Results 1 to 10 of about 50,154 (270)

Transcending the "Male Code": Implicit Masculine Biases in NLP Contexts [PDF]

In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (CHI '23). Association for Computing Machinery, New York, NY, USA, Article 138, 1-19, 2023
Critical scholarship has elevated the problem of gender bias in data sets used to train virtual assistants (VAs). Most work has focused on explicit biases in language, especially against women, girls, femme-identifying people, and genderqueer folk; implicit associations through word embeddings; and limited models of gender and masculinities, especially
arxiv   +1 more source

Interacting with Masculinities: A Scoping Review [PDF]

In Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems (CHI EA '23). Association for Computing Machinery, New York, NY, USA, Article 179, 1-12, 2023
Gender is a hot topic in the field of human-computer interaction (HCI). Work has run the gamut, from assessing how we embed gender in our computational creations to correcting systemic sexism, online and off. While gender is often framed around women and femininities, we must recognize the genderful nature of humanity, acknowledge the evasiveness of ...
arxiv   +1 more source

Exploring Gender-Expansive Categorization Options for Robots [PDF]

CHI EA '22: CHI Conference on Human Factors in Computing Systems Extended Abstracts, April 2022, Article No.: 252, 2022
Gender is increasingly being explored as a social characteristic ascribed to robots by people. Yet, research involving social robots that may be gendered tends not to address gender perceptions, such as through pilot studies or manipulation checks.
arxiv   +1 more source

Gender Biases in Error Mitigation by Voice Assistants [PDF]

Proceedings of the ACM on Human-Computer Interaction, Volume 8, Issue CSCW1, 2024; Article No.: 60, Pages 1 - 27, 2023
Commercial voice assistants are largely feminized and associated with stereotypically feminine traits such as warmth and submissiveness. As these assistants continue to be adopted for everyday uses, it is imperative to understand how the portrayed gender shapes the voice assistant's ability to mitigate errors, which are still common in voice ...
arxiv   +1 more source

Voice Gender Scoring and Independent Acoustic Characterization of Perceived Masculinity and Femininity [PDF]

arXiv, 2021
Previous research has found that voices can provide reliable information to be used for gender classification with a high level of accuracy. In social psychology, perceived masculinity and femininity (masculinity and femininity rated by humans) has often been considered an important feature when investigating the influence of vocal features on social ...
arxiv  

Multilingual Holistic Bias: Extending Descriptors and Patterns to Unveil Demographic Biases in Languages at Scale [PDF]

arXiv, 2023
We introduce a multilingual extension of the HOLISTICBIAS dataset, the largest English template-based taxonomy of textual people references: MULTILINGUALHOLISTICBIAS. This extension consists of 20,459 sentences in 50 languages distributed across all 13 demographic axes.
arxiv  

Gender-Inclusive Grammatical Error Correction through Augmentation [PDF]

arXiv, 2023
In this paper we show that GEC systems display gender bias related to the use of masculine and feminine terms and the gender-neutral singular "they". We develop parallel datasets of texts with masculine and feminine terms and singular "they" and use them to quantify gender bias in three competitive GEC systems.
arxiv  

Test Suites Task: Evaluation of Gender Fairness in MT with MuST-SHE and INES [PDF]

arXiv, 2023
As part of the WMT-2023 "Test suites" shared task, in this paper we summarize the results of two test suites evaluations: MuST-SHE-WMT23 and INES. By focusing on the en-de and de-en language pairs, we rely on these newly created test suites to investigate systems' ability to translate feminine and masculine gender and produce gender-inclusive ...
arxiv  

VisoGender: A dataset for benchmarking gender bias in image-text pronoun resolution [PDF]

arXiv, 2023
We introduce VisoGender, a novel dataset for benchmarking gender bias in vision-language models. We focus on occupation-related biases within a hegemonic system of binary gender, inspired by Winograd and Winogender schemas, where each image is associated with a caption containing a pronoun relationship of subjects and objects in the scene.
arxiv  

Impacts of National Cultures on Managerial Decisions of Engaging in Core Earnings Management [PDF]

European Journal of Business and Management, 16(4):72-83 (2024)
This study investigates the impact of Hofstede's cultural dimensions on abnormal core earnings management in multiple national cultural contexts. We employ an Ordinary Least Squares (OLS) regression model with abnormal core earnings as the dependent variable.
arxiv   +1 more source