via Counterfactual Evaluationcited by 148
  20. 2020Intrinsic Bias Metrics Do Not Correlate with Application Biascited by 148
  21. 2019Black is to Criminal as Caucasian is to Police: Detecting and Removing Multiclass Bias in Word Embeddingscited by 146
  22. 2019Assessing Social and Intersectional Biases in Contextualized Word Representationscited by 134
  23. 2021Harms of Gender Exclusivity and Challenges in Non-Binary Representation in Language Technologiescited by 128
  24. 2018Assessing Gender Bias in Machine Translation -- A Case Study with Google Translatecited by 121
  25. 2021Gender Bias in Machine Translationcited by 116
  26. 2019On Measuring and Mitigating Biased Inferences of Word Embeddingscited by 112
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  28. 2019It's All in the Name: Mitigating Gender Bias with Name-Based Counterfactual Data Substitutioncited by 102
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  30. 2019Evaluating the Underlying Gender Bias in Contextualized Word Embeddingscited by 94
  31. 2018Understanding the Origins of Bias in Word Embeddingscited by 90
  32. 2019Does Gender Matter? Towards Fairness in Dialogue Systemscited by 89
  33. 2020Reducing Gender Bias in Neural Machine Translation as a Domain Adaptation Problemcited by 86
  34. 2019Toward Gender-Inclusive Coreference Resolutioncited by 84
  35. 2020Unmasking Contextual Stereotypes: Measuring and Mitigating BERT's Gender Biascited by 82
  36. 2020Multi-Dimensional Gender Bias Classificationcited by 80
  37. 2020Hurtful Words: Quantifying Biases in Clinical Contextual Word Embeddingscited by 79
  38. 2021Machine Translationese: Effects of Algorithmic Bias on Linguistic Complexity in Machine Translationcited by 70

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 1; 2023: 17; 2024: 23; 2025: 13; 2026: 8.

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  1. 2023Bias and Fairness in Large Language Models: A Surveycited by 626
  2. 2022"I'm sorry to hear that": Finding New Biases in Language Models with a Holistic Descriptor Datasetcited by 160
  3. 2023WinoQueer: A Community-in-the-Loop Benchmark for Anti-LGBTQ+ Bias in Large Language Modelscited by 42
  4. 2023Beyond the Safeguards: Exploring the Security Risks of ChatGPTcited by 36
  5. 2024Decoding Biases: Automated Methods and LLM Judges for Gender Bias Detection in Language Modelscited by 33
  6. 2023Vision-Language Models Performing Zero-Shot Tasks Exhibit Gender-based Disparitiescited by 31
  7. 2023Sociodemographic Bias in Language Models: A Survey and Forward Pathcited by 27
  8. 2023NBIAS: A Natural Language Processing Framework for Bias Identification in Textcited by 23
  9. 2024Stop! In the Name of Flaws: Disentangling Personal Names and Sociodemographic Attributes in NLPcited by 22
  10. 2024The Colorful Future of LLMs: Evaluating and Improving LLMs as Emotional Supporters for Queer Youthcited by 20
  11. 2025Position is Power: System Prompts as a Mechanism of Bias in Large Language Models (LLMs)cited by 19
  12. 2024Akal Badi ya Bias: An Exploratory Study of Gender Bias in Hindi Language Technologycited by 17
38 more
  1. 2023Fairness in Language Models Beyond English: Gaps and Challengescited by 16
  2. 2024From 'Showgirls' to 'Performers': Fine-tuning with Gender-inclusive Language for Bias Reduction in LLMscited by 15
  3. 2024Harmful Speech Detection by Language Models Exhibits Gender-Queer Dialect Biascited by 14
  4. 2024Identifying and Mitigating Social Bias Knowledge in Language Modelscited by 13
  5. 2023A Security Risk Taxonomy for Prompt-Based Interaction With Large Language Modelscited by 12
  6. 2023Tackling Bias in Pre-trained Language Models: Current Trends and Under-represented Societiescited by 11
  7. 2024FairDeDup: Detecting and Mitigating Vision-Language Fairness Disparities in Semantic Dataset Deduplicationcited by 11
  8. 2023iLab at SemEval-2023 Task 11 Le-Wi-Di: Modelling Disagreement or Modelling Perspectives?cited by 10
  9. 2024How Are LLMs Mitigating Stereotyping Harms? Learning from Search Engine Studiescited by 9
  10. 2024WinoPron: Revisiting English Winogender Schemas for Consistency, Coverage, and Grammatical Casecited by 9
  11. 2023In-Depth Look at Word Filling Societal Bias Measurescited by 8
  12. 2025Provocations from the Humanities for Generative AI Researchcited by 8
  13. 2025Unsupervised Concept Vector Extraction for Bias Control in LLMscited by 7
  14. 2025Rigor in AI: Doing Rigorous AI Work Requires a Broader, Responsible AI-Informed Conception of Rigorcited by 7
  15. 2023Gender-Inclusive Grammatical Error Correction through Augmentationcited by 6
  16. 2024Data Feminism for AIcited by 6
  17. 2023Towards Reliable Assessments of Demographic Disparities in Multi-Label Image Classifierscited by 5
  18. 2024What is Fair? Defining Fairness in Machine Learning for Healthcited by 5
  19. 2024QueerBench: Quantifying Discrimination in Language Models Toward Queer Identitiescited by 5
  20. 2024Do language models practice what they preach? Examining language ideologies about gendered language reform encoded in LLMscited by 5
  21. 2025Identities are not Interchangeable: The Problem of Overgeneralization in Fair Machine Learningcited by 5
  22. 2023Unlocking Bias Detection: Leveraging Transformer-Based Models for Content Analysiscited by 4
  23. 2024RuBia: A Russian Language Bias Detection Datasetcited by 4
  24. 2025LLMs Reproduce Stereotypes of Sexual and Gender Minoritiescited by 4
  25. 2023Challenges and Solutions in AI for Allcited by 3
  26. 2026Different Demographic Cues Yield Inconsistent Conclusions About LLM Personalization and Biascited by 3
  27. 2024Identifying Fairness Issues in Automatically Generated Testing Contentcited by 2
  28. 2024Transforming Dutch: Debiasing Dutch Coreference Resolution Systems for Non-binary Pronounscited by 2
  29. 2024Is Generative AI the Next Tactical Cyber Weapon For Threat Actors? Unforeseen Implications of AI Generated Cyber Attackscited by 2
  30. 2025taz2024full: Analysing German Newspapers for Gender Bias and Discrimination across Decadescited by 2
  31. 2024Ethics Whitepaper: Whitepaper on Ethical Research into Large Language Modelscited by 1
  32. 2024Implicit Priors Editing in Stable Diffusion via Targeted Token Adjustmentcited by 1
  33. 2025Fairness Dynamics During Trainingcited by 1
  34. 2025Theories of "Sexuality" in Natural Language Processing Bias Researchcited by 1
  35. 2025Are All Genders Equal in the Eyes of Algorithms? -- Analysing Search and Retrieval Algorithms for Algorithmic Gender Fairnesscited by 1
  36. 2026QueerGen: How LLMs Reflect Societal Norms on Gender and Sexuality in Sentence Completion Taskscited by 1
  37. 2023Detecting and Mitigating Indirect Stereotypes in Word Embeddingscited by 0
  38. 2023Don't Overlook the Grammatical Gender: Bias Evaluation for Hindi-English Machine Translationcited by 0

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