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Support for Increasing Low-Wage Workers’Compensation: The Role of
Fixed-Growth Mindsets About Intelligence
Shilpa Madan
1
, Anyi Ma
2
, Neeraj Pandey
3
, Aneeta Rattan
4
, and Krishna Savani
5, 6
1
Department of Marketing, Pamplin College of Business, Virginia Tech
2
Management Area, AB Freeman School of Business, Tulane University
3
Amrut Mody School of Management, Ahmedabad University
4
Department of Organisational Behaviour, London Business School
5
Department of Management and Marketing, The Hong Kong Polytechnic University
6
Department of Leadership, Management, and Organization, Nanyang Technological University
Approximately 44% of U.S. workers are low-wage workers. Recent years have witnessed a raging
debate about whether to raise their minimum wages. Why do some decision-makers support raising
wages and others do not? Ten studies (four preregistered) examined people’s beliefs about the malleabil-
ity of intelligence as a key antecedent. The more U.S. human resource managers (Study 1) and Indian
business owners (Study 2) believed that people’s intelligence can grow (i.e., had a growth mindset), the
more they supported increasing low-wage workers’compensation. In key U.S. swing states (Study 3a),
and a nationally representative sample (Study 3b), residents with a more growth mindset were more
willing to support ballot propositions increasing the minimum wage and other compensation. Study 4
provided causal evidence. The next two studies confirmed the specificity of the predictor. People’s
beliefs about the malleability of intelligence, but not personality (Study 5a) or effort (Study 5b), pre-
dicted their support for increasing low-wage workers’compensation. Study 6 examined multiple poten-
tial mechanisms, including empathy, attributions for poverty, and environmental affordances. The
relationship between growth mindset and support for raising low-wage workers’wages was explained
by more situational rather than dispositional attributions for poverty. Finally, Studies 7a and 7b repli-
cated the effect of growth mindset on support for increasing low-wage workers’compensation and pro-
vided confirmatory evidence for the mediator—situational, rather than dispositional, attributions of
poverty. These findings suggest that growth mindsets about intelligence promote support for increasing
low-wage workers’wages; we discuss the theoretical and practical implications.
Keywords: low-wage workers, lay theories, minimum wage, fixed-growth mindsets, attributions
Supplemental materials: https://doi.org/10.1037/xge0001303.supp
As many as 53 million Americans, or 44% of all workers aged
18–64, are employed in low-wage jobs (Ross & Bateman, 2019).
Often, these workers are unable to afford basic necessities, such as
food and shelter, and rely on government programs (e.g., food
stamps, public housing) to meet their basic needs (Belser & Rani,
2010;U.S. Census Bureau, 2013;U.S. Department of Labor,
2013a,2013b). In recent years, perhaps spurred by workers’advo-
cacy and public debate, several entities have taken steps toward
increasing the compensation of low-wage workers. For example,
some cities (e.g., New York City; Washington, D.C.; San Fran-
cisco), states (e.g., Arizona, Colorado, and Maine), and global cor-
porations (e.g., Costco, Ikea, Starbucks, and Whole Foods) have
raised their minimum wages in recent years (Kaufman, 2017;
National Conference of State Legislatures, 2017). Yet, many cor-
porations, localities, and small businesses continue to comply only
with the minimum established compensation standards (Hiltzik,
2020), which have not been raised nationally in the United States
since 2009 (Elwell, 2014).
Widespread stereotypes characterize these workers’jobs as
low-skilled or unskilled, and the workers themselves are stereo-
typed as lacking intelligence or competence (Fiske et al., 2002,p.
885). If people’s judgments of low-wage workers’compensation
are based in part on their views of the workers’intelligence or
Shilpa Madan https://orcid.org/0000-0001-8224-177X
Krishna Savani https://orcid.org/0000-0002-6934-1917
We received feedback from participants at the Society for Personality
and Social Psychology Conference in 2017 and 2022 and the Academy of
Management Conference in 2014, 2015, and 2022. We thank Carol Dweck
and Lisa Shu for helpful feedback on previous drafts, and Andrea Low,
Dayana Bulchand, Velvetina Lim, Yu Ding, and Janice Foo for generous
research assistance. The study materials, data, and analysis code are
available at https://osf.io/jtqmv/ (Madan, Ma, et al., 2022).
Correspondence concerning this article should be addressed to Krishna
Savani, Department of Management and Marketing, The Hong Kong
Polytechnic University, Li Ka Shing Tower, Hung Hom, Kowloon, Hong
Kong. Email: krishna.savani@polyu.edu.hk
1
Journal of Experimental Psychology: General
©2022 American Psychological Association
ISSN: 0096-3445 https://doi.org/10.1037/xge0001303
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2023, Vol. 152, No. 4, 935–955
935
This article was published Online First October 31, 2022.
