Argentina_Research

Arnold Mitchem Fellows Program 1
Arnold Mitchem Fellows Program
Uncovering Attitudes and Perceptions of Discrimination in Argentina
Sydney Sewell
DePaul University

Abstract
This study examines skin color discrimination in Argentina in three different ways:
one, examining if participants experience discrimination based on their skin color
alone; two, if participants face discrimination based on their skin color and
backgrounds of educational levels; and three, to test if participants face
discrimination based off their complexion and socioeconomic status. In the end, this
study wants to examine if skin color is trying to mediate the two in regard to
discrimination. In order to effectively introduce the phenomena of skin color
discrimination regardless of ones’ educational background and socioeconomic
status, this paper will generalize the problem through the United States’ lenses.
While previous research suggests that Blacks in the United States face
discrimination no matter their educational and socioeconomic background, there is
a lack of information given if the same issue is occurring in other parts of the world
where slavery existed, for example, Argentina. In order to test the phenomena in
Argentina, 405 participants are surveyed based on background questions about the
participants and questions pertaining to discrimination. The data is then measured
by two dependent and three independent variables. The data collected showed that
skin color in Argentina is not a main factor to receive discrimination, but rather the
participants’ class and educational levels. Because skin color alone is not a
determining factor for discrimination in Argentina, it shows that the Black
experience, or those of a darker complexion, is truly an experience tailored to the
United States.

The Context of Discrimination in the United States
I have always believed that Black/African Americans are the biggest targets
of discrimination in the United States. Dryer (2007) argues, “That Blacks
[oppression] carries a weight heavier than any other minority group because it
insinuates inferiority because of race,” (p.1). Blacks have been and will continue to
be outcasts in society simply because they are Black; therefore, in order to
understand why other minority groups are discriminated against, I would argue that
we should turn to Black history. Being Black has been deemed as filthy, unwanted,
and ugly, thus anyone who appears to have any signs of Blackness in them, for
example, darker skin, kinky hair, large lips, or a wide nose, they are open to
potentially facing discrimination (Russel-Cole, Hall, & Wilson, 2013). However, why
do these heinous depictions of Blacks exist? Well, I would believe the answer is
quite simple, slavery.
The first step to understanding Black American history is through the
peculiar institution of slavery. As a consequence of slavery, Blacks will continue to
struggle because of the stigma associated with slavery (Collins, 2000). Because of
this grave issue, scholar Robin M. Boylorn (2006) believes that Blacks are
“unprotected from the consequences of our race, consequences that are often
dismissed or overlooked,” (656). There are a myriad of ramifications that come from
slavery; for example, not being seen as aesthetically beautiful or having to work
twice as hard to get half as far (DeSante, 2013). While these consequences make up

an integral part of the unpleasant Black experience, I believe discrimination is a
permanent ramification that plagues Black/African American experience in the
United States.
First, in order to fully comprehend discrimination, it is vital to know an
appropriate definition of discrimination. The Merriam-Webster dictionary defines
discrimination as:
“The practice of unfairly treating a person or group of people differently from
other people or groups of people; the ability to recognize the difference
between things that are of good quality and those that are not; and the ability
to understand that one thing is different from another thing.”
Therefore, discrimination is something designed to specifically set groups
apart. I will introduce how discrimination divides Black and White Americans not
only because of skin color, but through education and socioeconomic status as well.
This will segue into my research question and the main focus in this paper.
The Various Forms Discrimination Takes in the United States
Skin color is an easy target for discrimination to be revealed. The United
States has an ugly history in regard to skin color discrimination, specifically the
Black and White American dynamic. Jones (2000) argues that skin color categories
on the basis of White and Black has social meaning in the United States; if one is
White, they are associated with psychological and economic advantages compared
to Blacks who are stuck at the bottom of the socioeconomic hierarchy. Because of
this heinous stigma, Blacks are discriminated against simply because they are Black.

While this issue can be an entire paper in itself, I will not go into grave detail about
skin color discrimination on a White versus Black basis. However, if we reflect back
fifty years ago to the malevolent Jim Crow laws, we can see the clear act of skin color
discrimination: Blacks had to sit at the back of the bus, Blacks could not attend the
same schools as Whites, and Blacks were even killed for whistling or even looking at
White women like Emmit Till (Thorton, 2010). While many would argue much of
this was a problem concerning segregation, I would argue segregation would not
have come about if it were not for discrimination!
Because skin color discrimination in the United States is a prevailing topic,
for this paper, I want to examine educational levels and class by adding skin color to
mediate the two. It is already known that if you’re Black and uneducated or Black
and poor, discrimination will be perceived. However, what if Blacks come from a
background with higher levels of education or have a college degree or higher
themselves? Do they still face discrimination? Boylorn (2006) believes that Blacks
have it harder as they seek or receive higher levels of education because of the
permanent negative assumptions and stigmas from the peculiar institution of
slavery. For example, White students always “observe” Blacks students’ hair and
music because it comes across as “deviant,” (Boylorn, 2006). Basically, no matter
what a Black student does in a higher educational setting, they are always
questioned and discriminated against simply because they are Black. Also, Boylorn
(2006) found that Black students are constantly stressing over if their professors

