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Ozan Isler

Researcher at Queensland University of Technology

Publications -  28
Citations -  456

Ozan Isler is an academic researcher from Queensland University of Technology. The author has contributed to research in topics: Medicine & Public health. The author has an hindex of 5, co-authored 13 publications receiving 210 citations. Previous affiliations of Ozan Isler include University of Nottingham & Doğuş University.

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The Price of Inequality: How Today's Divided Society Endangers Our Future

TL;DR: The causes and consequences of income and wealth inequality have become matters of deep interest, not only to social scientists but also to the general public as discussed by the authors. In clear and accessible language and...
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National identity predicts public health support during a global pandemic

Jay J. Van Bavel, +256 more
TL;DR: In a large international collaboration, this paper investigated self-reported factors associated with public health behaviours (e.g., spatial distancing and stricter hygiene) and endorsed public policy interventions during the early stage of the COVID-19 pandemic (April-May 2020).
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Is intuition really cooperative? Improved tests support the social heuristics hypothesis.

TL;DR: This study resolves the noncompliance issue, shows that misunderstanding does not confound tests of intuitive cooperation, and provides the first independent experimental evidence for intuitive cooperation in a social dilemma using time-pressure.
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Limits of the social-benefit motive among high-risk patients: a field experiment on influenza vaccination behaviour

TL;DR: In contrast to the literature observing intentions of low-risk populations, it is found no evidence that social-benefit motivates actual vaccination behaviour among a high-risk patient population, and those who self-categorize as being in the high risk group are more motivated by the self-benefit message.
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Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning

Tomislav Pavlović, +227 more
- 01 Jul 2022 - 
TL;DR: This paper applied machine learning on the multinational data collected by the International Collaboration on the Social and Moral Psychology of COVID-19 (N = 51,404) to test the predictive efficacy of constructs from social, moral, cognitive, and personality psychology, as well as socio-demographic factors, in the attitudinal and behavioral responses to the pandemic.