Post on 14-Apr-2022
Children’s Judgements of Fairness and Reparations
by
Inderpreet Kaur Gill
A thesis submitted in conformity with the requirements
for the degree of Master of Arts
Department of Psychology
University of Toronto
© Copyright by Inderpreet Kaur Gill (2021)
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Children’s Judgements of Fairness and Reparations
Inderpreet Kaur Gill
Master of Arts
Department of Psychology
University of Toronto
2021
Abstract
Do children, like adults, consider the original cause of the inequality as well as when the
inequality happened? In two experiments, we investigate how children reason about whether and
when past inequalities due to differences in hard work, bias and luck should be corrected.
Younger (5-6 years) children distribute coins equally regardless of the cause of the inequality or
when it happened (i.e. past or present). Older (7-8 years) children distribute more coins to the
child who worked harder (thus increasing inequality), and to the child who was biased against or
unlucky (thus decreasing inequality) when the inequalities happened in the present. However,
they were more likely to distribute coins equally when the inequality happened in the past. These
findings suggest younger children have strong preferences for equal distributions despite existing
inequalities and older children are less likely to rectify inequalities created in the past than those
created recently.
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Acknowledgments
First and foremost, thank you to my parents, Manjit and Rupinder, for their sacrifice,
unconditional support, and never-ending love. I would be nothing without the both of you. Your
work ethic, persistence, and positive attitude is admirable. I hope to make you proud.
I would also like to thank my amazing siblings, Ramneet and Jodhveer, for always making
me laugh, feeding me and motivating me to keep going. You both bring me so much joy.
To my dearest friends Sarah, Andy, Meaghan, Alanna and Jennie, thank you for lifting my
spirits, encouraging me, and for your friendship these last 10 years. You saw me through some of
my happiest and my most challenging days. I cannot begin to express my thanks to you.
To the greatest bonus parents a girl could have, Pat, David, Brian and Suzanne, thank you
for treating me like your own and never letting me feel just how far away from home I was.
Thank you to the friends I gained along the way to graduate school: Camille, Gioia, Denny,
Puja, Lama, Kristen, Charlotte, Kathy, Irene, Fibha, Lisa, Jasmine, Mehar and Setareh. From
bringing me up when I was down to thought-provoking intellectual conversations and spontaneous
adventures, you have each been there for me. I will be forever grateful for the positive impact you
have had on my life. How lucky am I to have such an inspiring group of strong, intelligent, and
kind women to call my friends?
To Ella and Umang, thank you for the pep talks on the way to get my daily ginger ale and
burrito. And, to Julia Espinosa, thank you for comforting me in the hallways of Sid Smith, letting
me pet Winnie on my bad days, and also for your guidance in navigating this new chapter. I am
forever indebted to the three of you for your words of encouragement, advice and emotional
support.
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Thank you to the wonderful research assistants at the StarLab for welcoming me and being
some of my first friends at the University of Toronto. Laura, Melissa, Morgan, Julie, Jasmine,
Maia and Sasha, I am so happy you did not believe what Umang was saying when I first got to the
lab.
To Dr. Wendy Craig, Dr. Valerie Kuhlmeier, Dr. Darko Odic, and Carolyn Baer, I would
not be writing an acknowledgement section, let alone a thesis, were it not for you. Thank you for
your profound belief in me and encouraging me to believe in myself. I would also like to thank
Dr. Yoel Inbar for being one of my committee members and for sharing your invaluable time and
expertise with me.
And, last, but not least, I would like to express my extreme gratitude to my supervisor
dream team: Dr. Christina Starmans and Dr. Jessica Sommerville. I consider myself incredibly
fortunate to have you both as my supervisors and to have this opportunity to learn from you.
Jessica, thank you for the many opportunities in my first year of graduate school, mentorship and
helping me grow as a researcher. Christina, thank you for your patience, insight, and unwavering
support. Thank you for making a safe space for me to learn from my mistakes. You inspire me to
be a better scientist.
"I had my ups and downs, but I always find the inner strength to pull myself up.
I was served lemons, but I made lemonade."
Beyoncé Giselle Knowles-Carter
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Table of Contents
Acknowledgments.......................................................................................................................... iii
Table of Contents .............................................................................................................................v
List of Figures ................................................................................................................................ vi
Chapter 1 Introduction .....................................................................................................................1
Chapter 2 Literature Review ............................................................................................................2
2.1 Adults’ Attitudes About Rectifying Inequalities .................................................................2
2.2 Infants’ Judgments About Fair Distributions .......................................................................7
2.3 Children’s Judgments About Fairness and Inequality .........................................................9
Chapter 3 Experiment 1 .................................................................................................................14
3.1 Method ...............................................................................................................................14
3.2 Results ................................................................................................................................16
Chapter 4 Experiment 2 .................................................................................................................18
4.1 Method ...............................................................................................................................19
4.2 Results ................................................................................................................................21
Chapter 5 General Discussion ........................................................................................................24
References ......................................................................................................................................35
Copyright Acknowledgements.......................................................................................................43
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List of Figures
1. Example of stimuli used in Experiment 1………………………………………………. 15
2. Average number of coins distributed to poor child in Experiment 1…………………… 17
3. Example of stimuli used in Experiment 2………………………………………………. 20
4. Average number of coins distributed to poor child in Experiment 2…………………… 22
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Chapter 1 Introduction
Much of the inequality that exists today can be traced back to events that happened
centuries ago and to events that persisted over a considerable period of time. For example, slavery
of Africans and African Americans in the United States not only affected individuals at the time
of the events, but also impacted descendants of the original victims so much so that a lot of the
inequality has dictated the experiences of future generations and the opportunities they would
have. As a result, inequality was continuously perpetuated over the years with each new generation
having to endure fewer rights, resources and opportunities. Recently, public discourse has centered
on how best to rectify present-day inequalities that resulted from discrimination in the past.
However, when the inequality originally happened to people in the past and has been passed down
through generations, it is difficult to navigate this and whether and how this inequality should be
corrected has become a divisive question. Employing a reparative scheme that involves unequal
distributions in the present raises concerns about whether such a scheme is most moral, or if there
are other distributions that may be more morally appropriate.
This research aims to investigate how people reason about rectifying past inequalities.
However, there is substantial disagreement among adults over what approach is fair. There are
those who think there is a moral obligation to make reparations (i.e. offering resources like money
or land; Posner & Vermeule, 2003) and there are some who think we should not give anything
because it would never restore true justice or equality (Frum, 2014; Williamson, 2014). There may
be two factors that interfere with adults’ sincere intuitions about what is considered fair: their
political affiliations, guiding them toward to pre-scripted policies of their favored political party,
and their own self-interest. One’s opposition to giving money to descendants of slavery, for
example, could be motivated by the belief that one will be contributing to reparations with their
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own money. Thus, if we are interested in exploring core intuitions about fairness, one avenue is to
examine the judgments of children, who are not biased by politics or self-interest, but have a
foundational understanding of fairness very early on in development.
