Ian Burn’s research while affiliated with University of Liverpool and other places

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Publications (21)


Help Really Wanted? The Impact of Age Stereotypes in Job Ads on Applications from Older Workers
  • Article

October 2024

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12 Reads

Journal of Labor Economics

Daniel Firoozi

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Ian Burn

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Daniel Ladd

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Figure 1. (a) Distributions of cosine similarity (CS) scores. (b) Locations of treatment and control phrases in the CSS distribution of job ad phrases. (c) Comparing the distribution of CSS scores and perceived ageism by stereotype.
Figure 1. Continued. Note: (a) Figure reports the distribution of cosine similarity scores for all trigrams from the job ads with the indicated stereotypes. The higher the cosine similarity score, the more related the trigram is to the stereotype, with a minimum of −1 and a maximum of 1. The phrases in the boxes are examples of phrases located at that point in the distribution. (b) Solid lines indicate the location of a control sentence in the cosine similarity score distribution. Dashed lines indicate the location of a treatment phrase (for the machine-learning treatments shown in Table 2). (c) The dark points/lines are at the average cosine similarity score of the treatment and control phrases as shown in Table 2, for the indicated stereotype. The height of the right-hand dark point/line in each panel indicates the difference in the perceived ageism of the machine-learning treatment phrases relative to the control phrases for individuals over 50 (Table 4, column 9).
Figure 2. Job ad examples.
Figure 3. Cosine similarity scores of administrative assistant templates (based on machine-learning treatments and the controls). Note: Graphs display median to 99th percentile range of trigram semantic similarity scores for stereotypes for Administrative Assistant
Figure 6. Survey results. Note: These numerical ratings reflect the degree to which survey respondents rated phrases as age-biased or not age-biased, with lower

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Stereotypes of older workers and perceived ageism in job ads: evidence from an experiment
  • Article
  • Full-text available

January 2023

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185 Reads

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3 Citations

Journal of Pension Economics and Finance

We explore whether ageist stereotypes in job ads are detectable using machine-learning methods measuring the linguistic similarity of job-ad language to ageist stereotypes identified by industrial psychologists. We then conduct an experiment to evaluate whether this language is perceived as biased against older workers searching for jobs. We find that job-ad language classified by the machine-learning algorithm as closely related to ageist stereotypes is perceived by experimental subjects as biased against older job seekers. These methods could potentially help enforce anti-discrimination laws by using job ads to predict or identify employers more likely to be engaging in age discrimination.

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Gender typicality and sexual minority labour market differentials

April 2022

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32 Reads

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12 Citations

British Journal of Industrial Relations

Sexual minorities experience significant differences in labour market outcomes relative to comparable heterosexuals, with larger differences in earnings than in labour supply. A common explanation of these differences is that they may reflect unobserved differences in masculinity and femininity in the sexual minority population. We leverage data on personality and behaviours in the National Study of Adolescent to Adult Health (Add Health) to test whether controlling for differences in masculinity and femininity through quantitative measures of gender typicality eliminates labour market differentials. While we find evidence that gender typicality does affect labour market outcomes of men and women on average, we find no evidence of a differential effect for gays and lesbians. Controlling for gender typicality does not affect the sexual orientation labour market differentials. The evidence suggests that existing estimates of earnings differentials are not affected by omitted variable bias due to not controlling for gender typicality.



Figure 1: Comparisons of Job Applicant Callback Rates by Age
Figure 2: Text of a Job Ad
Figure 5: Distributions of 95 th Percentiles of CS Scores for Stereotypes Related to Health
Does Ageist Language in Job Ads Predict Age Discrimination in Hiring?

