A Day in the Life of Maria: Navigating a Biased World


Maria is a 35-year old woman, born and raised in Mexico.

She moved to the UK 13 years ago, got a degree in Maths and Economics and started working in Finance in London post-grad. She married Luca 9 years ago and has two children, Rita and Julio, aged 8 and 3. Let’s examine her life from close up to try and better understand some of the challenges she faces in our biased world.

This Thursday morning is like every other morning.

Maria wakes up just before 6 am and starts her day with what can only be called unpaid labour. Skip the meditation and gratefulness journaling: her time-pressured morning involves unloading the dishwasher, folding laundry and a daily session of vigorous scrubbing of stubborn stains from Julio’s clothes. She prepares breakfast options for all: cut up fruit, cereal, toast and spreads, and scrambled eggs with two sausages for her husband, who is due back from a night shift as a nurse (writing this, my mind thought ‘male nurse’, as if it needs to be specified because I associate nurse with woman: it’s important to remember that we ALL have biases).

Globally women do three times the amount of unpaid work men do; twice the amount of childcare, and four times the amount of house chores. On average, women spend between three and six hours a day on unpaid labour, compared to men’s thirty minutes to two hours (3).

Maria will prepare breakfast and dinner most days and do more laundry and dishes than her husband Luca. Although she feels tired and dissatisfied with the amount of time she has left to relax in the evening, she doesn’t necessarily question the inequality between how much unpaid labour she does vs how much Luca does. She was raised in a family where her mother and grandmother did more of the cooking and cleaning, and so was Luca. She feels it is her unspoken role to take care of the house and children, even though she and her husband work similar hours (of paid labour that is…).

 After having dropped her children off at school, she drives to work. She has been promoted to a managerial role three months ago and has a meeting with HR to discuss her colleagues’ written feedback about her, which she is not entirely happy with. Consistently, her performance has been deemed excellent, the numbers say it all. It’s her personality and likability that have been criticised. She feels some of her team act differently around her since her promotion. One member of her team named Charles called her ‘assertive’ – interestingly he employed that same word to describe the previous white male manager a few months ago.

Back then he wrote: “Richard interrupts when is necessary. His assertiveness in meetings allows us to get to the point and move efficiently from the brainstorming phase to the execution phase.”

 For Maria his account read: “Maria is friendly and has helped us through the project – she can however be a little too assertive in meetings in her attempt to move things along.”

The difference in tone behind those chunks of feedback and contrasting connotations in the contextual uses of the word ‘assertive’ illustrate some of the biases women face in positions of power (4). In Iris Bohnet’s book What Works: Gender Equality by Design she talks about an experiment conducted in Harvard Business school: students were split into two groups; each was given the profile of a hypothetical venture capitalist and asked whether they would want to work with them: both candidates had exactly the same professional background and qualifications, the only difference was that one was a man called Howard, the other a woman called Heidi. The students in both groups recognised their candidates to be qualified, but those who had Howard were far more likely to want to work with him than those who had Heidi. Psychologists explain this as there being a disconnect between our perceptions of women’s roles, and the qualities required for a “typically male role”; in other words, Heidi’s competence in what is mostly seen as a ‘male job’ means she “no longer fits our mental model of the ideal woman.” Bohnet puts it more bluntly: “When performance is observable, successful women are rated as less likeable than men.”(5)

Maria discusses the mixed feedback in her HR meeting and agrees to focus on active listening and give people space to voice their ideas; deep down though, she feels those are things she already does, and she wonders whether some of her colleagues’ comments are rooted in judgements on how they believe she should act as a woman in the workplace, rather than observations on her actual behaviour and competence as a manager.

 A meeting overruns and Maria leaves work a little later than usual, at 6:30. She rushes to pick her children up from afterschool and day care. In the UK, most formal childcare is only available from 8 am to 6 pm, despite 75% of lower- and middle-income families working outside standard hours (6). She drives everyone home and starts making dinner. Rita sets the table. Julio is too young to do chores, but Maria makes a mental note to herself to make sure her children help out equally around the house when Julio is old enough. Studies show that girls do more household chores than their brothers starting from age of 5 (3).