There is currently little work directly exploring how children think about these issues.
However, insight can be gained by exploring adults’ reasoning about rectifying past inequalities,
as well as children’s reasoning about fairness and inequality more broadly. In the paragraphs that
follow, I will first review the adult literature, and then review the literature to date on children’s
judgments about fairness and inequality.
Chapter 2 Literature Review
2.1 Adults’ Attitudes About Rectifying Inequalities
While inequality has existed in North America for centuries, in recent years, it has been on
the rise at an unnerving rate. Inequalities relate to lived experiences and lead to large gaps in social,
cultural and economic rights. Lack of such rights provides different lived experiences for groups
that do not have access to such equality. Due to its personal relevance and it being such a prominent
element of life for many, people aim to understand the causes of inequality so they can decide how
best to approach inequalities and their own belief system (Kluegel & Smith, 2017). Though most
Americans recognize inequality exists as demonstrated by how the system discriminates against
Black and other minority groups in the US, for example, there lies an inconsistency in beliefs about
inequalities and in Americans’ attitudes about inequality related policies. Lerner & Miller (1978)
claim that according to a belief in the just world, people get what they deserve thereby making the
outcomes seemingly fair. If an individual has strong faith in a just world, they are more likely to
believe that the cause of the inequality has more to do with individual traits versus social structures
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(Smith, 1985). However, this belief state can allow people to negatively evaluate those who are
victims of inequality by justifying their inequality as a result from differences in effort or talent
while still regarding it as fair (Kluegel & Smith, 2017) meanwhile the inequality could be a result
of non-individual factors. As such, it is important to recognize how past inequalities come to be
and, how they are understood when determining how they should be corrected.
Through laboratory research, there is some evidence for an equality bias: adult participants
choose to equally divide resources between individuals (Harris & Joyce, 1980) and will divide
resources unequally if it means the distribution will reduce a financial inequality created by chance
(Dawes, Fowler, Johnson, McElreath & Smirnov, 2007; Xiao & Bicchiere, 2010). However, there
are scenarios in which resources should not be divided equally and an inequality should remain as
is. When given concrete information about someone’s performance where one individual works
harder compared to their partner, adults distribute more money to the person who is described as
working harder (Accominotti & Tadmon, 2020) presumably because it is fair to give more rewards
to the individual who worked harder. Whether an inequality is accepted or rejected is contingent
upon whether it is perceived to be fair or not (Starmans, Sheskin & Bloom, 2017). Adults evaluate
an inequality as fair when it is produced by fair processes such as those in line with normative
rules about resource allocation rather than simply being averse to inequality (Trump, 2020). Adults
reject inequalities when they violate the shared normative rules that could have explained unequal
outcomes as fair (Starmans, Sheskin & Bloom, 2017; Trump, 2020). Inequalities that adults judge
as fair are more prominently based on the following shared normative rules: inequalities as a result
of individual effort and merit than inequalities due to luck (Trump, 2020; Almas, Cappelen &
Tungodden, 2019; Sachweh & Sthamer, 2019; Nettle & Saxe, 2019) and inequalities between
ingroup and outgroup members (Van Oorschot, 2006). While normative rules are helpful in
evaluating fairness, these rules may lead to contradictions when these theoretical rules are applied
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to real-world scenarios. For example, when an effort-based inequality is partially observed,
whether it is fair is a matter of interpretation based on what was observed (Trump, 2020). As such,
applying a normative rule would contradict a true evaluation when a more whole picture is
available. Understanding the cause of inequalities beyond the surface level can help guide
decisions as to how to correct them in cases that may not be as transparent.
Much of the recent conversation regarding inequality in North America has been about
how we should reduce or rectify past inequalities. Public attitudes toward inequality are
multifaceted and sometimes inconsistent. For example, people may be against income inequality,
but also oppose redistribution of income at the same time (Trump, 2020; Page & Jacobs, 2009;
Gilens, 1999). Some of the ideas put forward to reduce inequality involve offering resources (i.e.
money or land) or opportunities (i.e. free college tuition) today to the descendants of those that
originally experienced the inequality (Coates, 2014; Roos, 2019; Stolberg, 2019). The idea of using
reparations as a means to repair inequalities that exist as a consequence of past inequalities has
been gaining more momentum recently. The intention is that reparations will help restore the
resources that were robbed from them, for example, Africans and African Americans due to slavery
across generations. Those in favour of reparations argue that they are not just a financial and
economic debt that is owed to the descendants, but also a moral debt that needs to be cleared for
the crimes of slavery from 400 years ago (Roos, 2019).
There have been a number of recommendations made as a way to reduce inequality such
as increased insurance programs and employing more liberal taxation systems (Atkinson, 2015).
Ignoring the specific details of such recommendations, most strategies to correct inequalities
involve redistributing monetary resources by transferring wealth from the rich to the poor
(Luebker, 2014). Adult’s beliefs and support for how economic resources should be distributed
underpin many of these political decisions to reduce income inequality. However, Americans are
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not in strong favour of remedying inequalities like this (García‐Sánchez, Osborne, Willis and
Rodríguez‐Bailón, 2020). For example, despite acknowledging income differences between the
rich and the poor, American public opinion shows support for tax-cuts for the rich and opposition
to government spending on social services (García‐Sánchez et al., 2020; Bartels, 2005; Fong,
2001).
It is possible that these conflicting intuitions about how to respond to inequalities may be
based on how people perceive the cause of these inequalities. Those who identify inequalities as
having to do with past wrongs, biases and bad luck, may likely be more inclined to correct the
inequalities. For example, believing that inequality is due to uncontrollable causes such as luck,
prejudice and discrimination garner more sympathy which, in turn, gives rise to prosocial actions
such as giving aid to the poor (Weiner, Osborne, & Rudolph, 2011). As such, individuals’
perceptions of inequality and causes of inequality affect their beliefs about redistribution (Alesina
& Angeleto, 2005; Alesina & La Ferrara, 2005; Kluegel & Smith, 1986). Beliefs that stress internal
and individual factors such as hard work, ambition, and merit as causes of inequality tend to lead
to decreased support for redistribution (Kluegel & Smith, 1986; McCall, 2013; Weiner et al.,
2011). Meritocratic beliefs presumably correlate negatively with redistribution policies because
meritocracy provides a sense of fairness in which the inequality is justified and redistributing
wealth from those who worked hard for it to those who did not is unfair (García‐Sánchez et al.,
2020; Kluegel & Smith, 1986). However, if the inequality came to be through luck, lack of
opportunities, or bias, all external factors one cannot control, this belief elicits more support for
redistribution (Kluegel & Smith, 1986; McCall, 2013; Weiner et al., 2011).