October 2021

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646 Reads

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18 Citations

Journal of Labor Economics

We study the relationships between ageist stereotypes - as reflected in the language used in job ads - and age discrimination in hiring, exploiting the text of job ads and differences in callbacks to older and younger job applicants from a resume (correspondence study) field experiment (Neumark, Burn, and Button, 2019). Our analysis uses computational linguistics and machine learning methods to examine, in a field-experiment setting, ageist stereotypes that might underlie age discrimination in hiring. In so doing, we develop methods and a framework for analyzing textual data, highlighting the usefulness of various computer science techniques for empirical economics research. We find evidence that language related to stereotypes of older workers sometimes predicts discrimination against older workers. For men, we find evidence that age stereotypes about all three categories we consider - health, personality, and skill - predict age discrimination, and for women, age stereotypes about personality predict age discrimination. In general, the evidence that age stereotypes predict age discrimination is much stronger for men, and our results for men are quite consistent with the industrial psychology literature on age stereotypes.



Why Retirement and Age Discrimination Policies Need to Consider the Intersectional Experiences of Older Women

December 2020

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36 Reads

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1 Citation

Innovation in Aging

We summarize how older women face intersectional experiences that affect their retirement security. These include differential trends in aging, life expectancy, labor supply, work history, retirement savings, and poverty at old age. We also highlight research showing that older women experience significantly more age discrimination than older men. affecting the ability for older women to improve their retirement security by working longer. We demonstrate through examples that these differential trends and intersectional experiences of older women have important policy implications. We provide examples of how Social Security policies, such as increases in the full benefit retirement age and changes to the retirement earnings test, have differential effects on older women. We also discuss how age and gender employment discrimination law fails to protect older women from intersectional sex-plus-age discrimination. We conclude by urging policymakers to consider how older women experience different challenges and how policy should consider their unique experiences.



The role of work values and characteristics in the human capital investment of gays and lesbians

May 2020

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35 Reads

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15 Citations

Education Economics

We show that educational outcomes of sexual minorities are consistent with efforts to mediate future discrimination. Gay men and lesbians obtain more years of schooling than heterosexual men and women, between 0.6 and 1.2 years. This difference is robust to controlling for observable characteristics for men but not women. Gay men and lesbian women also complete different college majors. Gay men are more likely to choose majors with lower levels of prejudice, higher levels of workplace independence, and occupations that emphasize relationships even though they pay less. Similarly, lesbian women choose majors with less prejudice and more workplace independence.


What Does a Job Candidate's Age Signal to Employers?
What Does a Job Candidate's Age Signal to Employers?

March 2020

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128 Reads

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33 Citations

Labour Economics

Research has shown that hiring discrimination is a barrier for older job candidates in many OECD countries. However, little research has delved into why older job candidates are discriminated against. Therefore, we have conducted an online scenario experiment involving recruiters to empirically investigate 15 potential stigma related to older age drawn from a systematic review of the literature. We found that older age particularly signals to recruiters that the applicant has lower technological skill, flexibility, and trainability levels. Together, these perceptions explain about 41% of the effect of age on the probability of being invited to a job interview. In addition, we found that the negative association between age and invitation probability is smaller when recruiters work for firms with a higher percentage of older employees. A DISCUSSION PAPER VERSION OF THIS STUDY IS FREELY DOWNLOADABLE HERE: https://ideas.repec.org/p/zbw/glodps/434.html


Citations (18)


... As examples, the phrases are things like 'good communication and teamwork', 'accounting software systems like Netsuite…' (software that is over 20 years old, and other software we mention is also older), and 2 The job ads were collected as part of a large-scale correspondence study of age discrimination (Neumark et al., 2019a). The present research, in turn, was used to develop a field experiment on how actual job applicants respond to ageist language in job ads (Burn et al., 2022b). 3 Moreover, this would be a reasonable expectation, given the correspondence-study evidence from prior work that the kinds of age-stereotyped phrases from the job ads that we use help predict age discrimination by employers (Burn et al., 2022a). ...

