Wilcox etal. (Reference Wilcox, Damarin and McDonald2022) astutely addressed the influence of current cybervetting practices with respect to three main stakeholders: job candidates, hiring managers, and organizations. In light of increased awareness of gender-related biases encumbering equitable organizational decision making (e.g., Gaddis, Reference Gaddis2015), a particularly important and timely consideration raised by Wilcox etal. was the potential for cybervetting to have a discriminatory effect on job candidates. Yet, despite this (very legitimate) concern that cybervetting may risk exacerbating such inequities, we further consider the contrary possibility that in certain contexts it may harbor some potential to mitigate them. To this end, we consider attributional augmenting as a psychological process via which cybervetting has the potential to attenuate inequitable and discriminatory hiring decisions.
Attributional augmenting
Attribution theory (Kelley, Reference Kelley1973) suggests that individuals attribute motives to either internal (e.g., a dispositional attribution) or external (e.g., a situational attribution) causes. One of the general principles of attribution, attributional augmenting, occurs when causes that would be reasonably expected to facilitate a behavior co-occur alongside causes that would be reasonably expected to inhibit that same behavior. In cases when an unexpected behavior occurs, the former (facilitating) causes are afforded extra weight in determining why such a behavior occurred; that is, they are augmented. For example, perceptions of women who are professionally accomplished in a male-dominated industry can be enhanced by attributional augmenting because they not only survived—and thrived—in the industry, but likely did so despite significant gendered obstacles. Such positive yet gender-role-violating behavior may trigger sense making efforts, with the perceiver paying closer attention to the candidate in an attempt to explain the atypical level of success (e.g., Barry & Crant, Reference Barry and Crant2000). When external factors cannot explain a socially desirable unexpected behavior, the perceiver may attribute such behavior to internal, positive qualities—i.e., effort—thereby positively influencing perceptions of the candidate (e.g., Lanaj & Hollenbeck, Reference Lanaj and Hollenbeck2015).
We suggest that augmenting may operate in employee selection when using cybervetting to screen job candidates with marginalized social identities or demographic characteristics such as gender. One of the more seismic shifts in the recruiting and selection landscape in recent decades has been the increasingly prevalent use of social media in the hiring process. We argue that attributional augmenting may be facilitated by candidate profiles on professional online sites (e.g., LinkedIn), which contain rich—and comparatively objective—job-relevant information about potential candidates (Zide etal., Reference Zide, Elman and Shahani-Denning2014); however, augmentation may be impeded by candidate profiles on nonprofessional online sites (e.g., Facebook).
Facebook profiles generally include information—either explicitly or inferentially via profile pictures—about users’ primary demographics, including gender, age (approximate or actual), and race, which research suggests are likely to trigger stereotypes and be associated with interview evaluations, thus raising the potential for hiring discrimination (see Lowman etal., Reference Lowman, Harms and Mills2019). Facebook’s predominantly social (as opposed to professional) nature limits the job-relevant information hiring managers are able to glean from it, thus risking that they lean more heavily on non-job-related and demographic information, increasing the risk of biased decision making. Indeed, research has found that Facebook reliance during hiring decisions has the potential to negatively affect assessments of female candidates in particular (Van Iddekinge etal., Reference Van Iddekinge, Lanivich, Roth and Junco2016).
LinkedIn profiles, on the other hand, despite offering much of the same demographic information as Facebook profiles, also include more job-relevant information such as education level, professional experience, skills, and job history. In these ways, LinkedIn profiles serve as proxy résumés for applicants (Zide etal., Reference Zide, Elman and Shahani-Denning2014), which can facilitate management of one’s professional image (Van Dijck, Reference Van Dijck2013). Based on the realistic accuracy model, characteristics of information (e.g., quality, richness, visibility) influence the accuracy of evaluators’ (here, hiring managers’) judgments (Funder, Reference Funder1995), and in turn, evaluators may be more likely to assign appropriate weight to applicants’ job-relevant achievements and skills—that is, positive internal qualities are augmented—resulting in positive evaluations rather than seeing the candidate predominantly in light of their gender (and associated biases).