There is also an abundance of evidence that perceptions of the causes of inequality depend
on one’s station in life. For example, a national survey found that wealthier individuals believe
that wealth and poverty depend on an individual’s hard work, talent, and motivation (Kluegel &
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Smith, 2017; Piff, Kraus & Keltner, 2018). Similarly, in another study investigating explanations
of economic inequality, individuals who reported belonging to higher social class rankings were
more likely to characterize economic inequality as arising from hard work and effort (individual
characteristics) and less likely to associate inequality with factors like the economic structure of
society, inheritance, discrimination or political influence (Krause, Piff & Keltner, 2009; Piff, Kraus
& Keltner, 2018). Individuals who believe poverty is a consequence of lack of hard work and effort
also tend to believe that economic inequality is a result of differences in ability and talent, and are
less supportive of wealth redistribution (Piff, Kraus & Keltner, 2018).
Individuals with greater income and higher status have also been found to be less
supportive of government involvement in mitigating inequalities (Piff, Kraus & Keltner, 2018).
According to prior research with publicly available data on legislative bills, wealthier politicians
are more likely to oppose policies such as raising the minimum wage as a means to reduce the
economic inequality (Kraus & Callaghan, 2014; Piff, Kraus & Keltner, 2018). Considering
individuals in upper social ranks associate wealth with merit and support ideologies of
deservingness, they are more likely to act against redistribution of wealth (i.e. through taxation on
the rich, higher minimum wage or universal healthcare; Page, Bartels & Seawright, 2013; Piff,
Kraus & Keltner, 2018).
As outlined thus far, many of the adults involved in discussions about reparations are not
in agreement with how to proceed, as reflected through the many competing policies and
philosophies that have been put forward over time. Disagreements in economic and philosophical
argument tend to be focused on how to fairly rectify inequalities and who is responsible for making
this correction. While adults value fairness and equality, social structures may be lending support
to economic inequality (Piff, Kraus & Keltner, 2018) and to divergence in how we should respond
to inequalities.
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Until now, I have highlighted ways in which political views and self-interest may obscure
the fairness judgments of adults and now, I will review the literature on how children reason about
fairness and inequality. If such a belief exists in children, it may be one of the driving forces in
how children decide to correct inequalities as a result of causes beyond merit. Investigating the
origins of these intuitions in young children will help us understand how we should correct for
inequalities and whether aspects of this debate may be universal early on.
2.2 Infants’ Judgments About Fair Distributions
While children and infants may not be thinking about inequality in terms of the injustices
of slavery, for example, they do make judgments about equal and unequal resource distributions.
Even infants as young as 12 months old can evaluate unequal and equal distributions and make
judgments about the distributers. Geraci & Surian (2011) familiarized two groups of infants, 7- to
12-months and 12- to 18-months, with equal and unequal distributions and analyzed their
expectations for which distributer they predicted an observer to approach. The older infants looked
longer at events which showed the observer approaching the equal distributor, illustrating they are
sensitive to equal distributive outcomes, can evaluate agents based on their fairness in distributive
actions and expect others to like equal distributors. When viewing images of the distributors placed
on a foam board, infants also manually chose the equal distributor in a forced-choice task,
suggesting 12- to 18-month-old infants prefer the agent who distributed an equal number of
resources to the recipients (Geraci & Surian, 2011). While 7- to 12-month-old infants did not look
significantly longer at the equal distributor compared to the unequal distributor, they did reach for
the image of the equal distributor, suggesting they recognized the difference between the different
outcomes of the distribution actions and preferred the equal outcome (Geraci & Surian, 2011).
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These findings illustrate infants can make simple egalitarian evaluations where they expect
everyone to receive an equal number of sources (Geraci & Surian, 2011).
This expectation of equal resource distribution was also observed in infants between 12-
and 15-months-old where they looked longer at unequal distributions between third-party
recipients (Schmidt & Sommerville, 2011; Sommerville & Ziv, 2018). Similarly, 19-month-old
infants also hold such expectations about equal distribution. Sloane, Baillargeon & Premack
(2012) showed 19-month-old infants events in which an experimenter distributes rewards between
two identical animated puppets equally or unequally. Infants in this experiment looked longer at
the unequal distributions suggesting they, too, expect distributors to divide resources equally
between two individuals. While Geraci & Surian (2011) found infants looked longer at events
where a third-party observer approached the equal distributor, in these studies, infants looked
longer at the unfair distributions, suggesting that the outcome violated their expectation of third-
party fairness. As further evidence that infants evaluate others based on their distributive
behaviours, infants associate praise with fair behaviour and admonishment and blame with unfair
behaviour (Deschamps, Eason & Sommerville, 2015) and prefer to socially engage with the
individual who distributed resources equally (Burns & Sommerville, 2014).
Do infants strictly follow this egalitarian rule or are they able to account for the equity
principle in their judgement decisions? Infants start to show they take merit into account at about
21-months. Sloane, Baillargeon & Premack (2012) had 21-month-old infants watch events in
which an experimenter asked two individuals to clean up toys for which they would be rewarded
later. Infants saw one event in which only one of the individuals cleaned up, and another event in
which both individuals cleaned up. Regardless of whether both of the individuals cleaned up the
toys or just one of them, the experimenter gave both of them stickers. Infants looked longer in the
events where just one of the individuals worked to clean up and both individuals were rewarded,
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suggesting while they prefer equal distributions, they expect individuals who worked hard to be
rewarded and expect resources to be divided equally between individuals who worked equally hard
(Sloane, Baillargeon & Premack, 2012). Infants’ expectations for how resources should be
distributed can also be measured within social dominance structures. Enright, Gweon &
Sommerville (2017) habituated 17-month-old infants to videos in which one agent is dominant and
the other is submissive, they then watched equal and unequal distributions. This study provided
further evidence that when given contextual information, infants can forgo their preference for
equal distributions suggesting that, in this case, infants expected the dominant agent to receive
more resources than the submissive agent.
2.3 Children’s Judgments About Fairness and Inequality
Turning to verbal judgments made by older children, a simple distribution with a windfall
of resources via a dictator game has been utilized to explore children’s reactions to inequality. In
this paradigm, children receive a windfall of resources (e.g., stickers) that they can divide between
themselves and another child. Six- to seven-year-old children tend to divide resources equally,
while younger children make more selfish decisions (Benenson, Pascoe & Radmore, 2006;
Hamman, Warneken, Greenberg & Tomasello, 2011; Melis, Altrichter & Tomasello, 2012). In
another study, there was an unequal distribution of resources that was a result of either
collaborative effort, a windfall of resources or individual work and one child had control over
majority of the resources therefore could choose whether or not to equally share the resources with
the other child (Hamman et al., 2012). When both children collaborated on effort and work, 3-
year-old children shared resources more equitably, but when children worked independently or did
not work at all, they did not share equally (Hamman et al., 2011).
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Later in childhood, children begin to negatively evaluate anti-meritorious distributions
(Elenbaas, 2019). In this study, 3- to 8-year-old children judged distributive actions based on
principles of equality, equity, and merit. Children rejected distributions that were inconsistent with
the fairness principles of merit and equity and evaluated them more negatively. With age, children
in this study increasingly disapproved of unfairness where the individual who did not work as hard
or the individual who had more resources to begin with was rewarded with more resources such
as toys and treats. Children also show such a strong aversion to inequity that 6- to 8-year-old
children would prefer to dispose of a resource than only give it to one individual (Shaw & Olson,
2012). Importantly, this study also found that if children are told recipients will receive an even
number of resources no matter how they choose to divide a resource, they do not throw away any
resources, suggesting that throwing away a resource is primarily considered to be an option when
a distribution will produce an inequality.