 Maria asks Rita about her day at school and her basketball practice. When Rita first expressed that she wanted to play basketball, Maria did research and found there were limited options for junior girl team sports compared to boy teams. Rita is disappointed because her practice was cancelled; the boys team needed the court for an impromptu pre-match practice, despite already having twice as many practices as the girls.

A survey by the Sports and Clubs Division in Gothenburg, Sweden found that, of the money invested into sports facilities and activities, 37% went to girls, and 63% went to boys; in all, the boys’ clubs in Gothenburg received 15 million kroner more than the girls’ clubs (7). And this is just one example of the overwhelming gap in funding between women’s and men’s sport. Exercising has many benefits for mental health and has been shown to increase bone density, particularly when practiced before puberty (8). Being active can play an important role in reducing osteoporosis (a condition where bones become more fragile and prone to fracturing), which affects women at a rate four times higher than men (9).

 That night, in bed, Maria’s head is whirring with the stressors she’ll face tomorrow: cleaning, cooking, self-consciousness at work, facing her colleagues, finding a new sitter for her Friday evening work party after Annie cancelled, the thought of having to skip the party if she doesn’t find one, wishing Luca wasn’t still on night shift duty. Some of those are normal challenges of a busy life, but the biased environment she lives in makes everything that much more challenging.

We know that eliminating bias is very difficult, perhaps even next to impossible. Our minds are masters at grouping, stereotyping, and oversimplifying. So how do we address bias? Is blocking it out the solution? Major US orchestras in the 1970s put curtains in auditions to make the selection process as unbiased as possible; as a result, the number of women accepted went up by 30% (10).

But is that really a solution? We can’t just shut the curtains and anonymise the whole world to stifle our biases. And we shouldn’t have to. We need to be open to identifying and gradually unlearning our biases for a more fair, inclusive and equal world.  

That's where Ellpha comes in...

. At Ellpha we believe in helping you tackle bias using artificial intelligence. Our new platform Talentuum promotes diversity and inclusion by identifying bias within talent assessments.  Our automated talent cycle questionnaires (we call them ‘Talent Growth Plans’) are designed for more objective and equal review of employees or ‘talents’ with pointed questions and a performance-over-personality focus. Most importantly, Talentuum identifies and points out biases within feedback provided, allowing for managers reviewing their employees to stop, reflect and re-evaluate how their unconscious biases may have interfered with their feedback, thus enabling them to improve over time. We promote inclusive and diverse environments by making recruitment, promotion and review decisions as unbiased as possible (11).

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1. Unconscious Bias | diversity.ucsf.edu. Diversity.ucsf.edu. https://diversity.ucsf.edu/resources/unconscious-bias. Published 2021.

2. Recruitment C. Tackling Conscious and Unconscious Bias - Change Recruitment. Changerecruitmentgroup.com. https://www.changerecruitmentgroup.com/knowledge-centre/tackling-conscious-and-unconscious-bias. Published 2021.

3. Criado-Perez C. Invisible Women: Exposing Data Bias In A World Designed For Men; 2020:p.39,67-90

4. Criado-Perez C. Invisible Women: Exposing Data Bias In A World Designed For Men; 2020:p.91-111

5. Bohnet I. What Works: Gender Equality By Design.; 2016:21-44.

6. Criado-Perez C. Invisible Women: Exposing Data Bias In A World Designed For Men; 2020:p.237-252

7. Smart Economics: Calculating Gender Equality Dividends. Swedish Association of Local Authorities and Regions. https://www.jamstall.nu/wp-content/uploads/2015/01/skl-smart-economics.pdf. Published 2012.

8. Criado-Perez C. Invisible Women: Exposing Data Bias In A World Designed For Men; 2020:p.46-66

9. Alswat K. Gender Disparities in Osteoporosis. J Clin Med Res. 2017;9(5):382-387. doi:10.14740/jocmr2970w

10. Rice C. How blind auditions help orchestras to eliminate gender bias. The Guardian: Women in Leadership. https://www.theguardian.com/women-in-leadership/2013/oct/14/blind-auditions-orchestras-gender-bias. Published 2013.

11. ellpha. (2021) www.ellpha.io


"It is time for parents to teach young people early on that in diversity there is beauty and there is strength."
Maya Angelou, poet and civil rights activist