Our social networks are partially ascribed from the day we are born, escalate into a larger web throughout our lifetime, and can give us a significant advantage in the labour market. Segolene Zeller writes that our social capital becomes an ascribed status, alongside gender, family lineage, and skin colour. Since interacting across social boundaries may be difficult, our social networks tend to lack diversity. She suggests using behavioural science strategies in the design of organisational processes to support employees in creating the necessary change. 

An individual’s network often lacks significant diversity. In fact, “ (…) individuals’ networks and networks within associations, organisations, and communities, are often homogenous along key dimensions, such as race, age, and sex” (Kim, 2005, p. 60). Evidence from large-scale surveys has demonstrated homogeneity in large systems (Burt 1985, Marsden 1987, Fischer 1982). Individuals like to associate themselves with others of similar backgrounds and interests, which can result in environments where the friends of our friends are already our friends, rather than strangers.

Network closure creates benefits for members, “(…) such as trust development, meticulous enforcement of norms, and rapid diffusion of knowledge” (Kim, 2005, p.70). Research by Nahapiet et al (1998) shows that there is an organisational advantage, in part, due to social networks (sometimes also referred as our “social capital”) facilitating the creation and sharing of intellectual capital (Nahapiet et al, 1998). Finding yourself in a particular network group can give you a significant advantage within the sphere. On the other hand, interacting across social boundaries may be harder to achieve. These social groups can lead us to be faced with bounded rationality which consists of our tendency to rely on the safety of familiarity and to remain in homogeneous relationships, rather than pursue potential gains from a more diverse network (Kim, 2005). Thus, the networks you find yourself to be part of can significantly define opportunities that will be available to you.

While we can have certain control over the networks that we chose to be part of, most of the networks we find ourselves in are partially “ascribed,” and can either give you advantages or disadvantages, based on whether you find yourself within or outside the network structure of interest. In ‘The Study of Man’, Ralph Linton (1936) first defined ascribed statuses as those which are assigned to an individual without their control (e.g., gender, family lineage, skin colour): “People can be accorded status through inheritance or as a result of characteristics, such as social class, gender, or race” (Shelby, 2005, p.262). In other words, individuals are respected because of the family they are born into, their affiliations and group membership, and their age and seniority (Shelby, 2005). For example, in an ascribed society like India, it is accepted that social class and gender accrue distinct advantages and rights (Shelby, 2005).

In this article we demonstrate how our social networks are partially ascribed from the day we are born, escalate into a larger web throughout our lifetime, and can give us a significant advantage in the labour market. We argue that our social capital becomes an ascribed status, alongside gender, family lineage, and skin colour. If we get lucky enough to find ourselves in the circles which provide the opportunities we set to achieve, we will advance much quicker towards our goals.

The centre of what we will call our “spiderweb” starts when we are born, as our family and upbringing set us up into the first layer of the mesh. We inherit our families’ network, and we are born into a certain socio-economic background. For example, studies suggest that social interactions at the level of the residential neighbourhood have an effect on labour market outcomes (Bayer et al, 2008). Thus, as social networks stem from residential segregation, we can infer that they are partially race or ethnic-based (Judith, 2011). As we age, our network grows through our education, as we meet future classmates and have access to institutions that greatly differ in benefits. This can afford us various advantages in our professional network. Our network develops further as we enter the workforce and connect with organisational decision-makers and coworkers. Understanding the origin of networks and their homogeneity and ascribed traits is important to discern differences across groups in labour market outcomes. Since well-connected networks are a symptom of having some privilege and can be questioned as actual representations of merit, we seek to explore how these advantages play out in organisational activities.

Firstly, these ascribed networks can be used unintentionally as signals in the recruiting process. Research by Rees (1966) shows that employees tend to instinctively recommend people like themselves. Fernandez and his colleagues (2000) also reported that new hires referred by current employees in a phone call centre were significantly more likely to be similar to current employees than non-referred new hires. Similarities lay in characteristics such as education, and gender (p<.001). Candidates who were referred and their referrals differed by 1.77 years of education and 33% of them were from different genders (Fernandez et al, 2000). Further studies also demonstrated that candidates recommended by current employees received preferential treatment (Brown et al 2016; Pinkston, 2012; Bartus 2001; Datcher 1983) and that word-of-mouth candidates have a greater chance of being hired (Yakubovich and Lup, 2006; Fernandez and Weiberg, 1997). This is confirmed by OECD’s (2013) research that finds that people with more extensive social networks tend to have a higher likelihood of employment (OECD).

