According to a recent survey, ** 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 ** percent of the female respondents. However, female respondents found to a greater extent than male respondents that workplaces treat men and women equally.

At the dawn of the 2020s, building fairer and more inclusive economies must be the goal of global, national and industry leaders. To get there, instilling gender parity across education, health, politics and across all forms of economic participation will be critical.

Over the past 14 years, the Global Gender Gap Index included in this report has served as a compass to track progress on relative gaps between women and men on health, education, economy, and politics. Through this annual yardstick, stakeholders within each country are able to set priorities relevant in each specific economic, political and cultural context.

This year’s report highlights the growing urgency for action. Without the equal inclusion of half of the world’s talent, we will not be able to deliver on the promise of the Fourth Industrial Revolution for all of society, grow our economies for greater shared prosperity or achieve the UN Sustainable Development Goals. At the present rate of change, it will take nearly a century to achieve parity, a timeline we simply cannot accept in today’s globalized world, especially among younger generations who hold increasingly progressive views of gender equality.

The global gender gap index benchmarks national gender gaps on economic, political, education, and health-based criteria. In 2025, the country offering the most gender equal conditions was Iceland, with a score of 0.93. Overall, the Nordic countries make up 3 of the 5 most gender equal countries worldwide. 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 second-least gender equal country Pakistan 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 have 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 9 million people are estimated to be at acute risk of famine. The Middle East and North Africa have the largest gender gap Looking at the different world regions, the Middle East and North Africa have 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.

Gender Pay Gap legislation introduced in April 2017 requires all employers of 250 or more employees to report annually on their gender pay gap.

The gender pay gap is the difference between the average earnings of men and women, expressed relative to men’s earnings.

You can also:

• https://gender-pay-gap.service.gov.uk/Viewing/search-results" class="govuk-link">explore this data on a dashboard
• https://data.gov.uk/dataset/gender-pay-gap" class="govuk-link">export all national gender pay gap data

The gender wage gap indicator compares the median earnings between male and female workers in Champaign County.

Two worker populations are analyzed: all workers, including part-time and seasonal workers and those that were not employed for the full survey year; and full-time, year-round workers. The gender wage gap is included because it blends economics and equity, and illustrates that a major economic talking point on the national level is just as relevant at the local scale.

For all four populations (male full-time, year-round workers; female full-time, year-round workers; all male workers; and all female workers), the estimated median earnings were higher in 2023 than in 2005. The greatest increase in a population’s estimated median earnings between 2005 and 2023 was for female full-time, year-round workers; the smallest increase between 2005 and 2023 was for all female workers. In both categories (all and full-time, year-round), the estimated median annual earnings for male workers was consistently higher than for female workers.

The gender gap between the two estimates in 2023 was larger for full-time, year-round workers than all workers. For full-time, year-round workers, the difference was $11,863; for all workers, it was approaching $9,700.

The Associated Press wrote this article in October 2024 about how Census Bureau data shows that in 2023 in the United States, the gender wage gap between men and women working full-time widened year-over-year for the first time in 20 years.

Income data was sourced from the U.S. Census Bureau’s American Community Survey (ACS) 1-Year Estimates, which are released annually.

As with any datasets that are estimates rather than exact counts, it is important to take into account the margins of error (listed in the column beside each figure) when drawing conclusions from the data.

Due to the impact of the COVID-19 pandemic, instead of providing the standard 1-year data products, the Census Bureau released experimental estimates from the 1-year data in 2020. This includes a limited number of data tables for the nation, states, and the District of Columbia. The Census Bureau states that the 2020 ACS 1-year experimental tables use an experimental estimation methodology and should not be compared with other ACS data. For these reasons, and because data is not available for Champaign County, no data for 2020 is included in this Indicator.

For interested data users, the 2020 ACS 1-Year Experimental data release includes a dataset on Median Earnings in the Past 12 Months (in 2020 Inflation-Adjusted Dollars) by Sex by Work Experience in the Past 12 Months for the Population 16 Years and Over with Earnings in the Past 12 Months.

