3.1  Microaggression in videoconferencing

The term ‘microaggressions’ was coined to identify every day and ‘normalised’, even if sometimes unintentional, expressions of racism – including verbal, behavioural or environmental indignities, slights and insults toward people of colour (Sue, Capodilupo and Torino, 2007).

It was later found that it could also be useful to identify:

As the quote implies, this is a complex phenomenon that can take different forms as can be seen in this graph from the WomenTech Network (2025) – Figure 5.

Figure 5  Forms of gender-based microaggression experienced at work

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WomenTech Network (2025)

Title: What is the most common form of gender-based microaggression you experience or have experienced at work?

This circular (donut) chart illustrates the most common forms of gender-based microaggressions experienced in workplace settings:

• Being spoken over at meetings = 64%

• Being pigeonholed by cliché = 19%

• Being asked to supply the food = 11%

• Other = 0%

Figure 5  Forms of gender-based microaggression experienced at work

In video conferencing spaces, this from of aggression can take on different forms, becoming more serious the more persistent or repeated they are over time. These include:

• Micro assault: for example, name-calling.
• Microinsults or ‘subtle snubs’.
• Microinvalidation of someone’s voice or knowledge.
• Abrupt interruption when someone is speaking.
• Patronising gendered communication like ‘mansplaining’ – this is a pejorative term used for when a man explains something, usually to a woman, in an overconfident, condescending manner, without regard to their expertise.

In Unit 1, Section 4, you were introduced to the Social Identity Wheel and the idea that different identities impact the ways you experience the world and how others might see and treat you. We all have many social identities that come together or intersect in ways that shape our experiences of privilege and discrimination. The idea that different social identities intersect is known as ‘intersectionality’. You will learn more about this idea in Unit 3.

How microaggressions are performed or experienced is shaped by different, intersecting social identities (e.g. gender, race, sexuality and so on). It is important to highlight that some people, namely those from minoritised groups, are not only targeted more often but are less likely to be given social support from their peers and are met with more negative consequences after enduring this type of assault (Biglia and Toledo, 2020).

Figure 6  Minority groups reporting being discriminated against (Eurobarometer, 2023)

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Special Eurobarometer 535: Discrimination in the EU

This infographic compares the percentage of people who report experiencing discrimination based on whether they identify as part of a minority group.

Title at top of image: Those who consider themselves part of a minority group are more likely to say they have been discriminated against for those who consider themselves:

Large teal circles then display percentages:

• 83% part of a minority because of their gender identity

• 64% part of a minority because of their sexual orientation

• 61% part of a minority because of their skin colour

• 60% part of an ethnic minority

• 56% A Roma person

• 54% part of a minority because of their disabilities

• 46% part of a religious minority

The layout visually contrasts these experiences, with higher percentages clustered on the left-hand side.

The figure conveys a clear pattern: belonging to a minority group substantially increases the likelihood of encountering discrimination.

Figure 6  Minority groups reporting being discriminated against (Eurobarometer, 2023)

Data from a survey carried out by an American company, Lean In (2024), shows how intersectionality is a key factor in the triggering of these microaggressions and that, contrary to what might be expected, there are several cases where these have increased from 2019 to 2024. The questioning of the expertise of women with disabilities and/or those belonging to the LGBTQI+ community, for example, is extremely high and shows an upward trend in the case of LGBTQI+ women.