are evaluating them on their merit or their Blackness. Some Blacks students find
their professors’ believing they are “ignorant” or “incapable” of learning (Fischer et
al., 1996; Hernstein & Murray, 1994). It is clear that even though a Black individual
has higher levels of education, discrimination does not vanish from their lives.
Is it the same pattern for Blacks and socioeconomic status? While the Oprah
Winfrey discrimination case in Switzerland may not be an accurate portrayal of the
Black upper and middle classes in the United States, let’s take a look at the Black
upper and middle class through other reasonable examples. The Black upper and
middle class is constructed of Black Americans who work high paying white collard
jobs (Feagin & Sikes, 1994). Feagin and Sikes (1994) interviewed Black upper and
middle class individuals to understand their experiences with discrimination.
Overall, while many think that Blacks have it good once they work their way up into
society, Feagin and Sikes (1994) uncover that Blacks in the upper and middle class
socioeconomic hierarchy face the same amount of discrimination as those who have
lower socioeconomic statuses.
Even though this was a brief introduction into discrimination in the United
States based on education and socioeconomic levels mediated by skin color, it gives
an accurate depiction that discrimination is far from eradicated in the United States.
It does not matter a person’s color, educational background, or socioeconomic
status, discrimination in the United States will plague them, specifically Black
Americans. While this phenomena is known about the United States, it would be
interesting to uncover if this same issue exists in other countries because this issue

of skin color politics and skin color based discrimination is a wide-spread problem
across the globe, specifically in areas that were colonized by Europeans and had
African slaves (Russel-Cole, Hall, & Wilson, 2013).
Overall, I want to examine Argentina as my case study to further uncover the
phenomena. Why Argentina out of all the countries to study? It’s quite simple, like
the United States, Argentina is an ex-colony from Europe, with a myriad of European
immigrants. To add the frosting to the cake, Argentina also relates to the United
States historically through the peculiar institution of slavery produced by
Europeans. However, while the United States and Argentina have some things in
common, I chose Argentina as my case study because they have a unique twist,
unlike the United States: the Black population has “disappeared” in Argentina.
Because the Black population in Argentina is little to none, but they still had an issue
with slavery in the early seventeenth century, it would be interesting to understand
the effects of skin color and discrimination in a country with a similar, but quite
peculiar history in comparison to the United States.
After visiting Argentina during the summer of 2015, I had the opportunity to
examine skin color and discrimination at first-hand. Thus, I am able to ask and
potentially answer the questions of: who is discriminated against in Argentina? Is
skin color even an issue? Or, maybe it’s solely based on someone’s education or
socioeconomic status in Argentina?

The History of Discrimination in Argentina
In order to understand discrimination based on skin color in Argentina, it is
vital to know about Argentina’s history in regard to the peculiar institution of
slavery and the Black population.
In order to recall the short history about slavery and the Black population in
Argentina, it is important to recount the evils of the peculiar institution in Argentina
through the city and province of Buenos Aires, the largest and most prosperous
province out of the twenty-two in Argentina (Andrews, 1980).
While the slave trade in Buenos Aires started off fairly slow with only 233
African slaves as early as 1595, it was later discovered that 12,778 slaves were
imported to Buenos Aires from Brazil between the years 1606 and 1625 (Andrews,
1980). Andrews (1980) found that many African slaves imported to Buenos Aires
were from West Africa, Congo, Angola, South Africa, and even some East African
countries. While there was some importation of slaves in Buenos Aires, the amount
of slaves that Buenos Aires labored around this time was extremely low knowing
that in other slave labor based areas like the United States, the Caribbean islands,
and Brazil, there was an inundation of African slaves; southern states in the United
States would have had a declining economy if it were not for its strenuous slave
labor. I would guess that Buenos Aires may not have had an influx of African slaves
because it was not a permanent home to many slaves, but rather a temporary
destination before slaves were sent to other neighboring countries like Chile,
Paraguay, and Alto Perú—now called Bolivia (Andrews, 1980).

Furthermore, Buenos Aires did not need a myriad of slaves during the
seventeenth century because its economy was based on some trade and agriculture
(Andrews, 1980). However, this would soon change during the early eighteenth
century in Buenos Aires because slaves were transitioning from “typical” slave-like
labor to housekeeping work instead (Andrews, 1980). As time progressed on, a
handful of slaves would gain their freedom, but even after freedom was won, freed
slaves’ positions in Buenos Aires would not improve. Andrews (1980) found that
freed slaves continued to work similar positions as non-freed slaves in areas dealing
with manual labor.
By looking ahead into the mid-eighteenth century, more slaves were gaining
their freedom in Argentina because of Spanish law that, “…Tempered the harshness
of slavery by granting slaves a number of rights, the most important of which was
the opportunity to win their freedom,” (Andrews, 1980). Andrews (1980)
discovered that slaves could earn their freedom under Spanish law in a number of
ways; for example, if they married a freed slave, if a slave was a beneficiary under
their master’s will, or a slave was forced into prostitution by their master.
Regardless of being a freed or un-freed slave, slaves in Argentina had limited
amounts of freedom compared to white Spanish American citizens. This is the point
in time where the earliest forms of discrimination in Argentina start to exist. For
example, Andrews (1980) discovers that the Afro-Argentines of Buenos Aires could
not carry arms; walk the streets after a certain time period; wear certain material