Sources: U.S. Census Bureau; American Community Survey, 2023 American Community Survey 1-Year Estimates, Table S2001; generated by CCRPC staff; using data.census.gov; (16 October 2024).; U.S. Census Bureau; American Community Survey, 2022 American Community Survey 1-Year Estimates, Table S2001; generated by CCRPC staff; using data.census.gov; (20 October 2023).; U.S. Census Bureau; American Community Survey, 2021 American Community Survey 1-Year Estimates, Table S2001; generated by CCRPC staff; using data.census.gov; (21 September 2022).; U.S. Census Bureau; American Community Survey, 2019 American Community Survey 1-Year Estimates, Table S2001; generated by CCRPC staff; using data.census.gov; (7 June 2021).; U.S. Census Bureau; American Community Survey, 2018 American Community Survey 1-Year Estimates, Table S2001; generated by CCRPC staff; using data.census.gov; (7 June 2021).; U.S. Census Bureau; American Community Survey, 2017 American Community Survey 1-Year Estimates, Table S2001; generated by CCRPC staff; using American FactFinder; (13 September 2018).; U.S. Census Bureau; American Community Survey, 2016 American Community Survey 1-Year Estimates, Table S2001; generated by CCRPC staff; using American FactFinder; (13 September 2018).; U.S. Census Bureau; American Community Survey, 2015 American Community Survey 1-Year Estimates, Table S2001; generated by CCRPC staff; using American FactFinder; (13 September 2018).; U.S. Census Bureau; American Community Survey, 2014 American Community Survey 1-Year Estimates, Table S2001; generated by CCRPC staff; using American FactFinder; (13 September 2018).; U.S. Census Bureau; American Community Survey, 2013 American Community Survey 1-Year Estimates, Table S2001; generated by CCRPC staff; using American FactFinder; (13 September 2018).; U.S. Census Bureau; American Community Survey, 2012 American Community Survey 1-Year Estimates, Table S2001; generated by CCRPC staff; using American FactFinder; (13 September 2018).; U.S. Census Bureau; American Community Survey, 2011 American Community Survey 1-Year Estimates, Table S2001; generated by CCRPC staff; using American FactFinder; (13 September 2018).; U.S. Census Bureau; American Community Survey, 2010 American Community Survey 1-Year Estimates, Table S2001; generated by CCRPC staff; using American FactFinder; (13 September 2018).; U.S. Census Bureau; American Community Survey, 2009 American Community Survey 1-Year Estimates, Table S2001; generated by CCRPC staff; using American FactFinder; (13 September 2018).; U.S. Census Bureau; American Community Survey, 2008 American Community Survey 1-Year Estimates, Table S2001; generated by CCRPC staff; using American FactFinder; (13 September 2018).; U.S. Census Bureau; American Community Survey, 2007 American Community Survey 1-Year Estimates, Table S2001; generated by CCRPC staff; using American FactFinder; (13 September 2018).; U.S. Census Bureau; American Community Survey, 2006 American Community Survey 1-Year Estimates, Table S2001; generated by CCRPC staff; using American FactFinder; (13 September 2018).; U.S. Census Bureau; American Community Survey, 2005 American Community Survey 1-Year Estimates, Table S2001; generated by CCRPC staff; using American FactFinder; (13 September 2018).

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.

This dataset provides a broad set of indicators on dimensions of gender inequality based on the FROGEE Gender Equality in Eastern Europe survey. Read more here: https://freepolicybriefs.org/2020/01/01/frogee-gender-equality-survey/ Click to follow link." href="https://eur01.safelinks.protection.outlook.com/?url=https%3A%2F%2Ffreepolicybriefs.org%2F2020%2F01%2F01%2Ffrogee-gender-equality-survey%2F&data=05%7C02%7CMaria.Perrotta%40hhs.se%7C7d1b0dfc9b764afe2aaa08dc3d5e6fbf%7Cbb8ce15bd4e14149ad64662d32c03d02%7C0%7C0%7C638452723320440368%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&sdata=zabea8Z3pFdy1X38Pxm49brpb5KxmcvQeh68OVVqxgw%3D&reserved=0">https://freepolicybriefs.org/2020/01/01/frogee-gender-equality-survey/

To request the data please fill in and send the Data Request Form to maria.perrotta@hhs.se.

Suggested citation: FREE Network. (2024). FROGEE Gender Equality in Eastern Europe Survey Data [Data set]. Zenodo. https://doi.org/10.5281/zenodo.10777928 Click to follow link." href="https://eur01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdoi.org%2F10.5281%2Fzenodo.10777928&data=05%7C02%7CMaria.Perrotta%40hhs.se%7C884d556be1604ff039d508dc3db193a6%7Cbb8ce15bd4e14149ad64662d32c03d02%7C0%7C0%7C638453080265282124%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&sdata=kiam9yypggNa0TV5vEmNIl5Z4vb3nzuMhWPzqjQk5%2BE%3D&reserved=0">https://doi.org/10.5281/zenodo.10777928

According to the Global Gender Gap Report 2020, 88 percent of females worldwide had primary education, compared to 91 percent of males. By comparison, more females than males had attained tertiary education. The Global Gender Index benchmarks national gender gaps on economic, political, education, and health-based criteria. In 2020, the leading country was Iceland with a score of 0.87.