There is additional work on how children minimize inequality and their reactions to people
affected by inequalities where there is no cause or reason for the inequality. Li, Spitzer & Olson
(2014) showed children a video in which two people distributed resources to two puppets, but one
puppet received more resources, for no apparent reason. They found that 4- to 5-year-old children
were more likely to give additional resources to the puppet who had fewer existing resources in
order to correct the existing inequality between the puppets (Li, Spitzer & Olson, 2014).
Another study aimed to understand whether and when children maintain or reduce
inequalities between members of different social groups (Olson, Dweck, Spelke & Banaji, 2011).
When considering Black and White social groups, 7.5- to 11.5-year-old children rectified the
inequality by providing more resources to new members of the Black social group while 3.5- to
7.5-year-old children preserved the inequality. However, when presented with Asian and White
social groups or novel social groups, across all ages children gave the additional resources to the
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group who had more resources. These results suggest that perhaps the default response when
allocating additional resources is to maintain the inequality and favour the privileged group unless
the resources are to be divided between Black and White social groups. Given that older children
show flexibility in their resource allocation strategy, but only when it involves particular social
groups, there is reason to believe that under certain circumstances, children may be motivated to
attenuate inequalities. In this particular case, the flexibility is likely due to socialization which
prompted older children to override their otherwise dominant strategy to give more to the
privileged groups when the Black social group was disadvantaged with fewer resources.
Similarly, other research has looked into how children judge social inequalities between
racial groups. In one study, 5- to 6-year-old children and 10- to 11-year-old children’s judgments
of societal resource allocations in the face of pre-existing race-based inequalities were measured.
With age and a greater awareness of race-based inequalities, the findings showed older children
evaluated a medical resource inequality when Black Americans were disadvantaged more
negatively than when European Americans were disadvantaged (Elenbaas & Killen, 2016).
Interestingly, the study also found that when European Americans had fewer resources, older
children did not distribute more resources to them and only rectified the inequality when Black
Americans were disadvantaged.
Although children have a baseline preference for equal distributions, in some social
contexts they judge that unequal distributions are acceptable, and even necessary (see Starmans,
Sheskin, & Bloom, 2017 for review). Typically, when children are dividing resources between
others, they follow equality principles, but this principle may conflict with other available context
clues, such as merit and effort, that do not allow for equal distribution of resources. It is when
conflicting information arises (i.e. if one worked harder or if resource allocation is random) that
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children recognize that inequalities may be acceptable given certain conditions (Starmans et al.,
2017).
Additionally, children can overcome their own self-serving bias to be fair. In one study,
Warneken and colleagues (2011) had 3-year-old children work together on a problem-solving task
and looked at their subsequent reward distribution. Interestingly, even though children had the
opportunity in some conditions to reserve the rewards for themselves, they still distributed the
rewards equally, the majority of the time, between themselves and their partner. Furthermore, the
distribution of rewards between the partners did not involve conflict and the children distributed
resources spontaneously, showing a sophisticated understanding of equitable outcomes based on
shared work. In another study, 3- and 5-year-olds worked with a puppet-partner to collect coins
which they could exchange for rewards at a later time. When children contributed less compared
to their puppet-partner, they kept fewer rewards, suggesting young children not only consider
whether someone worked or not, but also how much one person worked relative to another when
dividing resources between themselves and a partner (Kannigiesser & Warneken, 2012).
Children can also identify two aspects of merit: one’s effort (hard work), and also the
outcome of one’s effort (the product of hard work). In the coin-collecting study described above,
children recognized when someone worked harder because they had more coins to show for it, and
accordingly judged that they were entitled to more rewards for their hard work (Kannigiesser &
Warneken, 2012). However, there are situations when contributions of effort do not necessarily
correspond with the outcome and, with age, children are able to incorporate this when making
decisions about how resources should be divided (Noh, D’Esterre & Killen, 2019). When effort
and outcome conflicted (i.e. high effort, low outcome vs. low effort, high outcome), 7- to 10-year-
old children showed a preference for the hard-working individual with age and showed decreasing
weight on outcome (Noh, D’Esterre & Killen, 2019). Older children also emphasized effort in their
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open-ended responses, noting that while they recognized one individual had a high outcome, they
were less deserving of rewards because they did not work hard. Similarly, when effort varied, but
outcome was controlled, 7- to 10-year-old children used effort when making decisions about
resource distribution (Noh, D’Esterre & Killen, 2019).
By 6 years of age, children also consider merit when distributing luxury or necessary
resources (Rizzo, Elenbaas, Cooley & Killen, 2016). While 3- to 5-year-olds did not differentiate
between luxury and necessary resources and preferred equal distributions between individuals, 6-
to 8-year-old children distributed luxury resources more meritoriously than necessary resources
by giving more luxury resources to individuals who worked harder. This suggests children not
only consider an individual’s merit, they also consider the consequences of distributing a certain
type of resource on the individual’s welfare.
While much of the prior work has focused on how children reason about inequalities
between specific social groups, or inequalities due to merit, little is known about the way children
reason about other reasons for inequality. How do children reason about inequalities caused by
bias and luck? Do children consider the cause of inequalities when reasoning about whether and
how to rectify existing inequalities? And, given that many real-world inequalities originate in the
distant past, how do children respond to inequalities created in the distant past? All else being
equal, both, children and adults, strongly prefer equal distributions (Deutsch, 1975; Fehr &
Schmidt, 1999; Shaw & Olson, 2012; Olson & Spelke, 2008). However, when it comes to
inequalities that happened in the past or inequalities as a result of a particular cause, equal
distribution of resources may not be the best response. As adults, we have conflicting intuitions
about how to approach and remedy past inequalities particularly with what ought to be done versus
what should be done. One caveat with understanding how adults reason about inequalities is that
they may be biased by their own political affiliation and self-interest. As such, to explore genuine
14
intuitions about whether or how to correct for inequalities we turn to children, who are not yet
exposed to such biases. While children have strong preferences for equal distributions, so much so
that they when equality has been violated, they will restore it (Shaw & Olson, 2012), the literature
has yet to address how they judge past inequalities and inequalities due to bias and luck. In this
thesis, I will explore children’s reasoning about whether and how to rectify inequalities that were
created through merit, bias, or luck, and investigate how their judgments are affected by the
recency of the inequality.
Chapter 3 Experiment 1
Experiment 1 explored how children reason about inequalities created by a third party, either due
to a difference in merit, because of bias, or through a lucky break, by giving children the
opportunity to correct the inequality with additional resources.