like silk, pearls, or lace; hold civil or military office; and even attend the same
schools as whites. Furthermore, from Andrews’ (1980) perspective, he argues that:
“One of the most irksome aspects of this system [discrimination] was that an
Afro-Argentine born of a family that had been free for generations was the
legal equivalent of an Afro-Argentine who had acquired his freedom the day
before: both were equally disadvantaged… Nor did an admixture of white
ancestry make any legal difference… Lines of descent tainted by “unclean”
blood were socially and legally irredeemable. Thus even in cases in which
Afro-Argentines could claim European ancestry, as long as they showed
obvious physical evidence of their African heritage they remained part of the
castes and therefore of a different legal status from their white kinsmen,” (p.
46).
It is clear to see that having African ancestry in Argentina, and other parts of
the world for that matter, could be quite burdensome. At the end of the day, if one
had African blood, they faced discrimination regardless if they had any traces of
white ancestry. However, does this still exist in present-day Argentina? Andrews
(1980) found as far back as 1825, British writer Woodbine Parish noticed a
significant decrease of Afro-Argentines in Buenos Aires—I am quite sure this was
the same for other provinces within Argentina as well. Parish argued that there was
a smaller Afro-Argentine population because of the abolition of the slave trade and
high mortality rates amongst the Black population (Andrews, 1980). Andrews
(1980) also makes note of writers like José Manuel Estrada who claimed that, ‘today,

there are almost no blacks in Buenos Aires,’ (p. 65). The genuine Black/African
blood was disappearing.
However, even though the Afro-Argentine population was slowly vanishing
from Argentina, specifically Buenos Aires, there was a negative stigma surrounding
being of black ancestry in Buenos Aires (Andrews, 1980). Thus, the process of
lightening the Afro-Argentine race began around the mid-eighteenth century—as
cited in the 1827 census (Andrews, 1980). Because of the lightening effect in the
Afro-Argentine population, labels were soon placed on people; this gave people
leeway to move away from the Black demographic and face less discrimination. Of
course, as seen in the United States and other parts of the world where colonialism
took place, being light is seen as more desirable in order to move up in society and
face less discrimination (Russell-Cole, Hall, & Wilson, 2013).
Study Rational and Hypothesis Development
With this broader historical context explained, it sets the tone to understand
discrimination within Argentina. While I could explain the peculiar institution of
slavery and the emancipation of the slaves in Argentina in more depth with the help
of Andrews’ (1980) text The Afro-Argentines in Buenos Aires, I cannot as I am trying
to convey a specific message within this article. As it was previously explained,
slavery forced the Black population to be at the bottom of the caste system, thus
making Black ancestry undesirable. Being Afro-Argentine was an open invitation to
receive discrimination. This opened doors to allow people who were of mix ancestry

--and who could potentially pass, as many did in the United States—receive a
different label to escape discrimination. However, of course, if one was White, it was
better and it meant less discrimination. For this reasons,
Hypothesis Development
Although the short history of Argentina introduced that there is hardly any
Blacks (Afro-Argentines) in Buenos Aires, I would argue that when someone is
darker in complexion in Argentina, which means being closer to Black,
discrimination will be faced.
Hypothesis 1: I will test the hypothesis that self-reporting darker skin color
participants will be more likely to report higher levels of experiences of
discrimination and lower levels of discriminatory behaviors towards others.
Hypothesis 2: By referring back to the United States’ history with the Black
population, I would hypothesize that participants who are darker in complexion in
Argentina that have higher levels of education will continue to report having higher
levels of experiences of discrimination and lower levels of discriminatory behaviors
towards others.
Hypothesis 3: Argentina is geographically located in Latin America. And in
Latin America, many Blacks, or individuals who are darker in complexion, face
similar ghastly experiences as those in the United States simply because they are
darker in complexion (Russell-Cole, Hall, & Wilson, 2013). Because of this uneasy
factor, I would hypothesize again that self-reporting darker complexion participants
in Argentina with higher levels of socioeconomic status will likely to report higher

levels of experiences of discrimination and lower levels of discriminatory behaviors
towards others.
Methodological Approach
Participants
Methodologically, the best way to test my hypotheses is by examining
whether or not Argentinians believe they face discrimination based on skin color.
After receiving skin color from Argentinians, I will then break down the skin color
categories to see how each category perceives and reacts to discrimination based on
their education and socio-economic levels. In order to effectively do this, I had to
give IRB approved surveys to Argentinians in Buenos Aires and Roca, Argentina. The
participants received a consent form before they proceeded to fill out the survey. It
is important to mention that in order to examine my hypotheses any further, I had
to use IRB approved surveys from other previous studies related to discrimination
and privilege in Argentina; these surveys were collected in 2013 and 2014 with the
same primary investigator, Luciano Berardi, PhD. For the year 2015, the new
surveys collected in Buenos Aires and Roca, Argentina had a total of 66 participants
between the ages of 18 and 66. With the three years combined, the ages range from
18 and 85 years of age with a total of 405 participants.
In addition, there is an uneven distribution between male and female
participants; there are 78.1% females and 20.4% males (Table I, in addition to this
table, all tables/charts can be found at the end of this article in the appendix

section). The same could be said about sexual orientation amongst the Argentinian
population; there are 90.6% heterosexuals, 3.9% homosexuals, 2.2% bisexuals, and
1.5% other (Table 2). Perhaps sexual orientation is not evenly displayed because
Argentina is a predominantly Catholic country (Philpott, 2004). Because of this
factor, many people may still be either “traditional” or not as progressive as others
would like. Because this article is discussing skin color, it is significant to add how
our participants are distributed amongst ethnicity (Table 3). As seen in Table 3, one
can see that many of our sampled participants identify as European, then Asian, and
following that comes those who come from mixed ancestry of indigenous or African
people. In order to paint a better picture of the ethnic breakdown amongst the
participants, I provided more tables (Table 4 & 5) to show how European ancestry
compares to those who are mixed and how color is further defined between
Blanca/o (White), Tostada/o (Fair Yellow/Tan), Trigeuna/o (Darker Tan/ Brown),
and Morena/o (Dark/Black). This is where most of the data will come from in
regard to how the participants experience, perceive, and understand discrimination.
Finally, the last factor that plays a vital role in identifying the participants is
through their class; this is measured by their backgrounds of education and socio-
economic status. I define backgrounds of education as the participants’ parents’
educational levels based on primary or less, secondary or technical school, or
college degree or higher. With the participants, secondary or technical school had
the highest number with college or higher coming in second, and primary or less
being last out of the three, as shown on the table (Table 6). As far as socio-economic
status, it was measured by examining media-alta (high working), media-trabajadora

