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Szasz, Teodora; Harrison, Emileigh; Liu, Ping-Jung; Lin, Ping-Chang; Runesha, Hakizumwami Birali; Adukia, Anjali – Grantee Submission, 2022
Images in children's books convey messages about society and the roles that people play in it. Understanding these messages requires systematic measurement of who is represented. Computer vision face detection tools can provide such measurements; however, state-of-the-art face detection models were trained with photographs, and 80\% of images in…
Descriptors: Childrens Literature, Books, Artificial Intelligence, Race
Josh Leung-Gagné; Sean F. Reardon – Grantee Submission, 2023
Recent studies have shown that U.S. Census-- and American Community Survey (ACS)--based estimates of income segregation are subject to upward finite sampling bias (Logan et al. 2018; Logan et al. 2020; Reardon et al. 2018). We identify two additional sources of bias that are larger and opposite in sign to finite sampling bias: measurement…
Descriptors: Income, Low Income Groups, Social Bias, Statistical Bias
Anjali Adukia; Callista Christ; Anjali Das; Ayush Raj – Grantee Submission, 2022
The way that people of different identities are portrayed in children's books can send subconscious messages about how positively or negatively children should think about people with those identities. These messages can then shape the next generation's perceptions and attitudes about people, which can have important implications for belief…
Descriptors: Childrens Literature, Books, Race, Gender Bias
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Adukia, Anjali; Chiril, Patricia; Christ, Callista; Das, Anjali; Eble, Alex; Harrison, Emileigh; Runesha, Hakizumwami Birali – Grantee Submission, 2022
The manner in which gender is portrayed in materials used to teach children conveys messages about people's roles in society. In this paper, we measure the gendered depiction of central domains of social life in 100 years of highly influential children's books. We make two main contributions: (1) we find that the portrayal of gender in these books…
Descriptors: Childrens Literature, Books, Gender Bias, Sex Stereotypes
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Liyang Sun; Eli Ben-Michael; Avi Feller – Grantee Submission, 2024
The synthetic control method (SCM) is a popular approach for estimating the impact of a treatment on a single unit with panel data. Two challenges arise with higher frequency data (e.g., monthly versus yearly): (1) achieving excellent pre-treatment fit is typically more challenging; and (2) overfitting to noise is more likely. Aggregating data…
Descriptors: Evaluation Methods, Comparative Analysis, Computation, Data Analysis
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Diana L. Jenkins; Aubrey L. Hoffer; Dawn DeLay – Grantee Submission, 2024
The current study explored the relation between sexual orientation, masculinity ideology, and sexism among 380 adult heterosexual and bisexual women. Participants completed measures of sexual orientation, masculinity ideology, hostile sexism, and benevolent sexism. Mean-level analyses concluded that heterosexual women scored significantly higher…
Descriptors: Masculinity, Ideology, Gender Bias, Sexual Orientation
Summer S. Braun; Caryn R. R. Rodgers; Arielle Linsky; Charity Brown Griffin; Catherine P. Bradshaw – Grantee Submission, 2023
The present study examined the association between students' perceptions of an equitable school climate and several psychosocial outcomes and tested whether these associations were moderated by students' race and gender. Data from 57,027 6th-12th grade students were analyzed using three-level models. Students who perceived their school to have a…
Descriptors: Student Attitudes, Equal Education, Secondary School Students, Psychological Patterns
Li, Chenglu; Xing, Wanli; Leite, Walter L. – Grantee Submission, 2021
There has been a long-standing issue of sparse discussion forums participation in online learning, which can impede students' help seeking practices. Researchers have examined AI techniques such as link prediction with network analysis to connect help seekers with help providers. However, little is known whether these AI systems will treat…
Descriptors: Artificial Intelligence, Educational Technology, Technology Uses in Education, Online Courses
Walter A. Herring; Daphna Bassok; Anita S. McGinty; Luke C. Miller; James H. Wyckoff – Grantee Submission, 2022
Federal accountability policy mandates that states administer standardized tests beginning in third grade. In turn, third-grade test scores are often viewed as a key indicator in policy and practice. Yet literacy struggles begin well before third grade, as do racial and socioeconomic disparities in children's literacy skills. Kindergarten…
Descriptors: Socioeconomic Status, Emergent Literacy, Grade 3, School Readiness
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Brian J. Reece; Diana L. Jenkins; Austin C. Folger; Daniel S. Shaw; Jenae M. Neiderhiser; Jody M. Ganiban; Leslie D. Leve – Grantee Submission, 2024
Although the adoption rate among same-sex couples has been increasing, limited research has focused on factors influencing decision making related to placing children with such couples, particularly from the standpoint of birth mothers. Additionally, there is a gap in the literature regarding how biases may influence birth mothers' decision to…
Descriptors: Adoption, Homosexuality, Decision Making, Mothers
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Denisa Gándara; Hadis Anahideh; Matthew P. Ison; Lorenzo Picchiarini – Grantee Submission, 2024
Colleges and universities are increasingly turning to algorithms that predict college-student success to inform various decisions, including those related to admissions, budgeting, and student-success interventions. Because predictive algorithms rely on historical data, they capture societal injustices, including racism. In this study, we examine…
Descriptors: Algorithms, Social Bias, Minority Groups, Equal Education
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David Menendez; Andrea Marquardt Donovan; Olympia N. Mathiaparanam; Vienne Seitz; Nour F. Sabbagh; Rebecca E. Klapper; Charles W. Kalish; Karl S. Rosengren; Martha W. Alibali – Grantee Submission, 2024
Do children think of genetic inheritance as deterministic or probabilistic? In two novel tasks, children viewed the eye colors of animal parents and judged and selected possible phenotypes of offspring. Across three studies (N = 353, 162 girls, 172 boys, 2 non-binary; 17 did not report gender) with predominantly White U.S. participants collected…
Descriptors: Children, Childrens Attitudes, Beliefs, Genetics
Brian T. Keller; Craig K. Enders – Grantee Submission, 2023
A growing body of literature has focused on missing data methods that factorize the joint distribution into a part representing the analysis model of interest and a part representing the distributions of the incomplete predictors. Relatively little is known about the utility of this method for multilevel models with interactive effects. This study…
Descriptors: Data Analysis, Hierarchical Linear Modeling, Monte Carlo Methods, Bias
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Regan Mozer; Luke Miratrix – Grantee Submission, 2024
For randomized trials that use text as an outcome, traditional approaches for assessing treatment impact require that each document first be manually coded for constructs of interest by trained human raters. This process, the current standard, is both time-consuming and limiting: even the largest human coding efforts are typically constrained to…
Descriptors: Artificial Intelligence, Coding, Efficiency, Statistical Inference
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D. Betsy McCoach; Scott Peters; Anthony J. Gambino; Daniel Long; Del Siegle – Grantee Submission, 2024
Teacher rating scales (TRS) often play a part in service eligibility decisions for gifted services. Although schools regularly use TRS to identify gifted students either as part of an informal nomination process or through behavioral rating scales, there is little research documenting the between-teacher variance in teacher ratings and the…
Descriptors: Gifted Education, Rating Scales, Academically Gifted, Academic Achievement
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