This images shows a graph that is horizontal, with three men and a woman walking on the bar lines. The three men are ahead and the women is a long way behind, with a noose around her feet.

Gendered Roles: some statistics to set the scene

Below are some examples that demonstrate the gendering of roles. Firstly, we explore the extent of labour force participation, which sets the scene in terms of the proportions of men and women in the workplace, from which we might infer a work-home divide with women taking on more household roles (although unemployment will also be a factor). We also look at the gender split between full-time and part-time work. We then look at occupational differences, specifically the gendering of science-based roles as being more masculine (and thus likely to be disproportionately occupied by men), and caring roles more feminine (and thus likely to be disproportionately occupied by women). Consider how the representation of women and men in particular roles might influence people’s perception of them and how accessible certain occupations may feel to a member of the minority sex in that occupation.

Work and Home

Women still undertake the majority of care work (including household chores), but this is now often undertaken alongside paid-work, as labour force participation rates for women have increased to levels much closer to men. However, this is not a consistent picture worldwide, as the following map [1] demonstrates.

A map of the world with countries coloured differently dependent upon their ratio of female to male in the labor force. The female-to-male ratio of labor force participation rates in calculated by dividing the labor force participation rate among women, by the corresponding rate for men. The labor force participation rate is defined as the proportion of the population ages 15+ that is economically active. All figures correspond to 'modeled ILO estimates' (see World Bank source for details). The map shows the numbers for most countries are well below 100%, which means that the participation of women tends to be lower than that of men. Yet differences are outstanding: in countries such as Syria or Algeria, the ratio is below 25%. In contrast, in Laos, Mozambique, Rwanda, Malawi and Togo, the relationship is close to, or even slightly above 100% Click to enlarge image Source: World Bank.

Overall the map demonstrates that men are usually more frequently employed than women. In many countries (both high and low income) the participation rates are comparatively close, but in others there is a significant gap. The labour force participation rates have changed over time, as the following two graphs demonstrate [1].

A graph with 7 lines drawn left to right, and fluctuating based upon the ratio of female to male in the labor force in Sweden, Ethiopia, Spain, China, Brazil, India and Egypt from 1990 to 2017. The female-to-male ratio of labor force participation rates is calculated by dividing the labor force participation rate ampng women by the corresponding rate for men. The labor force participation rate is defined as the proportion of the population ages 15+ that is economically active. Al figures correspond to 'modeled ILO estimates' (see source for details) The graph shows that Sweden has been the highest, with rates over 80% sine 1990, while Egypt has remained lowest, around 30% for that time. Brazil, Spain and Ethiopia have all increased, while China has dropped from 2nd highest, at around 90% to 4th highest at just below 80%. enlarge

This data reflects some of the worldwide trends that demonstrate labour force participation is growing, declining or broadly static depending on the country, and that the rates of labour force participation range considerably from the low to comparatively high. However, in the main participation rates have improved, as demonstrated below [1].

A scatter graph showing female labor force participation comparing 1980 on the vertical axis with 2016 on the horizontal axis. Th female labor force participation rate corresponds to the proportion of the female population ages 15 and older that is economically active. All figures correspond to national estimates, without ILO corrections (see limitations and exceptions in the sources) The scatter graph identifies continents by colour. In terms of changes across time, the female labor force participation rate today is higher than three decades ago. This is true in the majority of countries, across all income levels. An important point to note is that the chart above includes all women above 15 years of age. This means that the trends conflate changes across different population sub-groups (e.g. young women, married women, older women above retirement age, etc.). Indeed, group-specific trends do not always follow the overall trends. Specifically, trends in labor force participation among younger women are often different to the aggregate trends, notably in rich countries where participation expanded mostly among the older, often married female population. enlarge

Unpaid work

Part of the reason for the lower representation of women in the workforce is that they are disproportionately likely to take on roles that are not measured as economic activities, such as unpaid care work and managing the home. The following graph shows how some countries compare when considering the gender ratio of unpaid work.