(medium working), and baja-trabajodora (low-working). The reason why it is
broken down into these two categories is because the high class, or alta in Spanish,
had only one individual. Therefore, for the sake of the data, I added the outlier
participant into the high working class. As it would be easily predicted, the
participants are heavily concentrated in the medium working class, then high
working, and low working following this category (Table 7).
Procedures & Design
Participants will fill out an IRB approved survey that contained sixty-three
questions: eighteen of the questions were general questions about the participants;
for example, age, race, and socio-economic status; the next section of fourteen
questions pertained to freedom of harassment; then, there are seven questions
about attitudes of discrimination; the next eighteen were based on perceptions of
discrimination—they originated from Peggy McIntosh’s article on privilege and
discrimination; finally, the last set of six were about access to health, but for the sake
of this paper, we are not looking at access to health. Besides a survey with a consent
form, the participants were not examined any further. Both settings, the University
of Buenos Aires and the Socio-drama in Roca, had low-pressure environments.
Measures
Independent Variables
Skin Color: During the first eighteen general questions that were listed in the
survey, participants were asked their color on the basis of four categories: blanca/o

(white), tostada/o (light yellow/tan), triguena/o (darker tan/brown), and
morena/o (dark/Black). With skin color as an independent variable, I will measure
if discrimination is experienced and perceived by participants’ skin color.
Education: As with skin color, backgrounds of education were asked during
the first eighteen general questions of the IRB approved survey. Backgrounds of
education are measured through the participants’ parents’ levels of education.
Education levels are examined through primary or less, secondary or technical
school, and college or higher. I will measure education to see if participants face
discrimination if they come from a background of low or high levels of education
without skin color being involved. Then, I will add skin color and education together
to see if discrimination is faced.
Socio-economic status (SES): Socio-economic status is surveyed in the first
general eighteen questions like the other two independent variables. SES is
measured by media-alta (high working), media-trabajadora (medium working), and
baja-trabajadora (low working). I will examine SES by forcing it to stand alone to see
if participants face discrimination based off high or low levels of SES and then add
skin color to mediate SES—the same process as I am doing with skin color and
education.
Dependent Variables
Attitudes of Discrimination: This dependent variable contains seven
questions in the IRB approved survey. All seven questions will be used to determine
if participants face discrimination in Argentina (Table 8). The questions are scale
based ranging from one to four; one is strongly disagree and four is strongly agree.

Attitudes of discrimination will allow data to see who has discriminatory behavior
towards others.
Perceptions of Discrimination: This specific variable is surveyed with
eighteen questions. All eighteen questions will be used to measure participants’
levels of discrimination in Argentina (Table 9). As attitudes of discrimination are
measured, perceptions of discrimination uses the same scale of one to four with one
being strongly disagree and four as strongly agree. Perception of discrimination will
allow data to see who is actually experiencing discrimination first-hand.
Results
Preliminary Findings with ANOVA
A one-way ANOVA was conducted on my three hypothesis with the two
dependent and three independent variables. For my first hypothesis, I hypothesized
that skin color would be a determining factor to have high levels of experiences of
discrimination and lower levels of attitudes of discrimination. Skin color being the
determining factor to perceive discrimination is highly insignificant:
F(2,253)=.207,p=.813. Skin color being the main reason to have high or lower levels
of attitudes of discrimination is not significant: F(2,252)=1.820,p=.164.
My second hypothesis was that darker complex individuals with higher levels
of education will still have higher levels of perceptions of discrimination. I tested
this with the three levels of combined parental levels of education. The ANOVA
proved this hypothesis to not be significant: F(3,251)=.453, p=.716. Also, I

hypothesized that darker complexion individuals would have lower levels of
attitudes discrimination as well; this was proven to be insignificant: F(3,251)=1.222,
p=.302. However, I took the initiative to test an alternative hypothesis to see if
combined parental educational levels alone without skin color would have higher
levels of discrimination; this was proven to be marginally significant:
F(2,263)=2.84,p=.06
Finally, my last hypothesis was tested with the ANOVA. My last hypothesis
was that self-reporting darker participants with a high socioeconomic status would
still have higher perception of discrimination. The ANOVA proved this hypothesis
substantially insignificant: F(3, 250)=.428, p=.733. Also, within my last hypothesis, I
stated that self-reporting darker participants with a high socioeconomic status
would have lower levels of attitudes of discrimination; this was insignificant as well:
F(3, 249)=1.421, p=.237. However, as I did for the previous hypothesis, I tested an
alternative hypothesis for both dependent variables. With three level socioeconomic
status standing alone without skin color being a factor, it is highly significant in
terms of experiencing discrimination: F(2,263)=4.416,p=0.013. Also, with the three
level socioeconomic status being independent of skin color as a mediator, it showed
it was highly significant in regard to attitudes of discrimination: F(2, 262)=5.453,
p=0.005.
Findings
In order to test the hypotheses, I compared the means of the independent
and dependent variables: I compared the mean three times. First, I compared the
independent variable of skin color to the two dependent variables: attitudes of

