“Referral or favoritism?” — recommendations, networks and unequal access

The team is discussing an open role. Karim tells Anna and Jonas about someone he used to work with.

— I know someone excellent. I worked with her for three years. I’d vouch for her.
— So people with the right connections get a side door in? — Jonas asks.

Karim sees extra information about a candidate. Jonas sees an advantage that an equally strong candidate without the right contacts cannot obtain.

What really happened

Karim trusts the recommendation because he sees it as additional information. The person making the referral puts their own reputation on the line, so their judgment can be a useful signal that is missing from a CV. Jonas is looking at the other consequence of the same mechanism: a candidate without connections cannot produce that extra signal, even if they are equally capable. A referral can therefore reduce uncertainty for the employer while increasing the advantage of people who already have access to the right network. This is not simply a choice between “connections” and “common sense”. Both functions of networks are real.

What the research says

Labor-market research shows that referrals can provide employers with information that formal hiring processes do not capture and, under some conditions, can improve matching and subsequent employee outcomes (Di Stasio & Gërxhani, 2015; Burks et al., 2020). At the same time, social networks tend to resemble the people who hold them: we are more likely to know people with similar backgrounds, gender or social environments—a pattern known as homophily. Research shows that referral systems can therefore reproduce inequality and segregation even without an explicit intention to discriminate (Tassier & Menczer, 2008; Takács, Bravo & Squazzoni, 2018; Buhai & van der Leij, 2023; Hensvik et al., 2025). A recommendation can be a useful signal without being a neutral access channel.

How to handle it

Treat a referral as one source of information, not as a pass to the outcome. Referred candidates should still go through the same core criteria as everyone else. Organizations should also avoid relying only on current employees’ networks, because over time that can make the workforce reproduce itself. Keep two questions separate: “Is this person good?” and “Do equally good candidates have a comparable chance of entering the process?” The general rule: use the information embedded in relationships, but do not let the relationship itself replace assessment of competence or become the only route into the process.

How Empatyzer and Em can help

Empatyzer can help the team separate two issues that are easy to conflate: the value of a recommendation and the right to make the decision. Karim may see a referral as valuable information backed by personal reputation; Jonas may see the structural advantage that comes with having the right contacts. Em can help a leader draw the boundary clearly: “The recommendation gives us another source of information, but the candidate will be assessed against the same criteria as everyone else.” Empatyzer is not a candidate-selection tool and should not make hiring decisions from psychometric profiles. It can, however, help people discuss trust, fairness and status without casting one side as naive and the other as cynical. Micro-lessons reinforce the principle that relationships can improve information quality, but should not replace transparent decision criteria.