Economic Mobility &amp; Karma - Society Study
Creators: name: Caluori, Nava
name: McKee, Stephanie
name: Brown-Iannuzzi, Jazmin
name: Gervais, Will M
Publisher: name: Open Science Framework
Year: 2021
Subjects: subject: Social and Behavioral Sciences

description: I. Overview The goal of this project is to examine how economic mobility affects individuals’ emphasis of and desire to perpetuate karmic religious beliefs. We will conduct an online study that manipulates the salience of economic mobility and measure how it affects these processes. II. Methods and Measures All measures are included in the uploaded copy of our Qualtrics surveys. In this study, participants will be told that they will take on the persona of a character in a new society called Dorrania for the duration of the study. They will learn that Dorrania is still forming its social systems such as its religion, economic systems, political systems, etc., and that they will have the opportunity to weigh in on how these social systems should be formed. They will then learn a bit about the Dorranian character whose persona they will take on. In the upward mobility condition, they will learn that their character has gradually accumulated wealth and lives in an upper-class part of Dorrania. In the downward mobility condition, they will learn that their character has gradually lost wealth and lives in a lower-class part of Dorrania. Participants will then answer questions about Dorranian social systems as the character they read about. They will first answer questions about how much they think Dorrania’s new religion should emphasize various religious beliefs. Five of the items in this measure are adapted from White et al. (2020) (ex: People bring their outcomes upon themselves by their previous, unrelated actions in their life), and the remaining six items are drawn from the six-item SBS scale (Jong &amp; Halberstadt, 2016) (ex: There is some kind of life after death). Next, participants will answer questions about Dorrania’s economic system. They will answer one question about the extent to which they think the wealthy should be taxed to provide benefits to the poor, and will then answer three specific questions about wealth redistribution. We will test whether these four items have good reliability together, and if so, we will average them into one wealth redistribution index. Last, participants will complete a demographics questionnaire, data quality check questions, and will then be debriefed. III. Sample Size Plan For consistency with previous studies, we will recruit 650 participants. We will include attention checks and checks to confirm that respondents are human (as opposed to bots) in this survey. We will also exclude participants who report that they did not pay attention or answer honestly in our data quality check questions. If a significant amount of people do not pass these checks, we will continue data collection beyond 650 participants until we have collected a sufficient number of participants who have passed the checks. Participants will be recruited online through Amazon MTurk. IV. Hypotheses &amp; Analysis Plan We expect that participants in the upward mobility condition will want to emphasize karma-related religious beliefs more than participants in the downward mobility condition. We will test this prediction with an independent-samples t-test. We will assess the reliability of these 5 karma items and, if acceptable reliability is reached, we will average them into a karma index that we will treat as our dependent variable. The other items in this scale serve as filler items and therefore are not relevant to this analysis. We will also test whether participants in the upward mobility condition are less supportive of wealth redistribution policies than people in the downward mobility condition, and whether condition has an indirect effect on support for these policies through karma. We will also conduct exploratory analyses, such as whether any demographic measures may moderate our findings. We will investigate whether the results differ depending on including or excluding participants who fail attention checks. We will also investigate the data for potential outliers and may delete outliers if they violate model assumptions. Finally, we will investigate all model assumptions and will make the appropriate remedies when model assumptions are violated or, when necessary, will switch to a more appropriate analytic technique to analyze the data.