discrimination and perceptions of discrimination. The results from this comparison
are shown in Table 10. The second test is with skin color and education with the
same two dependent variables (Table 11). Finally, the last test compares skin color
and socio-economic status to the two dependent variables as well (Table 12).
Table 10 shows the skin color categories; however, at the end of the table
there is a total section. In the total section, triguena/o (tan) and morena/o
(dark/Black) are combined for the sake of the data since there was only a total of
four morena/o(s) who were surveyed out of the 405 participants from 2013-2015.
Table 10 shows that the tostada/o group has a higher mean of freedom of
harassment compared to the blanca/o and triguena/o/morena/o group. While
triguena/o/morena/o group is 0.01 higher than the blanca/o skin color group, it is
not significant. The dependent variable of attitudes of discrimination tells a slightly
different story. The blanca/o group has a higher mean of attitudes of discrimination
than tostada/o and triguena/o/morena/o. From blanca/o, means fall in order based
on shade, not surprising. However, I would say the data shows significant results; it
ranges from 2.08 to 1.87 in attitudes of discrimination. Finally, in regard to Table 10,
perceptions of discrimination are even more interesting than the other dependent
variables. While blanca/o has the lowest perception of discrimination, it is not
significant from the perceptions of discrimination that the darker complexion
participants face; therefore, there is nothing significant in regard to this dependent
variable with skin color.

In Table 11, it displays the comparison skin color with education to the three
dependent variables used in this study. For the skin color category blanca/o, it
shows that as one has a background with higher levels of education, the mean for
freedom of harassment increases. The same is for attitudes of discrimination; it
steady increases as the level of education rises. However, perceptions of
discrimination are drastically different. For the blanca/o skin color group,
perceptions of discrimination are higher with lower levels of education (primary or
less), but blanca/o(s) with backgrounds of college or higher is right beneath those
with primary or less. Thus, these findings are not significant.
Table 11 with tostada/o tells a very unique story as well because nothing is
significant. Although it shows that those with a secondary or technical school degree
have a higher mean for freedom of harassment and a lower mean for attitudes of
discrimination, it does not paint an effective picture about discrimination in regard
to tostada/o(s) in regard to education.
Furthermore, in Table 12, it shows the overall results of skin color mediating
socioeconomic status with the two dependent variables. As shown in the ANOVA
test, nothing in this table is significant.
Discussion and Conclusion
The findings show that skin color alone is not a factor in experiencing
discrimination in Argentina (Table 10). Therefore, my first hypothesis cannot be
supported through the data collected. As it was shown through results, perception
and attitudes of discrimination was not significant for the skin color categories; this
is the final piece to allow my first hypothesis to be invalid: darker complexion

individuals do not experience more discrimination or have less attitudes of
discrimination compared to lighter complexion participants.
My second hypothesis cannot be supported as well. As seen on Table 11, skin
color does not affect one’s combined parental levels of education. The ANOVA
proved this hypothesis to be very insignificant; however, as it was shown after
bringing an alternative hypothesis to light, combined parental levels of education
alone speaks more volume to discrimination faced amongst the Argentinian
population. Therefore, if someone self-reported Blanca/o(white), but has low levels
of combined parental levels of education, they will have lower levels of attitudes of
discrimination and higher levels of perception of discrimination just as a darker self-
reporting participant with the same dependent variable outcome. Thus, skin color is
not of importance in Argentina when education becomes a factor.
Finally, my third hypothesis cannot be supported from the data given as well.
As seen on Table 12, skin color does not mediate socioeconomic status for the
participants. But, as I did for the previous hypothesis in the results section of this
article, I found that when socioeconomic status stands without skin color, it shows
that people are discriminated against in terms of their economic class. Thus, it does
not matter if participants self-reported Blanca/o (white) or
Triguena/o/Morena/o(Darker Tan/Black), but if both come from high-middle class
backgrounds, perceptions of discrimination will be low while attitudes of
discrimination may be higher, as proven through the ANOVA.

All in all, what does this say about the phenomena of skin color
discrimination in Argentina? While skin color discrimination in the United States is
an issue where skin color mediates discrimination and education/socioeconomic
levels, in Argentina, the tables are turned: education and socioeconomic levels are
the mediators. Authors Baron and Kenny (1986) state that mediator variables,
“…Explain how external physical events take on internal psychological significance…
mediators speak to how or why such effects occur,” (p.1176). Therefore, in
Argentina, education and socioeconomic status speak to why participants face
discrimination or have high levels of attitudes of discrimination opposed to skin
color explaining discrimination, like in the United States.
While this study was effective in some aspects, I came across a few
limitations. The most substantial limitation I had was finding Black/Afro-Argentines
to complete the survey. Since I generalize the phenomena of skin color
discrimination in the United States on Black Americans, it would have been more
interesting to specifically examine the Black population of Argentina in comparison
to Blacks in the United States. While I used skin color as the independent variable,
not everyone’s skin color tells society on their ethnic makeup. However, the skin
color story in Argentina does give a hopeful outcome that skin color is not a factor in
itself to experience discrimination. Not only would self-reporting Black participants
add to my findings, but it would make the sample much larger to assess.
This segues into another limitation that I had over the summer, sample size.
While the sample size from all three years is at 405 participants, it would be even
more intriguing to examine data from a larger sample size, preferably something

