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)

ii

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.

iii

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

1

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

4

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

5

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 &

6

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.

7

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).

8

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,

9

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

12

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

13

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

15

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.

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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

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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

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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

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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

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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