Implicit Gender Bias in Recruitment Varun Sriram

M. S. Game Science and Design Northeastern University sriram.v@husky.neu.edu

Abstract

Gender is a range of characteristics pertaining to, and differentiating, but not limiting masculinity and femininity. Improper creation of stereotypes pertaining to gender creates bias towards genders in various social and professional scenarios ultimately leading to partiality in decision towards males and females. The goal of this study is to find out whether this particular bias is present in minds of the people. 13 participants who were involved in the study will be asked to recruit between male and female candidates to work for their company. Along with the power of choice, the participants answered a simple follow up question regarding their decision. Keywords: Gender Bias, Hiring, Recruitment, Cognitive Bias, Unconscious Bias.

Introduction Gender plays a very important role in reflecting an individual's personality. A lens through which we perceive others and also define ourselves. Gender is amongst the first distinguishes you learn to make as a child. Although gender does define an individual in some way, it does not limit an individual’s intellectual capabilities and strengths. “Gender is a multilevel system of differences and disadvantages that includes socioeconomic arrangements and widely held cultural beliefs at the macro level, ways of behaving in relation to others at the interactional level, and acquired traits and identities at the individual level.”(Cecilia R,1997)implicit beliefs are those that are held and activated subconsciously, without awareness, limiting how accurately people can report these ideas (Kellogg, 2003; Moskowitz, 2005). Some have hypothesized that implicit beliefs are more strongly associated with an individual’s actual behaviors (Fazio & Olson, 2003). The objective of this paper is to determine the existence of gender implicit bias while offering employment. Do people take decisions based on the qualifications of an individual alone or does gender of an individual play a part? The study states the below hypothesis. H0: People recruit employees on the basis of their experience and qualifications, not gender. H1: People recruit employees on the basis of their experience, qualifications and gender.

Background Proper and rational decision making is paramount in any life circumstances. It certainly holds more importance when an individual’s decision could have an impact on an organisational institution and its progress. When a person is in charge of recruiting people in a company, the decision making has to be made rational and prudent. Human mind is the most evolved of all species which can function on logical reasons. Although, human mind is not as always believed to be taken decisions rationally. In his 2011 tome on cognition, Thinking, Fast and Slow, Daniel Kahneman articulates a widely accepted framework for understanding human cognitive functioning by delineating our mental processing into two parts: System 1 and System 2(Cheryl, 2016) .While system 1 works on conscious decision making, system 2 relies on the subconscious mind. The decisions that are taken by the the subconscious mind are dependent on the individual’s opinions and notions. Because the implicit associations we hold arise outside of conscious awareness, implicit biases do not necessarily align with our explicit beliefs and stated intentions (Cheryl, 2016). “The biases that are formed on basis of a particular gender are called implicit gender biases. It is well documented that currently accepted gender stereotypes incorporate assumptions of men's greater status value; ie. men's traits are generally viewed as more valuable than women's, and men are diffusely judged as more competent.” (Broverman et al., 1972; Deaux & Kite 1987; Eagly, 1987). In a paper by(Carol I., Barbara L., Molly C, 2009)it has been indicated that, when ambiguity exists in an individual's qualifications or competence, evaluators will fill the void with assumptions drawn from gendered stereotypes. The main focus of this study is to find whether for certain positions, do people hire men over women in spite of qualifications and experience?

Method

Participants Participants who took part in this experiment were family, friends and peers. The game/study was created on StudyCrafter and shared over social media for the people to play.

Design and Experimental Manipulation In this study, there are two sets of independent variables, gender and the qualification. The dependent variable is the resumes that the participants will scrutinize and choose. The independent nominal variable gender(Male, Female) is the reason why this study is being conducted. The resumes will have gender but correlation between the skillset in the resume to the gender is unknown to the participant. The next independent ordinal variable is the qualification of the candidate(High, Medium). Similar to the previous point, the correspondence between the qualifications and the candidate is unknown to the participant. The dependent variable is the choice given to the person to choose between to candidates as he owns the power to select the rightful candidate.

Materials The experiment was made by using StudyCrafter which was uploaded online on the website. This platform has been developed to innovate in education, in particular to empower and enable students to perform experimental research. No personal data was collected from the participants and the participation was completely anonymous. Only the input which was the dependent variable was recorded and was used as data.