3.1 Method
Participants
Eighty children, ranging in age from 5- to 8-years-old, completed the study. Participants
were recruited at local community events, parks and through a participant database (40 5- to 6-
year-olds, 50% female, mean age: 71.95 months; 40 7-to-8-year-olds, 41% female, mean age: 94.9
months). An additional 15 children were tested, but were excluded for experimenter error (11) or
failed comprehension (4). The procedure was approved by REB at the University of Toronto,
parents provided their consent to have their children participate and children gave their assent to
participate. Children received a toy for participating in the study.
Procedure
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The study took place at the child developmental lab at the University of Toronto, local
parks, and community centres. Parents were informed of the study details and consented to their
children’s participation. Once consent and assent had been given and the child was comfortable to
continue, an experimenter took the child to another room (in lab) or to an isolated area nearby
(parks and community centres) for testing.
In each of three trials, participants were presented with pictures of two children who had
unequal amounts of money (see Figure 1). The reason for the inequality was described, and, across
conditions, was due to either merit, bias, or luck. Children were randomly assigned to one of three
counterbalanced orders (within-subjects). The three pairs of children used as stimuli in the study
were roughly of European descent and male. All stories described pairs of children who had helped
their teacher clean up after school that day and their teacher had given them some money.
Figure 1. Stimuli and respective stories for each condition (Merit, Bias, and Luck) which were
presented to participants in a counterbalanced order. The bolded terms signify the cause of the
inequality.
In the Merit condition, participants were told that one of the children worked harder to
clean up so the teacher gave him $10, while the other child did not work as hard to clean up, so
the teacher only gave him $5. In the Bias condition, participants were told that both children
16
worked equally hard cleaning up, but the teacher gave one child $10 because she liked the colour
of his t-shirt, and gave the other child $5 because she did not like the colour of his t-shirt. Finally,
in the Luck condition, participants were told that both children worked equally hard, but the teacher
pulled out one child’s name out of the hat first so she gave him $10 whereas the other child’s name
was pulled out of the hat second so the teacher only gave him $5.
After participants were told about how the teacher distributed the money and why, they
were asked comprehension questions about who had more money and why he had more money. If
participants did not answer these questions correctly, the experimenter corrected the participant
and asked the comprehension questions a second time. If they got it wrong a second time, their
data were excluded. Following the comprehension questions, participants were told there was an
additional $4 and they could choose how they wished to divide the extra money between the
children. Finally, participants were asked to provide an open-ended explanation for why they chose
to distribute the additional $4 in the way that they did.
3.2 Results
We conducted a 3(Condition: merit; bias; luck) X 2(Age Group: Younger Children (5- 6-
year-olds); Older Children (7- to 8-year-olds) repeated measures ANOVA with Condition as a
within-subject variable and Age Group as a between-subjects variable. The dependent variable
was how many coins participants gave to the poor child (i.e., the child who started with fewer
coins). There was a main effect of Condition, F(2,78) = 16.71, p < .001, η2 = .18, whereby children
gave more to the poor child in the Bias, t(79) = -5.136, p < .001, and Luck, t(79) = -4.408, p <
.001, conditions than in the Merit condition. Children did not significantly differ in whether they
gave more to the poor child in the Bias and Luck condition, t(79) = .385, p = .701. There was no
main effect of Age Group, F(1,79) = 1.53, p = .221, η2 = .02, but there was a significant interaction
17
between Condition and Age Group, F(2,78) = 9.93, p < .001, η2 = .113 (see Figure 2), which we
explored further by examining each age group separately.
Figure 2. Average number of coins (0-4) distributed to the poor child by both age groups across
the Merit, Bias, and Luck conditions. Error bars represent standard error of the mean.
For younger children, there was no main effect of Condition F(2,38) = 1.25, p = .293.
Participants in this age group distributed an equal number of coins to the poor child (MMerit = 1.78,
MBias = 1.9, MLuck = 2.15) regardless of why he had less money, t(39) = -1.380; -.746; .713, all p
values > .176.
Older children’s distributions showed a main effect of Condition, F(2, 38) = 32.43, p <
.001, whereby participants gave more coins to the poor child in the Bias condition, M = 2.83, than
in the Merit condition, M = 1.33, t(39) = -7.19, p < .001, and also gave more coins to the poor
child in the Luck condition, M = 2.40, than in the Merit condition, t(39) = -5.36, p < .001.
Participants were also more likely to give more coins to the poor child in the Bias condition than
in the Luck condition, t(39) = 2.60, p = .013.
0
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One sample t-tests against the chance level of 2 (representing equal distribution of coins)
revealed that older participants gave more than half of the coins to the poor child in the Bias
condition, t(39) = 4.71, p < .001, and the Luck condition, t(39) = 2.29, p = .028, but gave
significantly less than half of the coins to the poor child in the Merit condition, t(39) = 4.97, p <
.001.
Discussion
Our results demonstrated that younger children distributed resources equally when they
were given the opportunity to correct a pre-existing inequality, whereas older children distributed
resources unequally. In the Merit condition, an unequal distribution of the resources actually
increased the existing inequality, which can be explained by older children’s desire to reward those
who work hard. However, in the Bias and Luck conditions, we found that older children distributed
more resources to the child who was biased against or unlucky, presumably as a way to correct the
pre-existing inequality. It seems that equality was a driving force in young children’s distribution
allocations while that did not appear to motivate older children in their resource allocations. The
findings with the older children suggest that 7- to 8-year-old children negatively evaluated the
inequalities produced by bias and luck, and positively evaluated the inequality created by merit.
Chapter 4 Experiment 2
Economic inequalities that exist in modern-day North American societies were created over time
with the cause of the inequalities originating long in the past. Experiment 1 revealed how children
reason about present-day inequalities, but it is unclear how they reason about inequalities that
originated long before their current distribution decision. To explore this question, Experiment 2
19
proceeded in the same way as Experiment 1 except in that the inequalities were described as having
happened a year in the past. Do children consider the passage of time when evaluating whether
and how to correct for existing inequalities?
4.1 Method
Participants
Eighty children, ranging in age from 5- to 8-years-old, completed the study. Participants
were recruited through online advertisements and through a participant database (40 5- to 6-year-
olds, 60% female, mean age: 72.4 months; 40 7-to-8-year-olds, 35% female, mean age: 95.2
months). An additional 15 children were tested, but were excluded for failing comprehension
questions (14) or parental interference (1). The procedure was approved by REB at the University
of Toronto, parents provided their consent to have their children participate and children gave their
assent to participate. Children received a $5 Amazon gift card or the option to enter a draw to win
a $25 Amazon gift card for participating in the study.
Procedure
The study took place online through Zoom Video Conferencing. Before the study, parents
were emailed study details, online testing details, and a consent form. While on the video
conference call with the experimenter, parents verbally consented to their children’s participation
and children verbally gave their assent to participate. Once consent and assent had been given and
the child was comfortable to continue, the experimenter shared their screen to display the study
materials, presented via Qualtrics.
