Labor market
Source: Dahl and Krog (2018)
Labor market
Source: Dahl and Krog (2018)
In international comparison
Source: Quillian and Midtbøen (2021)
Labor market
Source: Dahl and Krog (2018)
Housing market
Source: Herby and Haagen Nielsen (2015)
Primary schools
Source: Olsen, Kyhse-Andersen, and Moynihan (2021)
Primary schools
Source: Olsen, Kyhse-Andersen, and Moynihan (2021)
Municipality politicians
Source: Dinesen, Dahl, and Schiøler (2021)
Post-stratification weighted results based on a random sample of 1,012 mainstream Danes (born in DK and both parents born in DK)
Post-stratification weighted results based on a random sample of 1,007 mainstream Danes (born in DK and both parents born in DK)
⇒ Do our efforts to identify and describe the extent of ethno-racial discrimination
also succeed in raising public recognition and support for equal-treatment polices?
Experimental-design by Haaland and Roth (2022): "Beliefs About Racial Discrimination and Support for Pro-Black Policies" in the US.
Now we are interested in hearing your thoughts on a recent social science study.
Researchers from the University of Copenhagen conducted a study on discrimination against non-Western minorities in Danish primary schools. They did this by sending fictitious applications to primary schools in Denmark, where a parent requested to transfer their child to the school's 3rd grade.
The fictitious applications were exactly the same except for one thing: the name of the father of the child who was to be admitted to the school and who sent the email. Half of the applications had a typically Danish-sounding name such as "Peter Nielsen," while the other half had a typically Muslim-sounding name such as "Mohammad Osman."
The researchers wanted to find out whether schools would view the exact same application more positively if it was sent by a parent with a Danish-sounding name compared to a parent with a Muslim-sounding name.
Out of 100 fictitious applications with Danish-sounding names, 25 of the applications were able to get the child admitted to the school.
What do you think: out of 100 fictitious applications with Muslim-sounding names, how many of the applications were able to get the child admitted to the school?
Mis-perception of ethnic discrimination by primary schools
Post-stratification weighted results based on a random sample of 1041 mainstream Danes (born in DK and both parents born in DK).
Post-stratification weighted results based on a random sample of each approx. 1041 mainstream Danes (born in DK and both parents born in DK).
Experimental-design by Haaland and Roth (2022).
→ Correction: A random 16 of respondents was provided with actual result of field experiment.
→ No correction: A random 16 of respondents was not and serves as control.
Experimental-design by Haaland and Roth (2022).
→ Correction: A random 16 of respondents was provided with actual result of field experiment.
→ No correction: A random 16 of respondents was not and serves as control.
The researchers found that out of 100 fictitious applications with Muslim-sounding names, 15 of the applications were able to get the child admitted to the school. In comparison, 25 out of 100 applications were able to get the child admitted to the school when the application had a Danish-sounding name.
This means that primary schools were 67% more likely to admit a student with a Danish-sounding name compared to a student with a Muslim-sounding name.
Experimental-design by Haaland and Roth (2022).
→ Correction: A random 16 of respondents was provided with actual result of field experiment.
→ No correction: A random 16 of respondents was not and serves as control.
Post-stratification weighted OLS regression with 95% confidence interval. n = 1669.
Post-stratification weighted results. On the right: OLS point estimate with robust 90 & 95% confidence intervals. Results are adjusted for the extent of the initial misperception of discrimination, type of field experiment, age, gender, region, education, household size, and labor force status. n = 769.
Post-stratification weighted results. On the right: OLS point estimate with robust 90 & 95% confidence intervals. Results are adjusted for the extent of the initial misperception of discrimination, type of field experiment, age, gender, region, education, household size, and labor force status. n = 1562 & 758.
Post-stratification weighted results. On the right: OLS point estimate with robust 90 & 95% confidence intervals. Results are adjusted for the extent of the initial misperception of discrimination, type of field experiment, age, gender, region, education, household size, and labor force status. n = 1,189.
Source: Haaland and Roth (2022)
Framing: The process by which a person uses a socially-constructed schema of interpretation to conceptually organize and understand an object, experience, or event (Goffman, 1974, page 21).
Possibly necessary because:
Fictional persons,
Evidence only in the aggregat.
Advancement of experimental-designs by Haaland and Roth (2022).
→ Correction: A random 16 of respondents was provided with actual result of field experiment.
