Sanaz Talaifar

All Publications

• A new pathway to college retention? Identity fusion with university predicts retention independently of grades Social Psychological and Personality Science Talaifar, S., Ashokkumar, A., Pennebaker, J. W., Medrano, F. N., Yeager, D. S., Swann, Jr., W. B. 2020: 108-117

  Abstract

  Individuals who are "strongly fused" with a group view the group as self-defining. As such, they should be particularly reluctant to leave it. For the first time, we investigate the implications of identity fusion for university retention. We found that students who were strongly fused with their university (+1 SD) were 7-9% points more likely than weakly fused students (-1SD) to remain in school up to a year later. Fusion with university predicted subsequent retention in four samples (N = 3,193) and held while controlling for demographics, personality, prior academic performance, and belonging uncertainty. Interestingly, fusion with university was largely unrelated to grades, suggesting that identity fusion provides a novel pathway to retention independent of established pathways like academic performance. We discuss the theoretical and practical implications of these findings.

  View details for DOI 10.1177/1948550619894995

  View details for PubMedCentralID PMC8009486

• Asymmetries in mutual understanding: People with low status, power, and self-esteem understand better than they are understood Perspectives on Psychological Science Talaifar, S., Burhmester, M. D., Ayduk, Ö., Swann, Jr., W. B. 2020

  View details for DOI 10.31234/osf.io/pwcxm

• Censoring political opposition online: Who does it and why Journal of Experimental Social Psychology Ashokkumar, A., Talaifar, S., et al 2020

  View details for DOI 10.31234/osf.io/r9c5z

• Deep alignment with country shrinks the moral gap between conservatives and liberals Political Psychology Talaifar, S., Swann, Jr., W. B. 2019; 40 (3): 657-675

  View details for DOI 10.1111/pops.12534

• An Evaluation of Amazon's Mechanical Turk, Its Rapid Rise, and Its Effective Use PERSPECTIVES ON PSYCHOLOGICAL SCIENCE Buhrmester, M. D., Talaifar, S., Gosling, S. D. 2018; 13 (2): 149–54

  Abstract

  Over the past 2 decades, many social scientists have expanded their data-collection capabilities by using various online research tools. In the 2011 article "Amazon's Mechanical Turk: A new source of inexpensive, yet high-quality, data?" in Perspectives on Psychological Science, Buhrmester, Kwang, and Gosling introduced researchers to what was then considered to be a promising but nascent research platform. Since then, thousands of social scientists from seemingly every field have conducted research using the platform. Here, we reflect on the impact of Mechanical Turk on the social sciences and our article's role in its rise, provide the newest data-driven recommendations to help researchers effectively use the platform, and highlight other online research platforms worth consideration.

  View details for DOI 10.1177/1745691617706516

  View details for Web of Science ID 000429909000006

  View details for PubMedID 29928846