The Impact of Benevolent Sexism on Women’s Career Growth: A Moderated Serial Mediation Model

If you picture what 'sexism in the workplace' looks like, you're probably thinking about something overt and obvious: a boss that dismisses women's ideas, a coworker that makes inappropriate comments, or an executive team comprised solely of men. But there's actually another type of workplace sexism. It's something much less obvious and far more subtle. It's called benevolent sexism.

Today's paper is an exploration of what it is, how it works, why it might be hard to spot, and what (if anything) we can do about it. In this study, the authors surveyed 400+ female employees across 18 industries, measuring their experiences with sexism, their self-esteem, their emotional exhaustion, and their use of different career development strategies. Then, they statistically modeled how these factors interacted over time. What the authors uncovered was a subtle but compelling pattern. What might seem like "positive" treatment turned out to have a hidden cost, but the study also points to strategies that can help push back against those effects. On today's episode, we're going to break down their research, see how they arrived at their conclusions, and try to figure out whether (or not) these arguments are solid. Let's dive in.

The authors draw on a framework called Ambivalent Sexism Theory, which I think is a useful mental model for this topic. It breaks sexism into two types: hostile and benevolent.

• Hostile sexism is the classic type that you're already familiar with: openly negative attitudes toward women, treating them as either incompetent, or manipulative, or inferior to men. This is the overt discrimination that shows up in hiring, pay, and promotion decisions. This kind of sexism is straightforward to spot and easy to condemn.
• Benevolent sexism is different. It sprouts from the "women should be cherished" type of thinking. The idea that women are pure, innocent, or in need of protection. On its face, this can sound chivalrous or even respectful. The issue is that this framing still assumes dependency. It casts women as fragile, emotional, and in need of guidance, which is incompatible with workplace equality. It structurally limits women's autonomy, discourages risk-taking, and cuts access to leadership roles.

Here's the thing: while hostile sexism provokes resistance, benevolent sexism often earns agreement. Sometimes, even from women themselves. And whereas hostile sexism might be recognized as discriminatory, benevolent sexism is much more socially acceptable. But that makes it more insidious. It's this quiet contradiction that makes the topic so tricky to unpack.

In this paper, the authors hypothesized that benevolent sexism undermines women's career growth indirectly, first by lowering self-esteem and then by increasing emotional exhaustion. They also believed that women who actively engage in career development strategies (like networking, seeking feedback, or self-nomination) would be better able to defend against those effects. This study is their attempt to validate those hypotheses. So how did they do it?

The framework for this study is Cognitive-Affective Personality System theory (CAPS). It posits that one's personality is comprised of cognitive-affective units, or CAUs, which include how we encode and evaluate ourselves, others, and situations, along with our goals, expectations, beliefs, and emotional states. The key idea is that different situations activate different CAUs, which then influence behavior. So something like benevolent sexism doesn't need to directly impact career growth to have an effect. Instead, it could just activate specific cognitive and emotional responses that then shape work performance and career outcomes. That is: if benevolent sexism can activate specific CAUs, then it can have measurable indirect effects on a woman's career. The authors believe this happens through two pathways: a cognitive pathway involving self-esteem, and an emotional pathway involving emotional exhaustion. And these two pathways work in sequence. Benevolent sexism reduces self-esteem, which then increases emotional exhaustion, which finally impacts career growth. This is what's called "serial mediation": one variable influences a second variable, which then influences a third variable, creating a chain of effects rather than each variable acting independently.

Let's talk about the first mediator: self-esteem. An individual's overall evaluation of their self-worth and self-respect. It can be positive or negative, and while it's generally stable over the long term, it can be significantly influenced by situational factors in the short term. This distinction matters because the authors are arguing that benevolent sexism acts as one of those short-term situational triggers. When women are exposed to benevolent sexism, it adversely affects their self-evaluation and triggers negative self-cognition. It affects women's recognition of their abilities by reinforcing dependence and incompetence, especially when these attitudes are communicated by powerful people like supervisors. For example:

• Female employees often receive feedback based on personality traits, while male employees receive feedback based on skills and results. This can undermine women's confidence in their abilities and self-worth.
• When women are praised for their appearance rather than their abilities, they may internalize the belief that their value is primarily based on looks, which reduces self-esteem.

Experiencing (or even just witnessing) benevolent sexism can lead to increased self-objectification and body shame. This reduced self-esteem then limits motivation and ability for career development. Women with lower self-esteem are less likely to pursue leadership positions, negotiate for higher salaries, or seek career advancement opportunities, particularly in traditionally male-dominated fields. This diminished self-esteem makes them more vulnerable and creates difficulty in aligning their personal identity with their professional roles, which then negatively impacts job satisfaction and career growth.