→ Researcher: A random 16 of respondents additionally received the following framing of the correction:
We asked #Name, who is a university researcher, for a comment on the study. S/he explained:
"The results are credible. The study was conducted according to the highest standards of evidence within the research field."
Kristina Bakkær Simonsen,
Aarhus Universitet
Martin Vinæs Larsen,
Aarhus Universitet
Jakob Majlund Holm,
Aarhus Universitet
Mathilde Cecchini,
Aarhus Universitet
→ Lawyer: A random 16 of respondents additionally received the following framing of the correction:
We asked #Name, who is a lawyer, for a comment on the study. S/he explained:
"The results are alarming. Discrimination like this is prohibited by Danish law."
Tine Birkelund,
Institut for Menneske Rettigheder
Nikolaj Nielsen,
Institut for Menneske Rettigheder
Tarek Hussein,
Institut for Menneske Rettigheder
Nanna Margrethe Krusaa,
Institut for Menneske Rettigheder
→ Affected: A random 16 of respondents additionally received the following framing of the correction:
We asked #Name, who is a non-Western minority person, for a comment on the study. S/he explained:
"The results make me sad. It worries me to hear that people with a name like mine are not treated equally."
Loubna Mekhchoun
Mohammed Al'Bannay
Hassan Musse
Yasmin Mohamed
Post-stratification weighted OLS point estimate with robust 90 & 95% confidence intervals. Results are adjusted for the extent of the initial misperception of discrimination, type of field experiment, age, gender, region, education, household size, and labor force status. n = 2,973, 3,904, 1,895 & 2,973.
Machine learning based analysis of effect heterogeneity according to Chernozhukov, Demirer, Duflo, and Fernández-Val (2022).
Recognition
Name-blind applications
→ Control 0: A random 16 of respondents was not exposed to the initial elicitation:
Researchers from the University of Copenhagen conducted a study on discrimination against non-Western minorities in Danish primary schools. They did this by sending fictitious applications to primary schools in Denmark, where a parent requested to transfer their child to the school's 3rd grade.
...
→ Control 0: A random 16 of respondents was not exposed to the initial elicitation:
Researchers from the University of Copenhagen conducted a study on discrimination against non-Western minorities in Danish primary schools. They did this by sending fictitious applications to primary schools in Denmark, where a parent requested to transfer their child to the school's 3rd grade.
...
Post-stratification weighted OLS point estimate with robust 90 & 95% confidence intervals. Results are adjusted for the extent of the initial misperception of discrimination, type of field experiment, age, gender, region, education, household size, and labor force status. n = 2,973, 3,904, 1,895 & 2,973.
Post-stratification weighted results based on a random sample of 1,003 mainstream Danes (born in DK and both parents born in DK)
Evidence-based awareness raising is unlikely to be successful.
While citizens may donate to recognize minority hardships,
they hesitate to endorse policies that could impact their group's privileges.
Thank you for
for your Attention!
Chernozhukov, V., M. Demirer, E. Duflo, et al. (2022). Generic Machine Learning Inference on Heterogenous Treatment Effects in Randomized Experiments.
Dahl, M. and N. Krog (2018). "Experimental Evidence of Discrimination in the Labour Market: Intersections between Ethnicity, Gender, and Socio-Economic Status". In: European Sociological Review, pp. 402-417.
Dinesen, P. T., M. Dahl, and M. Schiøler (2021). "When Are Legislators Responsive to Ethnic Minorities? Testing the Role of Electoral Incentives and Candidate Selection for Mitigating Ethnocentric Responsiveness". In: American Political Science Review, pp. 450-466.
Goffman, E. (1974). Frame analysis: An essay on the organization of experience. Harvard University Press.
Haaland, I. and C. Roth (2022). "Beliefs about Racial Discrimination and Support for Pro-Black Policies". In: The Review of Economics and Statistics, pp. 1-15.
Herby, J. and U. Haagen Nielsen (2015). "Rapport om etnisk diskrimination pa boligmarkedet".
Olsen, A. L., J. H. Kyhse-Andersen, and D. Moynihan (2021). "The Unequal Distribution of Opportunity: A National Audit Study of Bureaucratic Discrimination in Primary School Access". In: American Journal of Political Science.
Quillian, L. and A. H. Midtbøen (2021). "Comparative Perspectives on Racial Discrimination in Hiring: The Rise of Field Experiments". In: Annual Review of Sociology, pp. 391-415.
Labor market
Source: Dahl and Krog (2018)
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