According to a recent survey, 55 percent of the male respondents believed that their respective countries have gone far enough in terms of giving women equal rights with men. This statement was only supported by 42 percent of the female respondents. However, female respondents found to a greater extent than male respondents that workplaces treat men and women equally.

The research aim was to explore how to promote gender equality using Information and Communication Technologies (ICTs). The researcher conducted semi-structured interviews with a total of 19 respondents, both men and women. The researcher used the information that was collected from interviews and document analysis to evaluate the facts and findings of the study. The researcher used SPSS Version 21 to analyse the data in Section A for the respondents’ biographical data and perceived use of ICTs. The researcher then used NVIVO to transcribe and code data and then used Microsoft Excel to present the data set from which themes were generated to analyse data in Section B and C in order to answer the research questions.

The difference between the earnings of women and men shrank slightly over the past years. Considering the controlled gender pay gap, which measures the median salary for men and women with the same job and qualifications, women earned one U.S. cent less. By comparison, the uncontrolled gender pay gap measures the median salary for all men and all women across all sectors and industries and regardless of location and qualification. In 2025, the uncontrolled gender pay gap in the world stood at 0.83, meaning that women earned 0.83 dollars for every dollar earned by men.

The global gender gap index benchmarks national gender gaps on economic, political, education, and health-based criteria. In 2024, the country offering most gender equal conditions was Iceland with a score of 0.94. Overall, the Nordic countries make up four of the five most gender equal countries in the world. The Nordic countries are known for their high levels of gender equality, including high female employment rates and evenly divided parental leave. Sudan is the least gender equal country Sudan is found on the other end of the scale, ranked as the least gender equal country in the world. Conditions for civilians in the North African country has worsened significantly after a civil war broke out in April 2023. Especially girls and women are suffering and have become victims of sexual violence. Moreover, nearly nine million people are estimated to be at acute risk of famine. The Middle East and North Africa has the largest gender gap Looking at the different world regions, the Middle East and North Africa has the largest gender gap as of 2023, just ahead of South Asia. Moreover, it is estimated that it will take another 152 years before the gender gap in the Middle East and North Africa is closed. On the other hand, Europe has the lowest gender gap in the world.

The Gender Equality Index is a tool to measure the progress of gender equality in the EU, developed by EIGE. It gives more visibility to areas that need improvement and ultimately supports policy makers to design more effective gender equality measures.

The Gender Equality Index has tracked the painfully slow progress of gender equality in the EU since 2010, mostly due to advances in decision-making. While equality is more pronounced in some Member States than in others, it is far from a reality for everyone in every area. Gender norms around care, gender segregation in education and the labour market, and gender inequalities in pay remain pertinent.

The Index allows Member States to easily monitor and compare gender equality progress across various groups of women and men in the EU over time and to understand where improvements are most needed. The 2022 Index has a thematic focus on care in the Covid-19 pandemic. It explores the division of informal childcare, long-term care and housework between women and men.

The Gender Equality Index is a composite indicator. With a total of six core domains (work, money, knowledge, time, power and health) and two satellite domains (violence against women and intersecting inequalities), it offers a synthetic and easy-to-interpret measure for gender equality, indicating how far (or close) the EU and its Member States are from achieving gender equality on a scale of 1 to 100.

Building on previous editions alongside EIGE’s approach to ensuring intersecting inequalities are captured, the Gender Equality Index 2022 continues to show the diverse realities that different groups of women and men face. It examines how elements such as disability, age, level of education, country of birth and family type can intersect with gender and create many different kinds of pathways in people's lives.

According to an annual survey conducted in China in the beginning of 2025, around 66 percent of surveyed female professionals said that gender inequality at work persists because of the ongoing childbirth burden for women. Only 23 percent of male respondents agreed with that opinion. However, an equal proportion of men and women thought that gender discrimination at work is caused by educational reasons.

Achieve gender equality and empower all women and girls : The region has made progress in achieving gender equality and empowering women and girls, particularly in education and health and to a lesser extent women’s participation in formal employment and national policy making. This is attributed to growing awareness of the need to address gender inequalities; While almost all countries in the Pacific have adopted specific gender policies and strategies, the resources for integrating and implementing these priorities are limited. Budgets for national women’s offices are less than one percent of national appropriations; Gender inequality is highlighted by the high prevalence rates of violence against women (more than 60 percent in Melanesia, and more than 40 percent in Polynesia and Micronesia). Sexual and reproductive health and rights issues also remain substantial challenges to be addressed under Goal 5. Fertility rates, especially teenage fertility, remain high in some.

Find more Pacific data on PDH.stat.

This data contains aggregated weighted statistics at the regional level by gender for the 2020 Survey on Gender Equality At Home as well as the country and regional level for the 2021 wave. The Survey on Gender Equality at Home generates a global snapshot of women and men’s access to resources, their time spent on unpaid care work, and their attitudes about equality. Researchers and nonprofits interested in access to survey microdata can apply at https://dataforgood.facebook.com/dfg/tools/survey-on-gender-equality-at-home.