Now let's talk about the second mediator: emotional exhaustion.This is a state of being emotionally and physically drained due to prolonged workplace demands. Some might call it emotional burnout. It's characterized by persistent fatigue, a lack of motivation, and diminished effectiveness in task performance. According to CAPS theory, emotional exhaustion develops through the emotional experience pathway as an affective manifestation of those cognitive-affective units. When women perceive benevolent sexism it can undermine their sense of competence and trigger stress responses. This leads to anxiety and self-doubt, which can transform into stable behaviors like avoiding leadership roles, hesitating to voice opinions, or conforming to expectations out of fear of judgment. But how does benevolent sexism create emotional exhaustion? Well it's through two mechanisms.

• On one hand, it increases women's anxiety and uncertainty, leading to a lack of confidence in professional abilities, feelings of insecurity, and self-doubt.
• On the other hand, it requires women to show certain emotions like obedience and tenderness, which may conflict with actual job requirements and increase the burden of emotional labor.

All that being said, there's still hope: in the form of a potential buffer. Not a solution to the problem, but a way to potentially lessen the worst effects: career development strategies.

Career development strategies, or CDS are things like self-nomination and self-presentation, networking, and the like. The authors argue that CDS functions as a form of self-regulation: the uniquely human ability to consciously control and adjust one's thoughts, emotions, impulses, and behaviors to align with social expectations or personal goals. The hypothesis is that CDS can moderate the negative impact of benevolent sexism on self-esteem, which would then reduce the serial mediation effect through emotional exhaustion to career growth. In other words: if you can protect self-esteem, you can interrupt the chain at the first step, and cut off (or at least lessen) the downstream effects.

To test this, they used snowball sampling to collect data from female employees across several industries: accommodation and catering, wholesale and retail, education and training, and medical and health. Questionnaires were distributed to these organizations in collaboration with the HR managers, and eventually reached over 400 participants. To minimize common method bias, (which occurs when both predictor and outcome variables are collected from the same source at the same time), data collection was conducted in three waves with one-month intervals between each stage. This temporal separation is important because it helps ensure that responses aren't artificially inflated just because someone is filling out the whole survey at once while in a particular mood or mindset. The questionnaires featured varied response formats and scales to further mitigate these risks.

• In the first wave, respondents provided information on their understanding of benevolent sexism and their demographic information.
• In the second wave, data on self-esteem and emotional exhaustion were collected.
• The third wave focused on gathering information on career development strategies and career growth.

Once the survey results were collected, the authors conducted confirmatory factor analysis (CFA) to assess discriminant validity of all the variables. CFA tests whether your measurement model actually fits the data. The idea is to see if treating each construct as a separate, distinct thing makes more sense than lumping them together in various combinations. They found that a five-factor model, which treated benevolent sexism, self-esteem, emotional exhaustion, career growth, and career development strategies as separate constructs, demonstrated the best fit compared to alternative models. The fit indices all fell within acceptable ranges, with the comparative fit index and Tucker-Lewis index both around 0.9, and the root mean square error of approximation around 0.04. For context, values above 0.9 for the fit indices and below 0.05 for the error measure generally indicate good model fit.

For hypothesis testing, they used the PROCESS macro: an add-on for SPSS that automates the analysis of mediation, moderation, and conditional process (that is, moderated-mediation models). The macro essentially acts as a wrapper that runs multiple regression models in a specific causal sequence, computes indirect effects, and then uses bootstrapping (resampling the data thousands of times) to generate bias-corrected confidence intervals for those effects. In this study, the macro was used to estimate both serial mediation and moderation within the same structural pathway, a design sometimes called a moderated serial mediation model. It allowed the authors to test this multi-stage, conditional chain without building a full structural equation model in Mplus. It provided regression coefficients, effect sizes, and significance levels for each link in the process simultaneously.

So what did they find?

• Benevolent sexism was negatively related to career growth. It had a significant negative relationship with self-esteem and was positively related to emotional exhaustion.
• Both self-esteem and emotional exhaustion played mediating roles. That is, each one helped explain how benevolent sexism leads to stalled career progress.
• The authors found a chain reaction: benevolent sexism reduced self-esteem, which increased emotional exhaustion, which then impacted career growth. This kind of step-by-step pathway is known as serial mediation.
• But there was also a buffer. Women who actively used career development strategies (like networking, seeking feedback, or self-nomination) were less affected. Specifically, the link between benevolent sexism and self-esteem was only significant among women with low levels of those strategies. For women with high levels, that link disappeared.

But what else can we learn from this paper? Namely, that it's possible to take a subtle form of discrimination and make its mechanisms visible with statistical modeling. The serial mediation model is valuable because it shows that the damage isn't direct, but works through a cascade of effects. This kind of analysis is broadly cross-applicable to any domain where indirect or "second-order" harms are suspected. It can be used to trace how microaggressions influence academic outcomes, how stereotyping degrades performance, or how organizational culture impacts employee well-being and turnover. This method gives researchers a way to quantify the hidden causal architecture of bias, translating what feels intangible or cultural into a measurable chain of relationships that can be tested, replicated, and, ideally, interrupted.