A horizontal bar chart showing the ratio of unpaid care work in 21 countries between females and males. The bars show the female-to-male ratio of time devoted to unpaid services provided within the household, including care of persons, housework and voluntary community work. All over the world, women spend more time than men on these activities. Yet there are clear differences when it comes to the magnitude of these gender gaps. At the low end of the spectrum, in Uganda women work 18% more than men in unpaid care activities at home. While at the opposite end of the spectrum, in countries such as India, women work 10 times more than men on these activities. enlarge

The Office for National Statistics in the UK have calculated that when it comes to unpaid domestic chores at home, women do 60% more than men [2]. But the type of activity also matters, with men more likely to take on transportation, such as driving children to activities, but a lot less likely to do the cooking, childcare and housework. This suggests that even within the home, there is a gendering of the types of unpaid work undertaken.

Part-time and full-time work

Women are disproportionately likely to work part-time compared to men. This offers them flexibility to take on caring roles, which they are more likely to undertake than men, but it is also associated with lower rates of pay and less preferential working conditions. The graph below sets out some of the international differences between rates of part-time work between men and women.

A graph showing the part time employment rates of man and women in 50 countries, all showing women having higher rates of part time work. France, Germany, United Kingdom, Japan and Canada are highlighted in different colours. Bulgaria has the lowest part time rates for both men and women, below 5%, while the Netherlands is highest for both genders, men at around 19% and women almost 60% enlarge

Source: Labour Market Statistics: Full-time part-time employment; OECD (2019), Part-time employment rate (indicator). doi: 10.1787/f2ad596c-en

Participation rates in the workforce will be affected by factors such as: the time taken to complete domestic household chores and accessibility of labour-saving domestic devices, flexibility in working hours, contributions made by men in completing chores, maternal health and fertility rates, policies and provision supporting childcare, formal restrictions in place on women working, and cultural attitudes [3] .

Occupations

We can also see occupational segregation, whereby men and women are more likely to be employed in particular occupations. This can have knock on effects where there are benefits and opportunities attached to particular occupations.

Women in science?

Men are far more likely to be employed in science-based subjects than women. According to UNESCO, women scientists comprise less that 30% of the scientists globally. In the US (2011) [4] women comprised 26% of computer and mathematical-based occupations. In the UK (2017) [5] women comprised 23% of science, engineering, technology and mathematics-based occupations (excluding health). Eurostat suggests a more positive picture for women in science in Europe. Overall, however, men are disproportionately represented in science-based fields.

Women in caring roles?

Women are far more likely to be based in caring roles. Some national-level statistics are given below.

Where? Proportion of women in role
Australia, 2018 [6] 88% of nurses are women
China, 2016 [7] 98% of nurses are women
UK, 2018 [8] 89% of nurses and health visitors are women
US, 2011 [9] 92% of registered nurses are women

In some countries women are not always allowed to undertake the same roles as men, or some restrictions apply, as the map below demonstrates [10]:

A map of the world with countries coloured red or green dependent upon whether non-pregnant and non-nursing women are allowed to do the same jobs as men, red for no and green for yes. The graph shows that the USA, Australia, some of Southern Africa and much of Europe, with the notable exception of France, allows non-pregnant and non-nursing women to do the same jobs as men. enlarge

As the following two charts demonstrate, women are more likely than men to be employed in services, and men are more likely than women to be employed in industry [11].

