treatment CVs that include socioemotional skill signals, both providing information on the same type of task performed at work. For example, for the IT cluster we identified four types of tasks: tasks related to (1) server, (2) internet, (3) software or website, and (4) hardware and maintenance. For each of these tasks, we create alternative bullets for control and treatment CVs. For example, one neutral sentence for a hardware-related task would state “Provided support for technical failures with equipment such as PC, printer or scanner,” whereas the alternative sentence that signals teamwork would state “Worked as a team in identifying deficiencies and supplying the necessary hardware.” We then randomly allocate four neutral sentences to the control CVs’ job description, and one neutral sentence and three sentences that signal each of the three socioemotional skills separately to the treatment CVs’ job description.

For generation of realistic, credible, and comparable extracurricular activities, we benefitted from the way candidates signaled their socioemotional skills in the reverse audit study as well as interviews with human resources personnel and a focus group discussion with university placement directors of two prominent universities in Ankara, Turkey. To keep the CV length compatible between control and treatment CVs and to signal high cognitive skills for our candidates, in the same section we also added a sentence in both control and treatment CVs that indicates the candidate was an honors student in their undergraduate university.

Finally, for the taglines, we create comparable statements regarding the current job of the candidate. For the control versions, we include information that is available in the CV characteristics listed below the tagline, for example, of the form “IT specialist who has an experience of 3 years in solving software/hardware issues, internet and servers.” For the treatment versions instead, we signal at least one socioemotional skill within the tagline as well: “A determined IT specialist who can coordinate with the team members to provide detailed solutions to server, internet, software or hardware problems.” Examples of alternative job descriptions, extracurricular activities, and taglines created in this way are given in Table 18 in Appendix C.

# _Background characteristics_

The goal in the design of the CVs is to generate CVs that are equivalent except for the treatment variables. We therefore assign the other background characteristics either randomly, or we make the characteristic the same for all candidates of the same cluster and/or location.

Age (date of birth): We varied date of birth from September 1989 to December 1991, which implies that our candidates were 25 to 28 at the time of application. We imposed about a 6-month difference in age by gender, with female candidates being, on average, 6 months younger than male candidates. The imposed difference was necessitated by most vacancies requiring men to have completed their compulsory military service at the time of application. Military service in Turkey is compulsory only for men and lasts for about 6 months. Since men and women graduate at the same time of the year (June), our male and female CVs could be equated either on the length of work experience (in months) or on age. We chose the former option. As we know that employers can have age-related preferences, we always control for age in the analysis.

Job experience: Jobs are assigned randomly from a set of available jobs and positions collected from online sources for the selected occupational clusters. We assigned the number of positions held so that 75 9