The procedure was similar to Experiment 1, except that to help children think about “last
year”, they were asked to confirm their age now, the current season, and how old they were last
year in this season. Children again saw photos of three pairs of children, chosen to roughly match
20
the age of the each age groups (see Figure 3). The order in which children viewed the trials was
randomized by Qualtrics. The pairs of children used as stimuli in this experiment were roughly of
European descent and male. All trials described pairs of children whose teacher gave them unequal
amounts of money after they helped clean up after school one year ago and which child had been
given less money was counterbalanced between participants.
Figure 3. Stimuli and respective stories for each condition (Merit, Bias, and Luck) which were
presented to participants aged 5- to 6-years-old in a counterbalanced order. Older children aged 7-
to 8-years-old, were presented with the images used in Experiment 1 as those stimuli more closely
represented that age group. The bolded terms signify the cause of the inequality that happened one
year ago.
In the Merit condition, participants were told that one of the children worked harder to
clean up last year, so the teacher gave him $10, while the other child did not work as hard to clean
up, so the teacher only gave him $5. In the Bias condition, participants were told that both children
worked equally hard to clean up last year, but the teacher gave one of them $10 because she liked
the colour of his pants, and only gave the other child $5 because she did not like the colour of his
pants. Finally, in the Luck condition, participants were told that both children worked equally hard
21
last year, but the teacher pulled out one child’s name out of the hat first so she gave him $10
whereas the other child’s name was pulled out of the hat second so the teacher only gave him $5.
After participants were told about how the teacher distributed the money and why, they
were asked comprehension questions about who had more money, why he had more money and if
the children worked equally hard last year or if one worked harder. If participants did not answer
these questions correctly, the experimenter corrected them and asked the comprehension questions
a second time. If they got it wrong a second time, their data were excluded. Following the first set
of comprehension questions, participants were told that the children worked equally hard in the
present and that the amount of money they have in the present is equivalent to the amount of money
their teacher had given them a year ago: “This is how much money they have from last year. Now
I’m going to tell you what happened today. Today, both Alex and Jeff helped their teacher paint
the classroom walls. Alex painted 2 walls, and Jeff also painted 2 walls. They both worked equally
hard today.”. Participants were asked another comprehension question about whether the children
worked equally hard in the present or if one worked harder. If they got this comprehension question
wrong once, they were corrected by the experimenter, and if they answered incorrectly a second
time, their data were excluded. Finally, participants were told there was an additional $4 and they
could choose how they wished to divide the extra money between the children. After they had
distributed the money, participants were asked to provide an open-ended explanation for why they
chose to distribute the additional $4 in the way that they did.
4.2 Results
As in Experiment 1, we conducted a 3(Conditions: Merit; Bias; Luck) X 2(Age Group:
Younger Children (5- to 6-years); Older Children (7- to 8-years)) repeated measures ANOVA with
Condition as a within-subject variable and Age Group as a between-subjects variable. The
dependent variable was how many coins participants gave to the poor child (i.e., the child who
22
started with fewer coins). There was a main effect of Condition F(2,78) = 7.02, p = .001, η2 = .083,
whereby children gave more coins to the poor child in the Bias, t(79) = -3.324, p = .001, and Luck,
t(79) = 2.778, p = .007, conditions than in the Merit condition. There was no significant difference
in the number of coins that were distributed to the poor child in the Bias condition and in the Luck
condition, t(79) = .560, p = .577. There was no main effect of Age Group, F(1,79) = 1.04, p = .310,
η2 =.013. There was also no significant interaction between Condition and Age Group F(2,78) =
.129, p = .879, η2 = .002 (Figure 4), but because we found different results for each age group in
Experiment 1, we examined each Age Group separately in Experiment 2 as well for consistency.
Figure 4. Average number of coins (0-4) distributed to the poor child by both age groups
across the Merit, Bias, and Luck conditions. Error bars represent standard error of the
mean.
For younger children, there was no main effect of Condition, F(2,38) = 1.97, p = .147, η2
= .048. Participants in this age group distributed an equal number of coins to the poor child
0
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regardless of the cause of the inequality that happened a year ago (MMerit = 2.05, MBias = 2.45,
MLuck = 2.38).
Older children’s distributions showed a main effect of Condition, F(2,38) = 6.972, p =
.002, η2= 1.52, whereby participants distributed more coins to the poor child in the Bias condition,
M = 2.65, t(39) = -3.20, p = .003, and the Luck condition, M = 2.60, t(39) = 3.05, p = .004 than in
the Merit condition, M = 2.15. Participants gave equally to the poor child in the Bias and Luck
conditions, t(39) = .36, p = .720.
One sample t-tests against the chance level of 2 (representing equal distribution of coins)
revealed that older children gave significantly more than half the coins to the poor child in the
Bias, t(39) = 4.33, p < .001, and Luck, t(39) = 4.216, p < .001, conditions, but their distributions
did not differ from chance in the Merit condition, t(39) = 1.00, p = .323.
Discussion
There was no main effect of condition with the younger children; they distributed an equal
number of coins to the poor child across all conditions. However, there was a main effect of
condition with the older children. Older children distributed an equal number of coins between
both children in the Merit condition, but gave more coins to the poor child in the Bias and Luck
conditions. Older children’s responses in the Merit condition suggest that in the present where
children’s hard work is described as being equal, they are dividing the coins equally between the
pair suggesting they might not have evaluated the past inequality as an unfair inequality, but rather
just a method of rewarding those who work hard. With respect to the Bias and Luck conditions,
older children gave more than half the coins to the poor child in these conditions suggesting that
they wanted to correct the past inequality.
24
Although we found the same overall pattern of results for both age groups in Experiment
1 and Experiment 2, the older children were overall more likely to correct inequalities that
happened in the present (Experiment 1) than in the past (Experiment 2; see Figures 2 & 4). This
set of findings with older children suggests that whether the inequality occurred in the present or
the past may have an effect on children’s judgments of whether and how to correct the inequalities.
They are seemingly less motivated to correct existing inequalities when they were created in the
past. However, there is a need for caution when comparing the results of Experiment 1 and
Experiment 2 because children were not randomly assigned to conditions, and because Experiment
1 was conducted in the lab, while Experiment 2 was conducted online.
Chapter 5 General Discussion
Two experiments examined how children reason about the cause of inequalities and the
amount of time that has passed as they evaluate whether to correct existing inequalities. In
Experiment 1, younger children tended to distribute coins equally regardless of the cause of the
inequality while older children were sensitive to the reason for the existing inequality. When the
existing inequality was due to one child working harder, older children gave more coins to the rich
child, thus increasing the inequality, however, they gave more coins to the poor child in the Bias
and Luck conditions, thus reducing the inequality. Experiment 2 found that as in Experiment 1,
younger children tended to distribute coins equally in all conditions and older children again
considered the cause of the inequality. When the pre-existing inequality was due to one child
working harder a year ago, but the children were described as working equally hard in the present,
older children distributed coins equally. However, they gave more coins to the poor child in the
Bias and Luck conditions thereby reducing the pre-existing inequalities from a year ago.
