This collection includes both ASU Theses and Dissertations, submitted by graduate students, and the Barrett, Honors College theses submitted by undergraduate students. 

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It is a well-established finding in memory research that spacing or distributing information, as opposed to blocking all the information together, results in an enhanced memory of the learned material. Recently, researchers have decided to investigate if this spacing effect is also beneficial in category learning. In a set of

It is a well-established finding in memory research that spacing or distributing information, as opposed to blocking all the information together, results in an enhanced memory of the learned material. Recently, researchers have decided to investigate if this spacing effect is also beneficial in category learning. In a set of experiments, Carvalho & Goldstone (2013), demonstrated that a blocked presentation showed an advantage during learning, but that ultimately, the distributed presentation yielded better performance during a post-learning transfer test. However, we have identified a major methodological issue in this study that we believe contaminates the results in a way that leads to an inflation and misrepresentation of learning levels. The present study aimed to correct this issue and re-examine whether a blocked or distributed presentation enhances the learning and subsequent generalization of categories. We also introduced two shaping variables, category size and distortion level at transfer, in addition to the mode of presentation (blocked versus distributed). Results showed no significant differences of mode of presentation at either the learning or transfer phases, thus supporting our concern about the previous study. Additional findings showed benefits in learning categories with a greater category size, as well as higher classification accuracy of novel stimuli at lower-distortion levels.
ContributorsJacoby, Victoria Leigh (Author) / Homa, Donald (Thesis director) / Brewer, Gene (Committee member) / Davis, Mary (Committee member) / Department of Psychology (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12
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Description

Significant health inequalities exist between different castes and ethnic communities in India, and identifying the roots of these inequalities is of interest to public health research and policy. Research on caste-based health inequalities in India has historically focused on general, government-defined categories, such as “Scheduled Castes,” “Scheduled Tribes,” and “Other

Significant health inequalities exist between different castes and ethnic communities in India, and identifying the roots of these inequalities is of interest to public health research and policy. Research on caste-based health inequalities in India has historically focused on general, government-defined categories, such as “Scheduled Castes,” “Scheduled Tribes,” and “Other Backward Classes.” This method obscures the diversity of experiences, indicators of well-being, and health outcomes between castes, tribes, and other communities in the “scheduled” category. This study analyzes data on 699,686 women from 4,260 castes, tribes and communities in the 2015-2016 Demographic and Health Survey of India to: (1) examine the diversity within and overlap between general, government-defined community categories in both wealth, infant mortality, and education, and (2) analyze how infant mortality is related to community category membership and socioeconomic status (measured using highest level of education and household wealth). While there are significant differences between general, government-defined community categories (e.g., scheduled caste, backward class) in both wealth and infant mortality, the vast majority of variation between communities occurs within these categories. Moreover, when other socioeconomic factors like wealth and education are taken into account, the difference between general, government-defined categories reduces or disappears. These findings suggest that focusing on measures of education and wealth at the household level, rather than general caste categories, may more accurately target those individuals and households most at risk for poor health outcomes. Further research is needed to explain the mechanisms by which discrimination affects health in these populations, and to identify sources of resilience, which may inform more effective policies.

ContributorsClauss, Colleen (Author) / Hruschka, Daniel (Thesis director) / Davis, Mary (Committee member) / Barrett, The Honors College (Contributor) / School of Human Evolution & Social Change (Contributor) / Department of Psychology (Contributor)
Created2022-05