Educational signals can come into play as we tend to prefer hiring candidates that come from similar institutions to us. For example, 37% of managers who attended top-ranked universities preferred to hire graduates from similar schools (Lambropoulos, 2016). Network privileges also seem to be exacerbated in ambiguous situations. Research by Fossati (2020) demonstrated that employers seem to attend more to a candidate’s educational background when the information at hand is limited, uncertain, or conveys ambiguous signals (Fossati). Thus, our networks can be used as a hiring instrument. The webs we are born into push us into certain educational networks and seem to serve as a basis for recruiting colleagues similar to us.

Once we get hired into work institutions, we start building our “work webs” and network privilege can persist from the connections we can access. Studies show that it is harder for women to build and nurture their work relationships (Ibarra, 2016). A couple of reasons for this, including the tendency to more easily connect with people who are similar to us, is that males dominate the senior ranks in organisations, which leads to women often having a harder time building relationships with decision-makers and influential stakeholders (Ibarra, 2016). Networking across organisational hierarchies is already hard enough that adding gender into the equation increases the difficulty. Men’s networks often overlap with their work, much more than for women (Ibarra, 2016). For example, an analysis of 67 developed and developing countries shows that women are less likely than men to know an entrepreneur (World Bank Group Gender & Development, 2014); while 42.2% of men had such affiliations, only 33% of women did so globally (GEM, 2019). Women can also be consistently excluded from informal gatherings such as golf games and happy hours, which can result in it taking longer to build trust with colleagues, and the networks necessary to progress within a company (Ibarra, 2016). Thus, these all contribute to unequal opportunities in the labour market, as explained by disadvantages in ascribed networks. The networks we are born into drive us into our educational networks, and our educational networks lead us into professional networks that are further driven by market inequalities.

As we have seen, many of our opportunities are inherently driven by the connections we make throughout our lifetime, and most of these stem from “ascribed ties.” Since our social networks seem to lead to significant advantages or disadvantages in the job market, it is crucial to find ways to mitigate inequalities that stem from ascribed social networks and to attempt to equalise the playing field. This article outlines a couple of ideas of interventions that may help us achieve this. A first suggestion is to redefine the default incentive structures in organisations. Organisations should focus on bringing awareness to these privileges and possibly redesign internal processes to promote equal opportunities.

In terms of recruiting practises, more research is needed to understand the impact of referral hiring on diversity outcomes and to test interventions to mitigate this challenge. For example, are referral bonus programs helping or harming diversity outcomes? What can explain the lack of action? Do organisations care for the diversity of their teams? While more and more research reveals the benefits of diversity on company outcomes (Marder, 2021; Rock et al 2019), there might still be an intention-behaviour gap. The intention-behaviour gap is the discrepancy between an individual’s intention to change a behaviour, and the lack of action that follows. Using behavioural science strategies in the design of organisational processes can support employees in creating the necessary change. If referral hiring is proven to harm the diversity of organisations, framing the problem as a loss at the point of the decision could help motivate the change that is needed.

Additionally, organisational training to inspire and develop skills and abilities for employees to network outside of their direct network links can help mitigate network inequalities in the labour market by allowing more diverse talent into the candidate pool. For example, as part of their Diversity and Inclusion initiatives, Slack partnered with ​The Next Chapter​, an apprenticeship program for formerly incarcerated individuals in which they train and hire these citizens​ to become engineers (Fluker, 2021). Using behavioural change strategies such as commitment devices or nudges, in combination with technology tools, could help drive the behaviour change needed (Cecchi-Dimeglio, 2017; Thompson, 2020) to attenuate network inequalities. Maintaining awareness of these inequalities is also crucial and could be taught at school as part of the educational system or at job search entities before an individual joins the professional world. This will empower individuals to build their own network structures.

Finally, as the number of diverse employees (e.g., women) in senior ranking positions increase, more role models will be within reach, enabling under-represented groups to build connections with organisation decision-makers more easily. Changing organisational cultural norms to be more inclusive to under-represented groups (e.g., by building more opportunities for women to connect with coworkers aside from after-work happy hours when they have more of an opportunity to attend) will level the playing field. As evidenced in this paper, we progress through various network groups that are partially assigned to us, which either advantage or disadvantage us over the course of our lifetime.

♣♣♣

Notes:

• This blog post represents the views of the author(s), not the position of LSE Business Review or the London School of Economics and Political Science.
• Featured image by Buecherwurm_65, under a Pixabay licence
• When you leave a comment, you’re agreeing to our Comment Policy.

Print Friendly