Under the Workplace Gender Equality Act 2012, non-public sector employers with 100 or more staff must report to the WGEA annually, which covers over 12,000 Australian organisations. Information collected and contained in the data files are the gender composition of the workforce and governing bodies/boards, percentage of organisations with policy and/or strategies across a broad range of gender equality issues, paid parental leave and flexible work arrangement offerings.

Visit Data Explorer (https://data.wgea.gov.au/) for key trends and data visualisations

Visit Metadata registry (https://wgea.aristotlecloud.io/about/wgea/gender_equality_indicators) for further information about how we use the data to measure gender equality.

The Data Quality Declaration (https://www.wgea.gov.au/data/data-quality-declaration) addresses the overall quality of the Agency data in terms of relevance, timeliness, accuracy, coherence, interpretability, accessibility, and the institutional environment.

India's performance on UNDP's Gender Inequality Index - score, rank, expert analysis and comparison with global peers.

Gender statistics on the numbers of women and men in key decision-making positions across a number of different life domains. The domains covered include: politics; public administration; judiciary; business and finance; social partners and NGOs; environment and climate change; and media.

Data on decision-making are collected for 35 European countries - the 28 EU Member States, 4 candidate countries (Montenegro, the former Yugoslav Republic of Macedonia, Serbia and Turkey) and the remaining EEA countries (Iceland, Liechtenstein and Norway).

Figures are available at international, European, national, regional and local level. Most data are updated annually, but some key data are updated more frequently. In particular, data on national and European politics are updated quarterly, and data on large companies biannually, in order to ensure that the information is always right up to date.

Introduction

This study reproduces the results of the article Relationship of gender differences in preferences to economic development and gender equality (DOI: 10.1126/science.aas9899) and partially its supplementary material.

The code for the analysis can be found at the following GitHub page: https://github.com/scerioli/Global-Preferences-Survey

Preparation of the data

Data Collection, Cleaning, and Standardization

The data used in the Falk & Hermle 2018 is not fully available because of two reasons:

1. Data paywall: Some part of the data is not available for free. It requires to pay a fee to the Gallup to access them. This is the case for the additional data set that is used in the article, for instance, the one that contains the education level and the household income quintile. Check the website of the briq - Institute on Behavior & Inequality for more information on it.

2. Data used in study is not available online: This is what happened for the LogGDP p/c calculated in 2005 US dollars (which is not directly available online). We decided to calculate the LogGDP p/c in 2010 US dollars because it was easily available, which should not change the main findings of the article.

Global Preferences Survey

This data is protected by copyright and cannot be given to third parties.

To download the GPS data set, go to the website of the Global Preferences Survey in the section "downloads". There, choose the "Dataset" form and after filling it, we can download the data set.

Hint: The organisation can be also "private".

The following two relevant papers have to be also cited in all publications that make use of or refer in any kind to GPS dataset:

• Falk, A., Becker, A., Dohmen, T., Enke, B., Huffman, D., & Sunde, U. (2018). Global evidence on economic preferences. Quarterly Journal of Economics, 133 (4), 1645–1692.

• Falk, A., Becker, A., Dohmen, T. J., Huffman, D., & Sunde, U. (2016). The preference survey module: A validated instrument for measuring risk, time, and social preferences. IZA Discussion Paper No. 9674.

GDP per capita

From the website of the World Bank, one can access the data about the GDP per capita on a certain set of years. We took the GDP per capita (constant 2010 US$), made an average of the data from 2003 until 2012 for all the available countries, and matched the names of the countries with the ones from the GPS data set.

Gender Equality Index

The Gender Equality Index is composed of four main data sets.

• Time since women’s suffrage: Taken from the Inter-Parliamentary Union Website. We prepared the data in the following way. For several countries more than one date where provided (for example, the right to be elected and the right to vote). We use the last date when both vote and stand for election right were granted, with no other restrictions commented. Some counties were a colony or within union of the countries (for instance, Kazakhstan in Soviet Union). For these countries, the rights to vote and be elected might be technically granted two times within union and as independent state. In this case we kept the first date. It was difficult to decide on South Africa because its history shows the racism part very entangled with women's rights. We kept the latest date when also Black women could vote. For Nigeria, considered the distinctions between North and South, we decided to keep only the North data because, again, it was showing the completeness of the country and it was the last date. Note: USA data doesn't take into account that also up to 1964 black women couldn't vote (in general, Blacks couldn't vote up to that year). We didn’t keep this date, because it was not explicitly mentioned in the original data set. This is in contrast with other choices made, but it is important to reproduce exactly the results of the publication, and the USA is often easy to spot on the plots.

• UN Gender Inequality Index: Taken from the Human Development Report 2015. We kept only the table called "Gender Inequality Index".

• WEF Global Gender Gap: WEF Global Gender Gap Index Taken from the World Economic Forum Global Gender Gap Report 2015. For countries where data were missing, data was added from the World Economic Forum Global Gender Gap Report 2006. We modified some of the country names directly in the csv file, that is why we provide it as an input file.