We contend that attributional augmenting may be activated when female applicants display positive job-relevant information or characteristics that are counter to gender stereotypes, such as agentic leadership skills. Ahiring manager may make sense of such astereotypical positive behavior by paying closer attention to the candidate’s work-related accomplishments, thereby potentially mitigating the extent to which bias may be introduced during the selection decision. Based on the underlying premise of attributional augmenting, we next consider circumstances under which cybervetting via professional online sites may have the potential to combat gender discrimination in hiring, ultimately helping to create a more equitable hiring landscape for female candidates. Specifically, we suggest that job level and gender composition of jobs both indicate unexpected yet socially desirable behaviors or characteristics which may increase the likelihood of attributional augmenting in these circumstances.
Contextual considerations
Job level
Although women occupy almost half of the workforce, they hold only about a quarter of managerial positions in the private sector (Catalyst, 2017). Many gender stereotypes about women are seen as inconsistent with the attributes believed to be needed for managerial success, thus women are often considered less suitable for executive- or managerial-level roles (Koch etal., Reference Koch, D’Mello and Sackett2015). This is similarly true for jobs in STEM-related fields (Science, Technology, Engineering, and Mathematics) due to their perceived lack of fit (Heilman, Reference Heilman1983) with the job itself. Baron etal. (Reference Baron, Markman and Hirsa2001) found that the process of attributional augmenting altered the gender-biased equation for managerial-level roles, with women perceived more favorably than men when they were described as entrepreneurs. Thus, the overall profile that emerges from cybervetting for female applicants with extensive prior experience in higher level positions increases the likelihood that the hiring manager will consider female applicants’ appropriateness for the position as more comparable to that of male applicants with similar experience—and maybe even more so due to the augmentation effect.
Gender composition of jobs
The extent to which jobs are gender (im)balanced is also relevant with respect to how cybervetting could impact potential biased hiring. Women hold a minority of positions in STEM-related fields (Landivar, Reference Landivar2013), whereas men tend to be underrepresented in the industries of healthcare, elementary education, and domestic work (Croft etal., Reference Croft, Schmader and Block2015). The enduring prevalence of such gendered jobs is problematic for both men and women, and there is increasing recognition of the inequities inherent in many gender-imbalanced jobs. Moreover, research suggests that gender-imbalanced jobs are generally associated with more biased evaluations of candidates (McDonald etal., Reference McDonald, Damarin, McQueen and Grether2020). Yet, as noted earlier, perceptions of women who are professionally accomplished in a male-dominated industry may benefit from attributional augmenting. Specifically, the process underlying attributional augmenting would suggest that those women may be viewed more positively not only with respect to their achieved success in the work itself, but additionally because they were able to achieve that success despite the gender-related obstacles that they were more likely than their male counterparts to have faced. Thus, the perception of their success—and therefore also their potential—is enhanced.
Role of the perceiver
Finally, we suggest that the extent to which evaluators experience attributional augmenting to elevate their perception of the minority demographic candidate is dependent on the role of the perceiver. In the case of selection as it relates to gender considerations, this can be understood to be the gender and job role (e.g., human resources [HR] manager or operational manager) of the evaluator. We propose that female hiring managers may be more likely than male hiring managers to apply attributional augmenting when cybervetting female applicants for an executive position, for example. We expect this would occur because female hiring managers may be more likely than male hiring managers to have experienced obstacles to career advancement similar to those that the candidate has likely encountered, thus giving them an intimate recognition of positive qualities explaining her success, such as additional effort invested or gendered hurdles often overcome by female candidates in order to reach the same level of success as male candidates. Likewise, we propose that HR managers may be more likely than operational hiring managers to apply attributional augmenting to female applicants to male-gendered roles. Compared with operational managers, HR managers are likely more aware of gender biases and trained on how to overcome them in hiring decisions.
Conclusion
We extend Wilcox etal.’s (Reference Wilcox, Damarin and McDonald2022) suggestion that cybervetting may have implications with respect to biased hiring. However, we move beyond the focal article to suggest the alternate possibility that in some circumstances cybervetting may actually have the potential to facilitate a more equitable hiring landscape. We posit that attributional augmenting provides useful insights into these questions and consider important contextual considerations that serve to shape the landscape in which cybervetting occurs in relation to candidate gender.
Open access