Annual gender pay gap estimates for UK employees by age, occupation, industry, full-time and part-time, region and other geographies, and public and private sector. Compiled from the Annual Survey of Hours and Earnings.

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

According to a survey conducted in South Korea in 2020, about **** percent of female respondents felt that South Korean society was unfair to women, while only **** percent of male respondents felt the same. On the contrary, about **** percent of men thought they were treated unfairly.

Gender Pay Gap legislation introduced in April 2017 requires all employers of 250 or more employees to publish their gender pay gap annually. The gender pay gap is the difference between the average earnings of men and women, expressed relative to men’s earnings.

Abstract

Facebook’s 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. This survey covers topics about gender dynamics and norms, unpaid caregiving, and life during the COVID-19 pandemic. Aggregated data is available publicly on Humanitarian Data Exchange (HDX). De-identified microdata is also available to eligible nonprofits and universities through Facebook’s Data for Good (DFG) program. For more information, please email dataforgood@fb.com.

Geographic coverage

This survey is fielded once a year in over 200 countries and 60 languages. The data can help researchers track trends in gender equality and progress on the Sustainable Development Goals.

Analysis unit

• Public Aggregate Data on HDX: country or regional levels
• De-identified Microdata through Facebook Data for Good program: Individual level

Universe

The survey was fielded to active Facebook users.

Kind of data

Sample survey data [ssd]

Sampling procedure

Respondents were sampled across seven regions: - East Asia and Pacific; Europe and Central Asia - Latin America and Caribbean - Middle East and North Africa - North America - Sub-Saharan Africa - South Asia

For the purposes of this report, responses have been aggregated up to the regional level; these regional estimates form the basis of this report and its associated products (Regional Briefs). In order to ensure respondent confidentiality, these estimates are based on responses where a sufficient number of people responded to each question and thus where confidentiality can be assured. This results in a sample of 461,748 respondents.

The sampling frame for this survey is the global database of Facebook users who were active on the platform at least once over the past 28 days, which offers a number of advantages: It allows for the design, implementation, and launch of a survey in a timely manner. Large sample sizes allow for more questions to be asked through random assignment of modules, avoiding respondent fatigue. Samples may be drawn from diverse segments of the online population. Knowledge of the overall sampling frame allowed for more rigorous probabilistic sampling techniques and non-response adjustments than is typical for online and phone surveys

Mode of data collection

Internet [int]

Research instrument

The survey includes a total of 75 questions, split across into the following sections: - Basic demographics and gender norms - Decision making and resource allocation across household members - Unpaid caregiving - Additional household demographics and COVID-19 impact - Optional questions for special groups (e.g. students, business owners, the employed, and the unemployed)

Questions were developed collaboratively by a team of economists and gender experts from the World Bank, UN Women, Equal Measures 2030, and Ladysmith. Some of the questions have been borrowed from other surveys that employ alternative modes of administration (e.g., face-to-face, telephone surveys, etc.); this allows for comparability and identification of potential gaps and biases inherent to Facebook and other online survey platforms. As such, the survey also generates methodological insights that are useful to researchers undertaking alternative modes of data collection during the COVID-19 era.

In order to avoid “survey fatigue,” wherein respondents begin to disengage from the survey content and responses become less reliable, each respondent was only asked to answer a subset of questions. Specifically, each respondent saw a maximum of 30 questions, comprising demographics (asked of all respondents) and a set of additional questions randomly and purposely allocated to them.

Response rate

Response rates to online surveys vary widely depending on a number of factors including survey length, region, strength of the relationship with invitees, incentive mechanisms, invite copy, interest of respondents in the topic and survey design.

Sampling error estimates

Any survey data is prone to several forms of error and biases that need to be considered to understand how closely the results reflect the intended population. In particular, the following components of the total survey error are noteworthy:

Sampling error is a natural characteristic of every survey based on samples and reflects the uncertainty in any survey result that is attributable to the fact that not the whole population is surveyed.

