Stereotyping in a New Age of Conservatism

Kendra Quiroz Author

04/01/2021 Added

6 Plays

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Study focuses on the development of a Anti-Mexican American Attitudnial Bias scale.

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[00:00:02.850]Hello, my name is Kendra Quiroz,
[00:00:05.360]and I am a Psych and English major.
[00:00:09.270]The title of my study
[00:00:10.440]is "Stereotyping in a New Age of Conservatism."
[00:00:17.320]The history of Mexican-Americans in the U.S. is a long one.
[00:00:21.070]After this last presidency,
[00:00:22.670]and with the ever-increasing population
[00:00:24.580]of Mexican-Americans,
[00:00:26.500]it is imperative to conduct research over this demographic,
[00:00:30.280]and the way Mexican-Americans are perceived
[00:00:32.570]by the majority white country they call home.
[00:00:36.400]The history of discrimination against Mexican-Americans
[00:00:39.310]is an even longer one.
[00:00:41.690]The picture shown is a sign from Texas
[00:00:43.830]during the Juan Crow era.
[00:00:46.310]The term was coined to describe the laws passed
[00:00:48.500]after European-Americans realized Jim Crow laws
[00:00:51.770]did not apply to Mexican-Americans.
[00:00:54.910]Like our Black brothers and sisters,
[00:00:57.230]Mexican-Americans have always been at the mercy
[00:01:00.200]of raging white supremacy.
[00:01:06.890]The treaty of Guadalupe Hidalgo
[00:01:08.900]ended the Mexican-American War,
[00:01:11.210]but it opened an era of discrimination and Jim Crow laws
[00:01:14.880]directed at Mexican-Americans.
[00:01:17.980]Battles between the U.S. and Mexico lasted until 1925,
[00:01:22.760]with lynchings and murders of Mexican-Americans.
[00:01:30.610]Jim Crow laws resulted in discrimination
[00:01:33.010]in every area of social life.
[00:01:36.140]Today, hate crimes have increased against Latinx.
[00:01:40.330]According to the FBI's 2019 hate crime statistic,
[00:01:43.555]of the U.S. motivated hate crimes,
[00:01:46.770]14.1% were classified
[00:01:50.310]as anti-Hispanic or Latino.
[00:01:54.070]With the high Mexican-American population
[00:01:56.900]and the increase in hate crimes against Hispanics,
[00:02:00.240]we need to understand the content of prejudice
[00:02:02.830]against that population.
[00:02:05.320]We know little about the content, motivations,
[00:02:08.660]and behavior ramifications of such bias.
[00:02:12.510]Consequently, this research focuses on the development
[00:02:15.800]of a scale to measure anti-Mexican-American biases.
[00:02:23.280]These negative biases can still be seen in images
[00:02:26.120]from social media and news sources.
[00:02:28.870]The top right comic was printed
[00:02:30.480]in an upstate New York town in 2018.
[00:02:34.730]As you can see, the stereotypes that follow
[00:02:37.740]Mexican-Americans are still very much alive.
[00:02:44.190]While our focus was on Mexican-Americans,
[00:02:46.730]we know little about the content of biases
[00:02:49.050]for white Americans, as well.
[00:02:51.260]We did examine biases against white Americans,
[00:02:53.980]and found participants were unable to automatically generate
[00:02:57.280]as many traits and stereotypes about whites
[00:03:01.090]than they were able to for Mexican-Americans.
[00:03:04.240]Perhaps it is because white is the norm,
[00:03:07.460]and stereotypes of Mexican-Americans
[00:03:09.790]are part of a national portrayal.
[00:03:12.700]Thus, our focus is the way Mexican-Americans are viewed.
[00:03:21.930]In our previous experiment,
[00:03:24.290]we focused on three constructs that may define bias.
[00:03:28.220]One are the belief in stereotypes.
[00:03:31.280]In the first experiment, participants provided traits
[00:03:34.050]that defined Mexican-American females and males.
[00:03:37.720]Second, we examined motivations by having participants
[00:03:41.230]report their perceived advantages and disadvantages
[00:03:44.320]Mexican-Americans possess.
[00:03:47.130]Third, we examined conservative ideology,
[00:03:50.500]such as ratings of policy and social issues and conservatism
[00:03:54.663]and the role it plays in the knowledge