25
Overall, these findings suggest that younger children have strong preferences for equal
distributions despite existing inequalities while older children distribute present-day resources
unequally to address past inequalities caused by bias or luck. Our observations with younger
children in Experiment 1 and Experiment 2 show the same pattern of results in which they
distribute an equal number of resources to both children regardless of the cause of the inequality.
This suggests that their distributions were based on their desire to distribute current resources
equally between two individuals, rather than to correct the existing inequality. Given younger
children’s preference for equal distributions in these experiments, they do not seem to be sensitive
to causes of the inequalities. Children’s tendency to perform equity-based distributions rather than
allocate based on equality increases with age (Hook & Cook, 1979; Peterson, 1983), but these
previous studies did not have existing inequalities prior to the new resource distribution. When
there is an existing inequality due to a windfall of resources, 5- to 6-year-old children show a
preference for equal outcome after the distribution (Hayashi, 2019). Though one thing to note that
is different compared to our experiments is that an equal outcome through unequal allocation was
possible in this study, but not in our experiments. Perhaps when there is an existing inequality, at
this age, if children are not able to produce an equal outcome through a resource allocation, they
default to equal allocation where everyone receives an equal number of resources.
The same observations in Experiment 1 also show that by age 7, children accept an
inequality if they evaluate it to be fair and will distribute resources unequally if it means that the
distribution will rectify a pre-existing inequality due to bias or luck. Older children increased the
pre-existing inequality in Experiment 1 by distributing more coins to the child who worked harder
further showing their flexibility with inequality under certain conditions. As such, older children
in Experiment 1 accounted for the cause that produced the inequality in the first place, and based
on the cause, they either corrected the existing inequality or increased it. In the Merit condition
26
where one child worked harder than the other, older children gave him more coins and increased
the inequality. It is possible that participants gave more coins to the rich child because he was
described as having worked harder today so children were distributing the coins based on
principles of merit. In the Bias condition where one child has been biased against resulting in him
having less money, it is possible that older children gave more coins to the poor child because
they wanted to correct the inequality that was a consequence of non-individual traits (i.e. the
teacher’s dislike of his t-shirt colour). This may also explain older children’s unequal distribution
of coins in the Luck condition: they gave more to the poor child as his wealth was determined by
chance. Their distributions seem to rely on their understanding of how a particular inequality came
to be which they then use to make distributions that will correct it if they see fit (i.e. in the Bias
and Luck conditions) or keep the inequality as is like they did in the Merit condition. By this logic,
older children increasing the inequality in the Merit condition is justified seeing as they distributed
the coins based on who worked harder and evaluated their unequal distribution as fair.
Furthermore, when the inequality was described to have happened a year ago in
Experiment 2, younger children distributed coins equally again across all conditions. Our data
from Experiment 2 revealed that when an inequality occurred in the past, older children gave
significantly more than half the coins to the poor child in the Bias condition (who was biased
against last year) and in the Luck condition (who was unlucky last year) as a way to reduce the
inequality. However, they distributed resources equally to the poor child and the rich child in the
Merit condition, possibly because they worked equally hard on the present day. This demonstrates
that children are not only evaluating which inequalities are unfair, but also using this evaluation to
correct an inequality by distributing resources unequally.
27
Compared to younger children, the data show support for older children’s sensitivity to
causes of inequality. We found that older children gave an equal number of coins to both children
in the Merit condition but distributed more coins to the poor child in the Bias and Luck conditions.
In the Merit condition, while one child worked harder a year ago and received more money as a
result, in the present day, both children worked equally hard and this equal input of work may
explain why older children distributed money equally. They distributed the coins based on
principles of merit possibly because they recognized that the original inequality was due to
differences in merit and if in the present, both children contributed equally, the same principle
governs equal distribution of coins in the present hence they distributed equally between the
children. However, in the Bias and Luck conditions, they gave more coins to the poor child
suggesting they recognize the disadvantages that arose as a consequence of an unfair past
inequality, and are thus motivated to distribute present-day resources unequally, favouring the poor
child, to reduce the inequality. Their motivation to distribute resources unequally to reduce the
inequality may be driven by adding together past experiences and current experiences in both
conditions. This addition of past and current experiences leads to a summation of disadvantages
related to the inequality over time for the poor child, As such, children may. distribute the coins to
favour the poor child who was biased against and unlucky given that the total inequality is larger.
In line with previous research that found that children negatively evaluate distributions that
go against the principles of equity and merit (Elenbaas, 2019; Rizzo et al., 2016), older children in
both Experiment 1 and 2, distributed resources in such a way that shows they are sensitive to the
causes of inequality. Interestingly when there was a difference in merit in the present, they
distributed more coins to the rich child (i.e the one who worked harder), but when the difference
in merit was in the past and both children worked equally hard in the present, they distributed coins
based on present-day contextual information. Whereas, in the Bias and Luck conditions, children
28
distributed more coins to the poor child both when the inequality happened in the present and in
the past. While older children show a sensitivity to causes of inequality, they are seemingly more
sensitive when the inequality happened in the present than when it happened a year ago. It could
be that the passage of time reduces the apparent inequality and when children look to reduce
inequality, they are more sensitive to its consequences in the present. Regardless, this is consistent
with what has been found in previous studies: with age, children become more aware of
inequalities and better at making decisions that have to do with correcting inequalities. For
example, one study looked at children’s societal resource allocation decisions in the presence of
pre-existing inequalities. Elenbaas & Killen (2016) had children evaluate how acceptable a race-
based medical resource inequality was, judge resource allocation strategies, and distribute medical
resources thereby providing evidence for their concerns about fairness. With age, children become
more aware of differences in wealth status, and older participants in this study judged inequalities
in this social context more negatively, and were more likely to reduce the inequality, when it
disadvantaged African-American children. While our experiments did not look at inequalities
more broadly like medical resource inequalities, this study and our study provide evidence that
older children are sensitive to causes of inequality and factors related to inequalities so much so
that they distribute resources unequally to reduce the inequalities.
While 7- to 8-year-olds seem to be sensitive to the reasons for pre-existing inequalities
when deciding how to distribute resources, both experiments found that 5- to 6-year-old children
distribute resources equally between children regardless of the cause of inequality. However,
previous research has found that 5- to 6-year-old children will distribute resources unequally in
order to rectify pre-existing inequalities under some circumstances. Specifically, in one study
(Rizzo & Killen, 2016), children were told stories about two recipients from either a wealthy town
with a lot of resources or a poor town with no resources and children from both towns worked to
29
produce an equal amount to control for the influence of merit. Children were asked to allocate
resources and judge their distributions as equal/unequal or equitable/inequitable. The results
showed that 5- to 6-year-old children rectified inequalities while also judging both equal and
equitable allocations as fair.