closer in size to the actual Argentinian population. Even though that would be
merely impossible, in my case as an undergraduate college student, it would give my
findings more depth on the realities of skin color discrimination.
Furthermore, another limitation that I faced while doing my research was
working with Statistical Package for the Social Sciences (SPSS). Statistical Package
for the Social Sciences (SPSS) was used to input and measure the data collected.
However, there were some technical errors on the systems’ behalf that made the
results of my data hard to follow, specifically with the skin color categories. I tried to
put triguena/o and morena/o into one category for darker complexion
Argentinians, SPSS read them separately.
While limitations were faced during this research process, this will only
allow me to have better ideas to expand on my findings. First, I will stay in Argentina
longer to get a substantial amount of data from the Afro-Argentines/Black
Argentinian population. First, I will get IRB approval and then I will do previous
research on areas that have a large Black population. This will only strengthen my
data and will be an easier comparison between the United States and Argentina. At
the beginning of this article, I examined discrimination amongst Black US citizens,
not those who fall into the “dark” category because they can come from a variety of
ethnic backgrounds. However, since I had to utilize what I had, I decided to test the
darker complexion population in Argentina as an appropriate comparison.

All in all, this article discussed a phenomena that often goes unnoticed within
and beyond the United States. Discrimination is alive and well throughout the world.
Discrimination is often associated as an “American” issue stemming from the
peculiar institution of slavery, but what about in other parts of the world where
slavery existed? Even though Argentina was the case study used in this article, it
shed light on the simple fact that while discrimination exists, skin color is not a
determining factor to experience discrimination or have attitudes of discrimination,
but rather education and socioeconomic status mediates skin color discrimination.
This shows that countries across the globe, like Argentina, are not focused on ones’
complexion, but rather their educational and economic status. While people should
not face discrimination no matter what their background may be, it demonstrates
that countries, like Argentina, are progressing beyond the outer layer of ones’ color.
This study can allow US citizens to think before they make assumptions
based off ones’ color, but rather think again. This can also help Argentinians
understand their phenomena of discrimination in contrast to the United States. All
in all, two different countries are able to learn about discrimination from a different
perspective to potentially eliminate discrimination and prejudice in the near future.

Appendix
Descriptive Statistics of Participants
N Minimum Maximum Mean Std. Deviation
Cu l es tu edad?(Whatis your age) 388 14 85 31.76 11.323
Valid N (listwise) 388
Table 1:
7. ¿Cuál es su genero? (Translation: What is your gender?)
Frequency Percent Valid Percent Cumulative Percent
Valid
Masculino
(Male)
83 20.4 20.8 20.8
Femenino
(Female)
317 78.1 79.3 100.0
Total 400 98.5 100.0
Missing 99 6 1.5
Total 406 100.0
Table 2:
8. ¿Cuál es su orientacion sexual? (Translation: What is your sexual orientation?)
Valid
Heteroxexual 368 90.6 92.2 92.2
Homosexual 16 3.9 4.0 96.2
Bisexual 9 2.2 2.3 98.5
Otro (Other) 6 1.5 1.5 100.0
Total 399 98.3 100.0
Missing 99.00 7 1.7
Total 406 100.0
Table 3:

¿Cuál es tu descendencia? (Marcá todos lo que consideres) (Translation: What is your offspring (ancestry)?)
Valid
Europeos (European) 188 46.3 48.0 48.0
Asiaticos (Asianb) 18 4.4 4.6 52.6
Pueb Originarios (Native) 62 15.3 15.8 68.4
Europeos y Pueb Origin
(mezcla) (European w/
Native)
72 17.7 18.4 86.7
Pueb Origin y Africanos
(mezcla) (Native w/ African)
4 1.0 1.0 87.8
Europeos y Africanos
(mezcla) (European w/
African)
7 1.7 1.8 89.5
Euro, African, y Pueb Origin
(mezcla) (European,African,
and Native)
3 .7 .8 90.3
Asiaticos y Otros (mezcla)
(Aisan with other)
1 .2 .3 90.6
Otro (Other) 27 6.7 6.9 97.4
11 2 .5 .5 98.0
12 8 2.0 2.0 100.0
Total 392 96.6 100.0
Missing
99 13 3.2
System 1 .2
Total 14 3.4
Total 406 100.0
Table 4:

European vs others
Valid
Europeos (European) 163 40.1 49.7 49.7
Indigenas & Mix (Indigenous
Mix)
(indigenas/eropeos/africanos
)
(Indigenous/European/Africa
n)
165 40.6 50.3 100.0
Total 328 80.8 100.0
Missing
99.00 11 2.7
System 67 16.5
Total 78 19.2
Total 406 100.0
Table 5:
Triguena/Morena (Translation: Darker Tan/Black Complexion)
Valid
Blanca/o (White) 176 43.3 45.2 45.2
Tostada/o (Tan) 110 27.1 28.3 73.5
triguena/morena
(Darker Tan/Black)
103 25.4 26.5 100.0
Total 389 95.8 100.0
Missing 99.00 17 4.2
Total 406 100.0
Table 6:
Combined parental level or education 3 categories
Valid Primary or less 100 24.7 24.9 24.9