Procedure The participants will play the role of a Hiring Manager and his job will be to choose the right candidate for a position in an engineering company. He will be provided with 4 sets of a pair of CV/resume. The participant will have to scrutinize them and choose the rightful candidate for the position. Depending on his choice, his rationale behind the choice will be questioned with an open ended question.

Resume list:

Candidate A Candidate B

Highly Qualified Man Moderately Qualified Woman

Moderately Qualified Man Highly Qualified Woman

Highly Qualified Woman Moderately Qualified Man

Highly Qualified Man Moderately Qualified Woman

The above table represents the set of candidate resumes the participant will have to scrutinize and select. Simply using the above table will make it hard to attribute as to why people choose one participant over the other. Thus, another list of resume was created with sets swapped with each other. Implementing a randomized list will yield better chances since randomization produces a variety of answers. Along with the objective of choosing the right candidate, the participants’ rationale behind the choice is questioned in the form of open ended responses. Referring to the table above, if either of the candidate is hired from a set, the hired person’s cell in the gets incremented by one and the candidate not hired is awarded a point in the “not hired” table.

Results Table below represents the distribution of candidates hired:

Hired Not Hired

High Medium High Medium

Male 20 2 6 24

Female 24 6 2 20 Computing a chi square test for the above table: Pearson's Chi-squared test

data: x X-squared = 4.7273, df = 3, p-value = 0.1929 Since the computed p-values is greater than 5%, it is conclusive evidence that the null hypothesis is true, participants recruited candidates based on their qualifications and skills and not gender. Some significant ratios: Recruitment of Highly Qualified Male= 20/52 Recruitment of Highly Qualified Female= 24/52 Recruitment of Moderately Qualified Male= 2/52 Recruitment of Moderately Qualified Female= 6/52 The ratios clearly signify that there is a borderline bias towards female hiring.

Discussion Overall, the results from the chi square test sheds light on the fact that there is not gender bias when it came to recruitment. On the contrary, numbers suggest that female candidates were chosen more than male candidates, especially the fact that moderately qualified women were chosen over highly qualified male. There are some interesting reasons provided by the participants to bolster the choice mentioned above. “She insists on her personal skills when the other only highlight an area of expertise. The skills that she chose to add to the resume give information on her vision of work, what she thinks is important to manage a team, and I agree with this vision. I also valued the fact that she has senior experience in a challenging sector: she might be thorough and efficient in her work. “ and “Want someone to lead a new team which needs to be set up. Also, chose Sophia because she has highlighted the leadership qualities which is necessary for the position of a manager/lead of the new team.“ There are two sects discovered during the study. People who choose GPA/academics over work experience and vice versa. Both sects have almost similar ratio of about 12/52 stating that excelling at academics and no work experience is equivalent to having more work experience. Another interesting perspective was noticed in one of the participants, he/she considered himself to be the boss of the selected candidates. One of his response for choosing candidate B over A was “This candidate has higher GPA and longer experiences. I think I need a strong technical guy because I am his boss. I value his actual work ability more.” An HR manager hires employees to the company, on the contrary, this participant overlooked this fact and employed candidates into his own team.

Conclusion Thus, the chi square test supports the null hypothesis validating that there is no gender bias when recruiters choose candidates to work for their company. Although there is a slight positive bias towards female candidate recruitment, their numbers isn’t enough to affect the overall result.

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Systematic Review. HHS Public Access. doi:10.1097/ACM.0b013e3181b6ba00.  Koenig, A. M., Eagly, A. H., Mitchell, A. A., & Ristikari, T. (2011). Are leader stereotypes                               

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APPENDIX

R scripts for Chi-Square test: Code: x <- matrix(c(20,2,6,24,24,6,2,20), byrow = TRUE, 2,4) View(x) rownames(x)<-c("Male","Female") colnames(x) <- c("Highly qualified Hired","Moderately qualified Hired", "Highly qualified Not-Hired","Moderately qualified Not-Hired") chisq.test(x) Output: [Workspace loaded from ~/.RData] > x <- matrix(c(20,2,6,24,24,6,2,20), byrow = TRUE, 2,4) > View(x) > rownames(x)<-c("Male","Female") > colnames(x) <- c("Highly qualified Hired","Moderately qualified Hired", "Highly qualified Not-Hired","Moderately qualified Not-Hired") > chisq.test(x)

Pearson's Chi-squared test data: x X-squared = 4.7273, df = 3, p-value = 0.1929 Images from studycrafter