Other factors beyond sampling error that contribute to such potential differences are frame or coverage error and nonresponse error.

Data appraisal

Survey Limitations The survey only captures respondents who: (1) have access to the Internet (2) are Facebook users (3) opt to take this survey through the Facebook platform. Knowledge of the overall demographics of the online population in each region allows for calibration such that estimates are representative at this level. However, this means the results only tell us something about the online population in each region, not the overall population. As such, the survey cannot generate global estimates or meaningful comparisons across countries and regions, given the heterogeneity in internet connectivity across countries. Estimates have only been generated for respondents who gave their gender as male or female. The survey included an “other” option but very few respondents selected it, making it impossible to generate meaningful estimates for non-binary populations. It is important to note that the survey was not designed to paint a comprehensive picture of household dynamics but rather to shed light on respondents’ reported experiences and roles within households

The data originates from Promusicae’s official website, which provides weekly and yearly charts for albums, singles, and additional music-related content categories. The paper associated to this sample is available here:

Sánchez-Olmos, C. (2025). Gender Inequality in Spain’s Official Music Charts: Neither Representation nor Success for Female Artists (2008–2020). Journalism and Media, 6(1), 10. https://doi.org/10.3390/journalmedia6010010

This dataset features the top 50 from 2008 to 2020, comprising 1300 recording units with an equal split between albums (650) and singles (650) (Figure 1). Promusicae represents Spanish record labels affiliated with the International Federation of the Phonographic Industry (IFPI) and is responsible for publishing these official charts. The analysis period started in 2008 when Promusicae published its first top 50 singles chart, which was later expanded to a top 100 format in 2015. Since Promusicae has published the singles chart since 2008, this year marks the beginning of the analysis period, ending in 2020.

Both charts were downloaded in Excel format from the Promusicae website. All albums and singles are coded to feature the following variables: artist, title, year of chart appearance, gender (soloist or band), position on the chart, and success achieved. The gender of the featured position is also coded in the single chart.

This code has its limitations. First, the use of binary gender coding fails to capture the diversity of sexual identities (de Boise, 2019). Furthermore, several methods for categorising mixed bands were identified based on the roles of men and women (including composers, singers, or instrumentalists). However, to facilitate discussion, we chose the categories proposed by Lafrance et al. (2011). Consequently, the final coding includes five distinct categories: male artists, male bands (entirely composed of men), female artists, female bands (consisting solely of women), and male–female groups (mixed duos, trios, or bands featuring both women and men).

Gender Pay Gap legislation introduced in April 2017 requires all employers of 250 or more employees to publish their gender pay gap data annually. The gender pay gap is the difference between the average earnings of men and women, expressed relative to men’s earnings.

https://gender-pay-gap.service.gov.uk/" class="govuk-link">The Gender Pay Gap Service allows you to browse and compare data from different organisations.

Narrative ID: NW17Narrative Title: Income and unpaid work in Latin America: intersection of gender and race inequalities [ECLAC]Theme: Economic empowermentSDG indicators: Beijing objectives: Related-narratives: Labels: App ID: [ITEM_ID]

Gender pay gap legislation introduced in April 2017 requires all employers of 250 or more employees to report annually on their gender pay gap.

The gender pay gap is the difference between the average earnings of men and women, expressed relative to men’s earnings.

This dataset contains the results of a three month audit of housing advertisements. It accompanies the 2020 ICWSM paper "Auditing Race and Gender Discrimination in Online Housing Markets". It covers data collected between Dec 7, 2018 and March 19, 2019. There are two json files in the dataset: The first contains a list of json objects representing advertisements separated by newlines. Each object includes the date and time it was collected, the image and title (if collected) of the ad, the page on which it was displayed, and the training treatment it received. The second file is a list of json objects representing a visit to a housing lister separated by newlines. Each object contains the url, training treatment applied, the location searched, and the metadata of the top sites scraped. This metadata includes location, price, and number of rooms. The dataset also includes the raw images of ads collected in order to code them by interest and targeting. These were captured by selenium and named using a perceptive hash to de-duplicate images.

The main SPSS dataset of over 700 variables covers 11 sections on 12 developed capitalist electoral democracies. (see Outline file included here for an overview of both sections and countries included, with the names in order of every variable and label.) The second SPSS file is of 29 variables of Covid-related daily data from OWID website that covers the same 12 countries from the start of Covid-19 in January 2020 to Aug 2, 2023.