[00:03:56.690]of the stereotypes for Mexican-Americans.
[00:04:00.850]We believe these approaches provide an integrated approach
[00:04:03.910]to the conceptualizations and measurement of bias.
[00:04:09.090]The most common stereotypes and traits
[00:04:11.076]provided by participants were used for verification.
[00:04:19.140]These are some of the results from our previous study.
[00:04:22.220]These were the most significant
[00:04:25.395]stereotypic traits for Mexican-Americans.
[00:04:28.820]The current study seeks to verify these stereotypic traits
[00:04:31.890]by asking participants on a one-to-seven scale
[00:04:34.940]how well they describe Mexican or European-Americans.
[00:04:39.240]Due to time, I will not be discussing
[00:04:41.580]European-American results,
[00:04:43.600]but some of the traits assigned to European-Americans
[00:04:45.870]were privileged, educated, and economically advantaged.
[00:04:54.890]We had two hypotheses.
[00:04:57.320]We expected to confirm adherence
[00:04:59.710]to stereotypical traits for Mexican-Americans.
[00:05:03.520]And second, we anticipated,
[00:05:05.700]those with higher conservative ideology
[00:05:08.310]would demonstrate more stereotypical bias
[00:05:11.170]against Mexican-American females and males.
[00:05:19.010]86 students participated.
[00:05:22.160]After consent, participants rated stereotypes and traits
[00:05:26.093]from Mexican and European-Americans for their relevance.
[00:05:30.690]The traits and stereotypes participants rated
[00:05:33.270]were provided by my UCARE project last year.
[00:05:36.381]Finally, they completed a series of ideology measures,
[00:05:40.100]including essentialism, policy and social conservatism,
[00:05:44.100]and general conservatism,
[00:05:46.200]along with political party affiliation,
[00:05:48.540]social dominance orientation, and system justification.
[00:05:57.250]All measures were rated on a seven-point scale.
[00:06:00.770]For policy and social conservatism,
[00:06:02.901]and political party identification,
[00:06:05.670]the means hover around the midpoint.
[00:06:12.040]Manova indicated significant differences
[00:06:14.450]for two ideology measures,
[00:06:16.960]conservatism for policy and social issues,
[00:06:19.720]and for extreme liberalism to extreme conservatism.
[00:06:23.880]Republicans are more conservative than other groups.
[00:06:32.700]For general Mexican-American stereotype endorsement,
[00:06:36.080]conservatism on policy and social issues is significant,
[00:06:40.280]and liberal/conservatism is marginally significant.
[00:06:44.940]There is a tendency that the higher one is in conservatism.
[00:06:49.420]The more likely one is to endorse
[00:06:51.450]Mexican-American stereotypes.
[00:07:00.380]Results indicated that policy and social issues conservatism
[00:07:04.500]is predictive of Mexican-American female stereotypes.
[00:07:08.850]Liberalism and conservatism was marginally significant.
[00:07:17.700]Conservative ideology predicted ratings
[00:07:20.130]of Mexican-American male stereotypes.
[00:07:24.310]The more you are conservative,
[00:07:26.060]the more you endorse the stereotype.
[00:07:33.390]Our hypotheses were confirmed.
[00:07:35.883]Stereotypic traits still exist and are endorsed more heavily
[00:07:39.660]by those with conservative ideology.
[00:07:42.580]There were no differences in conservative ideology
[00:07:45.670]based on political party.
[00:07:51.060]Future research holds, first,
[00:07:54.400]the development of measurement scale
[00:07:56.290]of anti-Mexican-American attitudinal bias.
[00:07:59.930]Second, determine if a Mexican-American sample
[00:08:03.070]would show the same biases as the findings here indicate.
[00:08:07.040]And third, we have data on European-Americans
[00:08:10.470]that still needs to be analyzed.
[00:08:15.580]With that being said,
[00:08:17.160]thank you so much for listening to me today
[00:08:20.500]and thank you to Dr. Esqueda
[00:08:22.870]for her constant support and guidance.
[00:08:25.470]And thank you to my research teammate and friend,
[00:08:28.430]Daniel Nguyen for assistance and coding.
[00:08:31.510]Thank you.

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