• Ratio of female and male labour force participation: Average International Labour Organization estimates from 2003 to 2012 taken from the World Bank database (http://data.worldbank.org/indicator/SL.TLF.CACT.FM.ZS). Values were inverted to create an index of equality. We took the average for the period between 2004 and 2013.

In our extended analysis, we also involved the following index:

• United Nations Development Programme Gender Development Index taken from Human Development Reports 2020. Note that we have downloaded the two tables of the Human Development Index for males and females, and used the ratio of the two as a GDI index, as described in the report.

This record for the Dataset 2 (Survey) from the Work Package 2 (Effects of, and Resistances to 'Anti-Gender' Mobilisations Across Europe) of the RESIST Project has been created in the Zenodo open repository, in line with the RESIST Project’s Data Management Plan, and according to the framework of the Open Science principles of the European Union. We followed the accepted gold-standard rule: “as open as possible – as closed as necessarily” to ensure research ethics, integrity, and compliance with the research policies of the EU and the consortium members.

Data gathered during the Work Package 2 (Effects of, and Resistances to 'Anti-Gender' Mobilisations Across Europe) have been classified as SENSITIVE and therefore the dataset will not be available in open access repositories for ten years after the end of the project (that is until 01/10/2036). After 01/10/2036, if certain conditions outlined by the project consortium are met, the dataset will be released publicly on Zenodo.

The report presents the results of a survey carried out in the 28 Member States of the European Union in December 2014. Some 27.801 respondents from different social and demographic groups were interviewed face-to-face at home in their mother tongue. Results have been compared with the 2009 survey where possible. Where appropriate, a variety of socio-demographic variables – such as respondents’ gender, age, terminal education age, occupation and ability to pay household bills – have been used to provide further analysis. Other key variables that have been used to provide additional insight include respondents’ views: about how widespread gender inequalities are in their country; on whether they think equality between men and women is a fundamental right; on whether tackling gender inequality should be an EU priority.

The results by volumes are distributed as follows:

• Volume A: Countries
• Volume AA: Groups of countries
• Volume A' (AP): Trends
• Volume AA' (AAP): Trends of groups of countries
• Volume B: EU/socio-demographics
• Volume B' (BP) : Trends of EU/ socio-demographics
• Volume C: Country/socio-demographics ---- Researchers may also contact GESIS - Leibniz Institute for the Social Sciences: https://www.gesis.org/eurobarometer

This fascinating compilation of the recent data on gender differences in education presents a wealth of data, analysed from a multitude of angles in a clear and lively way. In particular it looks at underperformance among boys, lack of self confidence among girls and family, school and societal influences before addressing policies to help boys and girls reach their full potential.

The Gender Statistics Database provides a broad overview of statistics on gender as well as information on the various aspects of (in)equality between women and men. These include indicators referred to the EU Strategy for Equality between Women and Men (2010-2015) and the Beijing Declaration and Platform for Action on Equality.

Moreover, it is possible to access the Gender Equality Index Scores on the same platform. The Index is a composite indicator that measures how far (or close) the EU and its Member States were from achieving complete gender equality in the reference year.

According to a survey about Chinese career women conducted in 2025, about 36.9 percent of female respondents said they had experienced gender discrimination at work, whereas only 11.3 percent of male respondents had similar experience. Similarly, more women than men felt that age was affecting their career prospects.

Do women elected officials contribute to the creation of public sector workforces that are more representative of the populations they serve? A more representative bureaucracy is expected to produce better outcomes, and thus understanding the role that elected leadership plays in diversifying the bureaucracy is important. Using data from over 5000 Brazilian municipalities from 2001 to 2012, we examine whether the election of women mayors leads to the formation of municipal executive bureaucracies that are more representative in terms of gender. In addition, we test whether the presence of a woman mayor leads to increased wages for women bureaucrats and smaller wage gaps between men and women bureaucrats. We find that while women mayors do not increase women’s numerical representation in the municipal executive bureaucracy, they do contribute to the creation of bureaucracies with fewer gender inequalities. Electing a woman mayor increases the average wages of women bureaucrats and decreases the gender wage gap in the bureaucracy. These findings suggest that women mayors advocate for the promotion of women to leadership positions and reduce the gap between men’s and women’s ranks in the bureaucracy since the salaries of Brazilian civil servants are linked to their positions.

The Gender Gap Index quantifies the gaps between women and men in four key areas: health, education, economy, and politics. Data is available from 149 countries for select years between 2010-2021. Scores are based on the level of access women have to resources and opportunities relative to men.

Since 2018, UK firms with at least 250 employees have been mandated to publicly disclose gender equality indicators. Exploiting variations in this mandate across firm size and time, we show that pay transparency closes 19 percent of the gender pay gap by reducing men’s wage growth. By combining different sources of data, we also provide suggestive evidence that the public availability of the equality indicators influences employers’ response as worse performing firms and employers potentially more exposed to public scrutiny seem to reduce their gender pay gap the most.