Graph comparing the number of males employed in services in 2017, on the vertical axis, compared to the number of women, on the horizontal axis. The services sector consists of retail trade, restaurants and hotels; transport, storage, and communications; financing, insurance, real estate, and business services; and community, social, and personal services. Countries tend to be clustered around around a diagonal midpoint, however most countries are on the lower side of this line, indicating that more women than men are employed in services. Qatar is notable for having around 35% male employment in services compared to almost 90% female. Somalia is shown as having no women employed in services, and less than 10% of men. enlarge

Graph comparing the number of males employed in industry, on the vertical axis, compared to the number of women, on the horizontal axis. The industry sector consists of mining, manufacturing, construction, and public utilities. The majority of countries have a higher percentage of men than women employed in industry. enlarge

These figures reflect the tendency for occupational segregation, as men and women are more likely to be found in particular types of work or industry. The gendering of types of work, particularly where roles are almost exclusively male or female, can be linked with the value placed on types of work – a theme we will return to when we look at the gender pay gap.

Read more:

Unpaid work (UK):

The Office for National Statistics published an article claiming Women shoulder the responsibility of ‘unpaid work’.

The House of Commons Briefing Paper entitled Women and the Economy looks at women’s participation in the UK labour market and in business

Women in Science (Global):

This UNESCO paper, Women in Science, presents data on the gender gap in science.

The Executive Summary of Science, Technology and Gender: An International Report, from UNESCO, presents data relating to gender disparity in science and technology.

Elsevier’s Gender in the Global Research Landscape presents an anlysis of research performance through a gender lens across 20 years, 12 geographies, and 27 subject areas.

Women in work

Our World in Data has published an overview of data related to the Female Labor Supply

References

  1. World Development Indicators (WDI) Data Catalog [Internet]. Datacatalog.worldbank.org. 2019 [cited 28 June 2019]. Available from: https://datacatalog.worldbank.org/dataset/world-development-indicators

  2. Women shoulder the responsibility of ‘unpaid work’ - Office for National Statistics [Internet]. Ons.gov.uk. 2019 [cited 28 June 2019]. Available from: https://www.ons.gov.uk/employmentandlabourmarket/peopleinwork/earningsandworkinghours/articles/womenshouldertheresponsibilityofunpaidwork/2016-11-10

  3. Ortiz-Ospina E, Tzvetkova S, Roser M. Female Labor Supply [Internet]. Our World in Data. 2019 [cited 28 June 2019]. Available from: https://ourworldindata.org/female-labor-supply

  4. Dept of Labor, Women’s Bureau, Data and Stats - Employment and Earnings by Occupation [Internet]. Dol.gov. 2019 [cited 28 June 2019]. Available from: https://www.dol.gov/wb/occupations_interactive.htm

  5. Women in STEM workforce 2017 - Welcome to the WISE Campaign [Internet]. Welcome to the WISE Campaign. 2019 [cited 28 June 2019]. Available from: https://www.wisecampaign.org.uk/statistics/women-in-stem-workforce-2017/

  6. Nursing and Midwifery Board of Australia - Statistics [Internet]. Nursingmidwiferyboard.gov.au. 2019 [cited 28 June 2019]. Available from: https://www.nursingmidwiferyboard.gov.au/about/statistics.aspx

  7. Yang J, Hao D. Dilemmas for nurses in China. The Lancet. 2018;392(10141):30. Available from https://doi.org/10.1016/S0140-6736(18)31185-1

  8. Narrowing of NHS gender divide but men still the majority in senior roles - NHS Digital [Internet]. NHS Digital. 2019 [cited 28 June 2019]. Available from: https://digital.nhs.uk/news-and-events/latest-news/narrowing-of-nhs-gender-divide-but-men-still-the-majority-in-senior-roles

  9. Are non-pregnant and non-nursing women allowed to do the same jobs as men? [Internet]. Our World in Data. 2019 [cited 28 June 2019]. Available from: https://ourworldindata.org/grapher/are-non-pregnant-and-non-nursing-women-allowed-to-do-the-same-jobs-as-men

  10. Ortiz-Ospina E, Tzvetkova S, Roser M. Female Labor Supply [Internet]. Our World in Data. 2019 [cited 28 June 2019]. Available from: https://ourworldindata.org/female-labor-supply

Share this article:

This article is from the free online course:

Understanding Gender Inequality

University of Exeter