2021
DOI: 10.1111/desc.13169
|View full text |Cite
|
Sign up to set email alerts
|

Testing the limits of structural thinking about gender

Abstract: White for help with data collection, and Ilayda Orhan and Haley Hegefeld for coding. Data Availability Statement:All study materials, data files, and analysis code that replicates all results in the manuscript and supplemental materials are also openly shared and are available on an anonymous link at: https://osf.io/6kx4e/?view_only=33413fde2df346328f32e0bc5e72d11e. LIMITS OF STRUCTURAL THINKING 2 Research Highlights• Two studies probed children's structural reasoning about gender norms and explored evaluative… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

1
23
0

Year Published

2021
2021
2024
2024

Publication Types

Select...
6
1

Relationship

0
7

Authors

Journals

citations
Cited by 15 publications
(24 citation statements)
references
References 49 publications
1
23
0
Order By: Relevance
“…In other words, structural attributions might enable children to causally account for observed disparities while avoiding personal attributions and their pernicious consequences. Optimistically, emerging research supports the idea that even young children are capable of forming structural attributions (Hussak and Cimpian, 2015;Vasilyeva et al, 2018;Peretz-Lange and Muentener, 2019;Yang et al, 2021). The present study contributes to this emerging research area in a few ways: First, the research on structural attributions often involves explicitly telling children about the cause of a given disparity (e.g., Hussak and Cimpian, 2015;Sutherland and Cimpian, 2019;Rizzo et al, 2020;Dunlea and Heiphetz, 2021).…”
Section: Personal Attributions and Prejudice Developmentsupporting
confidence: 54%
See 3 more Smart Citations
“…In other words, structural attributions might enable children to causally account for observed disparities while avoiding personal attributions and their pernicious consequences. Optimistically, emerging research supports the idea that even young children are capable of forming structural attributions (Hussak and Cimpian, 2015;Vasilyeva et al, 2018;Peretz-Lange and Muentener, 2019;Yang et al, 2021). The present study contributes to this emerging research area in a few ways: First, the research on structural attributions often involves explicitly telling children about the cause of a given disparity (e.g., Hussak and Cimpian, 2015;Sutherland and Cimpian, 2019;Rizzo et al, 2020;Dunlea and Heiphetz, 2021).…”
Section: Personal Attributions and Prejudice Developmentsupporting
confidence: 54%
“…This would indicate that framing shapes participants' conceptual understanding of disparities, rather than only their perceptual attention to different features of the visual scene, though we do not claim this indicates any longer-lasting impacts of framing outside of the context of the experiment. We also predicted that structural attributions would increase over development, as in prior work on structural attributions for gender differences (Vasilyeva et al, 2018;Amemiya et al, 2021;Yang et al, 2021).…”
Section: The Present Studymentioning
confidence: 71%
See 2 more Smart Citations
“…Emerging evidence suggests, to the contrary, that presenting people with information only about current structural constraints may be insufficient to promote structural thinking. For example, even when reasoners observe obvious structural constraints on girls' and boys' toy choices (e.g., girls could only reach dolls and not trucks), they still endorse intrinsic explanations for gender-stereotypical play behavior (Amemiya et al, 2021;Yang et al, 2021). A counterfactual approach argues that, without evidence that the structural constraints were difference-making (e.g., that girls would not have only played with dolls had there been fewer constraints), reasoners may reject that constraints caused the social group differences and continue to privilege intrinsic explanations.…”
Section: Implications Of Taking a Counterfactual Approach To Structural Causal Inferencementioning
confidence: 99%