.png){kind=icon}
返回
Understanding mechanisms behind discrimination using diffusion decision modeling*
.png){kind=icon}
PRE
AI
DOI：10.1016/j.jesp.2021.104134.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Past research has documented where discrimination occurs or tested interventions that reduce discrimination. Less is known about how discriminatory behavior emerges and the mechanisms through which successful interventions work. Two studies (N > 4500) apply the Diffusion Decision Model (DDM) to the Judgment Bias Task, a measure of discrimination. In control conditions, participants gave preferential treatment (acceptance to a hypothetical honor society) to physically attractive applicants. DDM analyses revealed participants initially favored attractive candidates and attractiveness was accumulated as evidence of being qualified. Two interventions & mdash;raising awareness of bias and asking for more deliberative judgments & mdash;reduced discrimination through separate mechanisms. Raising awareness reduced biases in drift rates while increasing deliberation raised decision thresholds. This work offers insight into how discrimination emerges and may aid efforts to develop interventions to lessen discrimination.
Keyword:
Diffusion decision model
Judgment bias task
Intervention
Discrimination
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.1
论文数:
3.8K
被引数:
1.5W
机构
引用论文
.png){kind=icon}
What Happens Before? A Field Experiment Exploring How Pay and Representation Differentially Shape Bias on the Pathway Into Organizations之前发生了什么？一项实地实验，探索薪酬和代表如何在进入组织的途径上差异地塑造偏见
OAAI
OAAI分享收藏SELF-REGULATION OF PREJUDICED RESPONSES - IMPLICATIONS FOR PROGRESS IN PREJUDICE-REDUCTION EFFORTS
PREAI
分享收藏
查看更多内容