Registered report protocol: Stress testing predictive models of ideological prejudice.
PLoS One
; 19(8): e0308397, 2024.
Article
en En
| MEDLINE
| ID: mdl-39208134
ABSTRACT
In this registered report, we propose to stress-test existing models for predicting the ideology-prejudice association, which varies in size and direction across target groups. Previous models of this relationship use the perceived ideology, status, and choice in group membership of target groups to predict the ideology-prejudice association across target groups. These analyses show that models using only the perceived ideology of the target group are more accurate and parsimonious in predicting the ideology-prejudice association than models using perceived status, choice, and all of the characteristics in a single model. Here, we stress-test the original models by testing the models' predictive utility with new measures of explicit prejudice, a comparative operationalization of prejudice, the Implicit Association Test, and additional target groups. In Study 1, we propose to directly test the previous models using an absolute measure of prejudice that closely resembles the measure used in the original study. This will tell us if the models replicate with distinct, yet conceptually similar measures of prejudice. In Study 2, we propose to develop new ideology-prejudice models for a comparative operationalization of prejudice using both explicit measures and the Implicit Association Test. We will then test these new models using data from the Ideology 2.0 project collected by Project Implicit. We do not have full access to this data yet, but upon acceptance of our Stage 1 registered report, we will gain access to the complete dataset. Currently, we have access to an exploratory subset of the data that we use to demonstrate the feasibility of the study, but its limited number of target groups prevents conclusions from being made.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Prejuicio
Límite:
Humans
/
Male
Idioma:
En
Revista:
PLoS One
Asunto de la revista:
CIENCIA
/
MEDICINA
Año:
2024
Tipo del documento:
Article
País de afiliación:
Estados Unidos
Pais de publicación:
Estados Unidos