Results 71 to 80 of about 6,437 (212)

A regularised latent‐class item response model for detecting measurement non‐invariance in ordinal response scales

British Journal of Mathematical and Statistical Psychology, EarlyView.
Abstract Measurement non‐invariance arises when the psychometric properties of a scale differ across subgroups, undermining the validity of group comparisons. At the item level, this manifests as differential item functioning (DIF), where item responses differ across groups after controlling for the latent trait.
Gabriel Wallin, Qi Huang
wiley   +1 more source

Debiasing convolutional neural networks via Meta Orthogonalization

, 2020
As deep learning becomes present in many applications, we must consider possible shortcomings of these models, such as bias towards protected attributes in datasets.
David, Kurtis Evan Alejo
core   +1 more source

New Accelerants of Inequality Regimes: AI‐Hiring Tools and Algorithmic Bias

Gender, Work &Organization, EarlyView.
ABSTRACT AI‐hiring technology is becoming increasingly widely adopted, raising important questions about what effect such technology may have on organizational inequality regimes. Although there is a large and growing body of literature surrounding the effects of AI hiring, its impacts, and bias, markedly less is known about who develops, sells, and ...
Emily Yarrow
wiley   +1 more source

Evaluating Debiasing Techniques for Intersectional Biases

, 2021
Bias is pervasive in NLP models, motivating the development of automatic debiasing techniques. Evaluation of NLP debiasing methods has largely been limited to binary attributes in isolation, e.g., debiasing with respect to binary gender or race, however ...
Subramanian, S, Han, X, Cohn, T, Frermann, L, Baldwin, T   +4 more
core   +1 more source

Fair Classification Without Sensitive Attribute Labels via Dynamic Reweighting

Applied Sciences
Fairness-aware classification with respect to sensitive attributes, such as gender and race, is one of the most important topics in machine learning. Although numerous studies have made outstanding progress through various approaches, one key limitation ...
Pilhyeon Lee, Sungho Park
doaj   +1 more source

The Price of Prominence: How CEO Extraversion Influences Board Attributions and the Dismissal‐Performance Sensitivity

Journal of Management Studies, EarlyView.
Abstract This study extends the socio‐cognitive perspective on CEO dismissal by examining how CEOs' observed levels of extraversion influence the dismissal‐performance sensitivity. Integrating attribution theory with research on personality and leadership, we theorize that more extraverted CEOs' prominence and perceived agency increase directors ...
Jan C. Hennig, Sebastian Firk, Joseph S. Harrison, Hauke Meyer, Michael Wolff   +4 more
wiley   +1 more source

Debiasing the supplier selection decision: a taxonomy and conceptualization

, 2010
PurposeThe authors perform a large‐scale review of debiasing literature with the purpose of deriving a mutually exclusive and exhaustive debiasing taxonomy.
Christian Buhrmann, Lutz Kaufmann, Craig R. Carter   +2 more
core   +1 more source

Algorithmic Status Inequality: An Integrative Perspective on AI‐Driven Social Stratification

Journal of Management Studies, EarlyView.
Abstract This Point introduces algorithmic status inequality that is, enduring disparities in social position, influence, and resource access reinforced by AI systems, as a critical lens for understanding technological stratification in organizations. I develop an integrative model showing how computational beliefs (i.e., cultural assumptions embedded ...
Jie Wu
wiley   +1 more source

AI Presents Both Problems and Opportunities for Minorities

Journal of Management Studies, EarlyView.
Abstract The recent Point article by Wu (2026) calls for a better understanding of factors that could lead to the development of AI systems that are likely to perpetuate social inequality. The Point article introduces the idea that computational beliefs interact with computational inequalities in a more systematic manner that develops AI systems which ...
María del Carmen Triana, Arun Upadhyay
wiley   +1 more source

A large-scale study and six-month follow-up of an intervention to reduce causal illusions in high school students

Royal Society Open Science
Causal illusions consist of believing that there is a causal relationship between events that are actually unrelated. This bias is associated with pseudoscience, stereotypes and other unjustified beliefs.
Naroa Martínez, Helena Matute, Fernando Blanco, Itxaso Barberia   +3 more
doaj   +1 more source