Reference:

Stereotypes of older workers and perceived ageism in job ads: evidence from an experiment
Help Really Wanted? The Impact of Age Stereotypes in Job Ads on Applications from Older Workers
  • Citing Article
  • January 2022

SSRN Electronic Journal

... Ageism, like other concepts related to discrimination, can also occur in various aspects of human life. Specifically regarding ageism, it mostly occurs in the workplace in the form of the assumption that older workers are considered less meticulous and even deemed unproductive in carrying out certain tasks (Burn I, Firoozi D, Ladd D, 2023). ...

Stereotypes of older workers and perceived ageism in job ads: evidence from an experiment

Journal of Pension Economics and Finance

... This is possibly because they perceive the workers to be insufficiently masculine due to their sexual orientation (Tilcsik 2011;Tilcsik et al. 2015;Waite and Denier 2015). More recently, Burn and Martell (2022) found that conforming to gender-typical behaviors and norms improves labor market earnings and labor supply of men. Campbell et al. (2024) also found evidence of gender expression affecting labor market outcomes, reporting that workers who have a feminine gender expression tended to have higher unemployment rate and higher poverty rates. ...

Gender typicality and sexual minority labour market differentials
  • Citing Article
  • April 2022

British Journal of Industrial Relations

... The low rates of transition from unemployment to employment among older workers could be partly attributed to age discrimination and employers' preconceived beliefs regarding older age. Employers might be hesitant to hire senior workers, perceiving them as being less productive, having poorer health, and being less capable of learning than younger employees (Burn et al. 2019). ...

Older Workers Need Not Apply? Ageist Language in Job Ads and Age Discrimination in Hiring
  • Citing Article
  • January 2020

SSRN Electronic Journal

... Thus, they often earmark older candidates for higher-level positions. However, when older job seekers apply for more basic positions, they may be perceived as less competent [47]. Consequently, older job seekers often endure discriminatory treatment. ...

Machine Learning and Perceived Age Stereotypes in Job Ads: Evidence from an Experiment
  • Citing Article
  • January 2021

SSRN Electronic Journal

... Among the many areas of EDI intervention, job advertisements (ads) have garnered growing attention (9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19). Job ads constitute the first point of contact between employers and job seekers, thus playing a crucial role in "gatekeeping" the labor force. ...

Does Ageist Language in Job Ads Predict Age Discrimination in Hiring?

Journal of Labor Economics

... Acknowledging this intersectionality is crucial for policymakers, as age and sex discrimination intersect in shaping the experiences of older women. It is noteworthy that older women, especially those who are single or widowed, are at a higher risk of living in poverty compared to their male counterparts, as highlighted by Burn et al. (2020). Therefore, policymakers should carefully consider the unique challenges faced by older women in the development of policies addressing aging and discrimination. ...

Why Retirement, Social Security, and Age Discrimination Policies Need to Consider the Intersectional Experiences of Older Women

Public Policy & Aging Report

... The scientific investigation of the labour market success of non-heterosexual individuals has branched into both a supply-side (Burn and Martell 2020) and a demandside research tradition (Burn 2018(Burn , 2020. Given that differences in labour market outcomes between sexual majority and minority individuals appear nowadays to be mainly driven by the demand side of the labour market (Fric 2017), it is necessary to further investigate labour market discrimination. ...

The role of work values and characteristics in the human capital investment of gays and lesbians
  • Citing Article
  • May 2020

Education Economics

... More concretely stereotypes represent beliefs about certain characteristics of group members (i.e. the cognitive component), prejudice reflects the emotional reaction to those stereotypes (i.e. the affective component), and discrimination refers to actions based on those stereotypes (i.e. the behavioural component). Indeed, many experiments indicate that stereotyping may affect hiring decisions, and subsequently, result in hiring discrimination against members of different social groups (Van Belle et al. 2018;Sterkens et al. 2021;Van Borm et al. 2021). ...

What Does a Job Candidate's Age Signal to Employers?
  • Citing Article
  • March 2020

Labour Economics