Secundary and technical
degree
159 39.3 39.6 64.4
College and higher 143 35.3 35.6 100.0
Total 402 99.3 100.0
Missing 99.00 3 .7
Total 405 100.0
Table 7:
23. Usted se considera parte de una familia de clase socio-económica: (Marque solo uno) (Translation: What is your families’
socioeconomic status?)
Valid
media-alta (High
average)
55 13.5 13.8 13.8
media-trabajadora
(average worker)
298 73.4 74.9 88.7
baja-trabajadora (low
working)
45 11.1 11.3 100.0
Total 398 98.0 100.0
Missing 99.00 8 2.0
Total 406 100.0
Table 8: Attitudes of Discrimination (Dependent Variable)
1. People from Bolivia, Peru and Paraguay have to go back to their countries they do not belong in
Argentina’s Society
1 2 3 4
2. I have friends or I can become a friend of people from Bolivia, Peru and Paraguay ® 1 2 3 4
3. People from Bolivia, Peru, Paraguay and Indigenes are not nice people to be around like the rest of the
Argentineans
1 2 3 4
4. People from indigenous background are lazy 1 2 3 4
5. People with dark skin are not as good as people that descent from Europeans 1 2 3 4
6. People from indigenous origin, Bolivia, Peru and Paraguay are hardworking people that deserve
respect like any Argentinean ®
1 2 3 4
7. People from indigenous origin, Bolivia, Peru and Paraguay belong to Argentina society like any other
person that lives in Argentina ®
1 2 3 4
Table 9: Perceptions of Discrimination (Dependent Variable)
1. People look strangely at me when I speak 1 2 3 4
2. People look strangely at me on the streets 1 2 3 4

3. People cross the street when I walk close to them 1 2 3 4
4. The police stop me on the street 1 2 3 4
5. In public places people close to me put away their things or they get anxious 1 2 3 4
6. In public transportation people do not sit next to me if there are other available seats besides
the one that is next to me
1 2 3 4
7. I have to dress betterwhen I need to go buy something 1 2 3 4
8. On the job I speak only with people who are my color/origin/ethnicity 1 2 3 4
9. In the University I speakonly with people of my color/origin/ethnicity 1 2 3 4
10. I find it difficult to find a job because of my appearance 1 2 3 4
11. I find it difficult to apply for a credit card 1 2 3 4
12. I find it difficult to apply for a loan 1 2 3 4
13. The security guards follow me at the supermarkets, theaters,malls, restaurants 1 2 3 4
14. Have you been told negative things about the neighborhood that you live in. 1 2 3 4
15. Have you been told negative things about your household 1 2 3 4
16. Have you been told negative things about how you dress 1 2 3 4
17. Have you been told negative things about how you speak 1 2 3 4
18. Have you been told negative things about the color of yourskin 1 2 3 4

Table 10: Hypothesis 1
Attituds of
discrimina
tion (7
items)
mean/Scal
e
discrimina
tion 1-18
Mean 2.0920 1.4532
N
124 124
Std.
Deviation
.79255 .40101
Mean 2.0355 1.4745
N
57 57
Std.
Deviation
.81824 .37766
Mean 1.8645 1.4897
N
71 72
Std.
Deviation
.82028 .38589
Mean 2.0151 1.4684
N
252 253
Std.
Deviation
.80887 .39037
Total
Triguena/Morena
Blanca‎/o
Tostada‎/o
triguena‎/
morena

discrimina
tion 1-18
Attituds of
discrimina
tion (7
items)
mean/Scal
e
Mean 1.5773 2.1032
N 12 12
Std.
Deviation
.44301 .82199
Mean 1.4971 1.8355
N 33 33
Std.
Deviation
.41909 .61665
Mean 1.5088 1.8680
N 21 22
Std.
Deviation
.48029 .88200
Mean 1.5154 1.8941
N 66 67
Std.
Deviation
.43766 .74458
Mean 1.4554 1.9457
N 25 25
Std.
Deviation
.31365 .82769
Mean 1.3917 2.0440
N 41 41
Std.
Deviation
.43235 .87114
Mean 1.4793 1.7328
N 29 27
Std.
Deviation
.36314 .67751
Mean 1.4352 1.9272
N 95 93
Std.
Deviation
.38141 .80973
Mean 1.4368 2.1071
N 20 20
Std.
Deviation
.41692 .83541
Mean 1.4820 2.3038
N 49 49
Std.
Deviation
.36246 .79413
Mean 1.4852 2.0227
N 22 22
Std.
Deviation
.32771 .92092
Mean 1.4728 2.1926
N 91 91
Std.
Deviation
.36359 .83485
Mean 1.4745 2.0355
N 57 57
Std.
Deviation
.37766 .81824
Mean 1.4559 2.0916
N 123 123
Std.
Deviation
.40145 .79578
Mean 1.4897 1.8645
N 72 71
Std.
Deviation
.38589 .82028
Mean 1.4698 2.0146
N 252 251
Std.
Deviation
.39050 .81044
College
and higher
Tostada‎/o
Blanca‎/o
triguena‎/
morena
Total
Total Tostada‎/o
Blanca‎/o
triguena‎/
morena
Total
Primary or
less
Tostada‎/o
Blanca‎/o
triguena‎/
morena
Total
Secundary
and
technical
degree
Tostada‎/o
Blanca‎/o
triguena‎/
morena
Total
Report
Combined parental level or
education 3 categories

Table 11 continued: Alternate Hypothesis 2
Attituds of
discrimina
tion (7
items)
mean/Scal
e
discrimina
tion 1-18
Mean 1.8782 1.5188
N 70 69
Std.
Deviation
.73386 .43255
Mean 1.9759 1.4322
N 97 99
Std.
Deviation
.82762 .38196
Mean 2.1662 1.4870
N 96 96
Std.
Deviation
.82132 .39487
Mean 2.0194 1.4747
N 263 264
Std.
Deviation
.80705 .40038
College
and higher
Total
Combined parental
level or education 3
categories
Primary or
less
Secundary
and
technical
degree