One way in which our experiments differ from this study, and therefore perhaps led to our
5- to 6-year-olds distributing resources equally across all conditions, could be due to the source of
the pre-existing inequality. In our experiments, a teacher intentionally distributed resources
unequally (based on merit, bias, and luck), while previous work has described inequality as
stemming from different contextual circumstances (i.e., from living in a wealthy town or a poor
town). This difference in 5- to 6-year-old children’s responses to correcting inequalities could be
due to there being a reason given for the original inequality in our Experiments whereas the cause
of the inequality in the other study is not explicitly known. Young children still show a preference
for equal allocation of resources as they judged equal distributions as fair despite distributing
resources unequally to reduce the inequality (Rizzo & Killen, 2016). With that being said, similar
to our findings, Rizzo & Killen (2016) also report age-related differences for which allocations are
judged as fair: 7- to 8-year-old children distributed the resources based on equity and did not
evaluate equal distributions as fair. Our findings agree with the age differences observed in fair
distributions (Rizzo & Killen, 2016), even though younger children distributed resources equally
in our study.
Relatedly, another study examined 4- to 5-year-old children’s’ responses to minimizing
inequalities and favouring advantaged people (Li, Spitzer & Olson, 2014). While children judged
advantaged people more positively, they also distributed a resource to the individual disadvantaged
by the pre-existing inequality. We see this in our findings where older children distributed
30
resources based on their evaluation of the cause of the inequality. They did not simply give more
resources to the poor child in all conditions, but distributed based on who was disadvantaged by
the inequality. Younger children in our Experiments distributed resources equally and did not show
motivation to correct the inequality, though. It is possible that this discrepancy may also be due to
the cause of the inequality where it is seemingly without cause in this study. Additionally, when
there is a delay between when children observed the inequality and when they allocated the
resources, they favoured the advantaged individual, possibly because they had forgotten whom the
inequality favoured. This could speak to the time difference manipulation we did between the two
Experiments: when the inequality is pushed to the past, older children marginally distribute
resources favouring the disadvantaged child suggesting that passage of time, like the delay in the
previously described study, influences distribution of resources.
Interestingly though, one study found that 6- to 8-year-old children would rather discard
an additional resource than make an unequal distribution and that this inequity aversion also
extends to throwing away a resource they could have kept for themselves (Shaw & Olson, 2012).
While these findings are revealing of children’s intuitions about equitable distributions when all
else is equal, our findings extend children’s reasoning of more complex fairness distributions
because we introduced pre-existing inequalities due to either merit, bias or luck, and then asked
children to make third-party resource distributions. Our findings show flexibility from children’s
preferences to avoid inequality considering that under certain circumstances, children proceed with
inequitable distributions unlike children’s reactions to inequity in the previous study described
above.
When all things are not equal (i.e. there is a difference in merit or effort), children’s
responses to resource distributions differ from equal allocation preferences. With age, children
tend to distribute more resources to someone who was more meritorious, presumably because they
31
evaluate merit-based allocations as more deserving (Kienbaum & Wilkening, 2009). Older (7- to
8-year-old) children judge that individuals who contribute more or work harder deserve more
resources and that this is an acceptable enough reason to not distribute resources equally (Noh,
2017; Baumard et al., 2012; Schmidt, Svetlova, Johe, and Tomasello, 2016). In line with these
findings, our studies also support for merit-based resource distributions with older children. In
Experiment 1, older children distributed more coins to the rich child who also happened to have
worked harder than the poor children, and in Experiment 2, older children distributed resources
equally between both children because they were described as working equally hard.
Much of the prior research on children’s understanding of inequality and unfairness has
examined judgments about merit. In these studies, children judge that individuals that work hard
deserve more, and individuals that are lazy do not deserve the same number of resources (Elenbaas,
2019; Rizzo et al., 2016; Worle & Paulus, 2018). Little previous work has examined the way
children judge other reasons for inequality such as bias and luck. Taken together, these findings
show that depending on the cause of the inequality, children have different views about how to
correct them. Our data not only speak to children’s ability to understand different causes of
inequalities and when the inequality happened, but also that children use these factors to correct
inequalities by producing unequal distributions despite their preference for equality. Specifically,
we find evidence that with age, children become more likely to employ distributions that will
correct unfair inequalities. These findings are in line with prior research demonstrating that
children negatively evaluate anti-meritorious distributions (Elenbaas, 2019; Rizzo et al., 2016),
but extend these findings to explore how children reason about inequalities produced by mitigating
factors other than merit: bias and luck.
Taken together, these findings suggest that younger children have strong preferences for
equal distributions despite existing inequalities, while older children distribute present-day
32
resources unequally to address past inequalities caused by bias or luck. We see that older children
were more motivated to minimize an inequality when it happened in the present and see this effect
when the inequality was moved to the recent, but to a lesser degree. It could be that the passage of
time between when the inequality first happened to when we are asking children to address it leads
to this dampening of effect and that they are not as motivated when it happened in the recent past.
Future research might extend this work by examining inequalities between children as a result of
their parents’ wealth—that is, inequalities that were created a generation ago (i.e. increasing the
passage of time even more). If inequality of wealth between the children is a result of their parents
working differing amounts, or of bias against their parents, or their parents' lucky break, will
children consider these causes when deciding how to distribute present-day resources?
Our current findings revealed that older children gave more money to the poor child in the
Bias and Luck conditions seemingly because the inequality was to do with factors beyond the
children’s control, while giving more to the rich child in the Merit condition because he worked
harder. In line with these findings, one possibility is that since inequality due to parents’ hard work,
bias, or luck does not have to do with factors or traits related to the children, participants may
choose to distribute more money to the poor child because his disadvantage is a result of his
parents. Another possibility is that for the same intuition, the inequalities are a consequence of
factors and traits at the parent level, children may treat the extra coins as a separate distribution
and distribute the coins based on the equal-allocation principle: divide the money equally between
both the rich and poor child. Finally, children may distribute the coins based on the hard work,
bias, or luck that befell the parents, in which case, the distributions would look similar to the results
from Experiments 1 and 2.
Fairness and equality are not necessarily synonymous with each other and it is not the case
that resources should be split equally under all conditions. There are instances in which one must
33
produce an inequality to be fair to those involved. Both adults and children avoid unequal
distributions of resources (Shaw & Olson, 2012; 2013), but there are some social contexts in which
unequal distributions are acceptable and even desirable for both children and adults because they
represent fair outcomes (Starmans, Sheskin, & Bloom, 2017). This thesis investigated whether and
how children consider the cause of the inequality, and when the inequality arose, when they are
considering whether to correct pre-existing inequalities. Taken together, the findings suggest that
younger children have strong preferences for equal distributions despite existing inequalities,
while older children distribute present day resources unequally to address past inequalities caused
by bias or luck. More broadly construed, the intuitive ability for children to understand fairness,
inequality and ultimately the importance of reparations will help inform how we approach and
rectify inequities as adults in our day to day lives. The developmental origins of judgments about
when and whether to rectify existing inequalities is a question which feeds into real world decisions
about long-standing inequalities having to do with class, race or gender.
34
35
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Copyright Acknowledgements