Attituds of
dis crim ina
tion (7
item s )
m ean/Scal
e
dis crim ina
tion 1-18
Mean
2.6739 1.4612
N 17 17
Std.
Deviation
.78773 .34473
Variance
.621 .119
Grouped
Median
2.7857 1.4444
Mean 2.0128 1.4128
N 85 85
Std.
Deviation
.77162 .40783
Variance .595 .166
Grouped
Median
1.7403 1.3000
Mean 1.9320 1.6316
N 21 21
Std.
Deviation
.68156 .38038
Variance .465 .145
Grouped
Median
1.7253 1.5417
Mean 2.0904 1.4568
N 123 123
Std.
Deviation
.78959 .40054
Variance .623 .160
Grouped
Median
1.8367 1.3722
Mean 2.2857 1.3944
N 10 10
Std.
Deviation
1.00565 .41280
Variance 1.011 .170
Grouped
Median
2.6857 1.3056
Mean 2.0101 1.4579
N 45 45
Std.
Deviation
.78052 .32781
Variance .609 .107
Grouped
Median
1.6667 1.4444
Mean 1.3571 2.2500
N 2 2
Std.
Deviation
.10102 .66782
Variance .010 .446
Grouped
Median
1.3571 2.2500
Mean 2.0355 1.4745
N 57 57
Std.
Deviation
.81824 .37766
Variance .670 .143
Grouped
Median
1.6395 1.4375
Mean 2.1429 1.5928
N 5 5
Std.
Deviation
1.08797 .46816
Variance 1.184 .219
Grouped
Median
1.9048 1.3529
Mean 1.8417 1.4961
N 51 53
Std.
Deviation
.80182 .38654
Variance .643 .149
Grouped
Median
1.5119 1.4349
Mean 1.8095 1.4360
N 10 10
Std.
Deviation
.82479 .40732
Variance .680 .166
Grouped
Median
1.6429 1.3415
Mean 1.8597 1.4943
N 66 68
Std.
Deviation
.81755 .39060
Variance .668 .153
Grouped
Median
1.4925 1.4153
Mean 2.4048 1.2103
N 3 2
Std.
Deviation
.95920 .09540
Variance .920 .009
Grouped
Median
2.0000 1.2103
Mean 2.4048 1.2103
m orena/o m edia-
trabajador
a
Total
tos tada/o m edia-alta
m edia-
trabajador
a
baja-
trabajador
a
Total
triguena/o m edia-alta
m edia-
trabajador
a
baja-
trabajador
a
Total
10. ¿Com o identificarias tu color
de piel?
blanca/o m edia-alta
m edia-
trabajador
a
baja-
trabajador
a
Total

Table 12 continued: Alternate Hypothesis 3
Attituds of
discrimina
tion (7
items)
mean/Scal
e
discrimina
tion 1-18
Mean 2.4132 1.4436
N 35 35
Std.
Deviation
.90815 .37027
Mean 1.9857 1.4480
N
192 193
Std.
Deviation
.78879 .38219
Mean 1.8313 1.6606
N
35 35
Std.
Deviation
.69769 .48383
Mean
2.0222 1.4757
N 262 263
Std.
Deviation
.80780 .40061
23. Usted se
considera parte de
una familia de clase
socio-económica:
(Marque solo uno)
media-alta
media-
trabajador
a
baja-
trabajador
a
Total

References
Andrews, George Reid. (1980). The Afro-Argentines of Buenos Aires, 1800-1900,
Madison, Wisconsin: U of Wisconsin P.
Baron, Reuben M., & Kenny, David A. (1986) “The Moderator-Mediator Variable
Distinction In Social Psychological Research: Conceptual, Strategic, and
Statistical Considerations.” The Journal of Personality and Social Psychology
51(6): 1173-82.
Boylorn, Robin M. (2006). “E Pluribus Unum: Out of Many, One.” Quantitative Inquiry
12(4): 651-80.
Collins, P.H. (2000). Black feminist thought: Knowledge, consciousness, and the
politics of empowerment (2nd ed.). New York: Routledge. N.p.
DeSante, C.D. (2013). “Working Twice as Hard to Get Half as Far: Race, Work Ethic,
and America’s Deserving Poor.” American Journal of Political Science 57(2):
342-56.
Dryer, R. (1997). White. London: Routledge. N.p.
Feagan, Joe R., & Sikes, Melvin P. (1994). Living with Racism: The Black Middle-Class
Experience, Boston, Mass: Beacon P.
Fischer, C.S., Hout, M., Jankowski, M.S., Lucas, S.R., Swidler, A., & Voss, K. (1996)
Inequality by design: Cracking the bell curve myth. Princeton, NJ: Princeton
University P. N.p
Hernstein, J.A., & Murray, C. (1994). The bell curve: Intelligence and class structure
In American life. New York: Free Press. N.p.
Jones, Trina. (2000). “Shades of Brown: The Law of Skin Color.” Duke Law Journal
49(6):1487-557.
Philpott, Daniel. (2004). “The Catholic Wave.” The Journal of Democracy 15(2):32-
46.
Russel-Cole, Kathy., Hall, R.E., & Wilson, M. (2013).The Color Complex: The Politics of
Skin Color in a New Millennium, New York: Random House P.
Thorton, Brian. “The Murder of Emmitt Till.” Journal of History 62(1):1-24.

Argentina_Research

Recommended

Recommended

More Related Content

What's hot

What's hot (18)

Argentina_Research