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.

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 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.

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 the Gender Inequality Index (GII), Denmark and Norway were the most gender equal countries in the world in 2023, reporting an index of ***** and *****, respectively. The Gender Inequality Index measures inequality between women and men in three dimensions: reproductive health, empowerment, and the labor market. A low GII value indicates low inequality between women and men and vice versa. Yemen was considered the least gender equal country that same year. Gender inequality in the workplace The most prominent source of gender inequality is the workplace, often captured by the gender pay gap. In 2023, women still earned one percent less than their male counterparts with the same qualification and the same job. Women are less represented in senior roles and top management positions, with only one third percent of companies worldwide having a woman in leadership positions. The same situation can be observed in government roles - only 17 out of 195 countries worldwide have ever had a woman in the highest position of executive power. Future outlook Numbers on how long it will take to close gender gaps highly differ between regions. In Europe, it is estimated that it will take around 67 years to achieve equality between the genders. In East Asia and the Pacific, on the other hand, it is projected to take 189 years. New data shows that the COVID-19 pandemic has increased female poverty worldwide and widened the gender poverty gap even further. Heightened female poverty will also negatively impact the Gender Inequality Index (GII).

The OECD Gender Data Portal, www.oecd.org/gender/data, includes 40+ selected indicators shedding light on gender inequalities in education, employment and entrepreneurship. Data and metadata for all the indicators are easily and freely accessible and displayed through interactive visualizations. The Gender Data Portal is one of the main outputs of the OECD Gender Initiative, launched in 2010 to improve policies and promote gender equality in the economy in both OECD and non-OECD countries. The Portal is part of the new OECD Gender Equality website www.oecd.org/gender, which also features Closing the Gender Gap: Act Now, a publication that presents new analysis of the productivity losses caused by gender inequality and proposes policy solutions to close the gender gaps. While much progress has been accomplished in recent years, there are still relevant dimensions of gender inequalities that are poorly monitored and measured. The OECD Gender Portal is thus a work in progress, that aims at progressively filling these gaps through new indicators. The last data release, for Women's Day 2013, includes new gender-sensitive indicators of job quality, timely indicators of labor market participation, indicators on top and low-achieving students in different subjects and on entrepreneurial culture. The data cover OECD member countries, as well as Russia, Brazil, China, India, Indonesia, and South Africa.

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Van Meter. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Van Meter, the median income for all workers aged 15 years and older, regardless of work hours, was $71,458 for males and $48,500 for females.

These income figures highlight a substantial gender-based income gap in Van Meter. Women, regardless of work hours, earn 68 cents for each dollar earned by men. This significant gender pay gap, approximately 32%, underscores concerning gender-based income inequality in the city of Van Meter.

- Full-time workers, aged 15 years and older: In Van Meter, among full-time, year-round workers aged 15 years and older, males earned a median income of $85,238, while females earned $56,750, leading to a 33% gender pay gap among full-time workers. This illustrates that women earn 67 cents for each dollar earned by men in full-time roles. This level of income gap emphasizes the urgency to address and rectify this ongoing disparity, where women, despite working full-time, face a more significant wage discrepancy compared to men in the same employment roles.

Remarkably, across all roles, including non-full-time employment, women displayed a similar gender pay gap percentage. This indicates a consistent gender pay gap scenario across various employment types in Van Meter, showcasing a consistent income pattern irrespective of employment status.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Van Meter median household income by race. You can refer the same here

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

The Measures for Advancing Gender Equality (MAGNET) initiative aims to broaden and deepen the measurement of women’s agency, based on the development of new tools and rigorous testing and comparison of both new and existing methods for measuring agency, and promoting the adoption of these measures at scale. By increasing the availability of innovative meaningful measures of agency for a broad range of contexts, we hope our work will lead to an improved understanding of what women’s agency is, how it manifests and how it can best be measured across contexts given the research question at hand. The policy goal of empowering women may be hindered by women’s lack of perception of the degree of gender inequality, their actual desire for egalitarianism, and what they do to push for change. Critical consciousness is defined as the capacity of oppressed or marginalized people to critically analyze their social and political conditions, endorsement of societal equality, and action to change perceived inequities (Freire, 1973). This tool, Gender Inequality: Critical Consciousness Scale, fills a gap of measuring critical consciousness on gender inequality adapted to the Global South. The scale has three components: critical reflection (degree to which women are aware of the conditions that discriminate them), critical action (what they do to push for change), and critical motivation (desire for egalitarianism). This tool is suited for surveys run by NSOs, other nationally representative individual- or household-level surveys, and for targeted thematic or impact evaluation surveys. We recommend the use of this tool in the design, monitoring, and evaluation of development programs aimed at improving women’s empowerment. This data study includes following files. 1. A survey document (including implementation guidelines). 2.Two files, CAPI_Choices and CAPI_Survey, along with the accompanying files, can be used to construct a CAPI program ready for survey implementation. Alternatively, users can use an Excel workbook "CAPI_.xlsx" that includes worksheets for survey and choices, along with others, for constructing a CAPI program ready for survey implementation.

This record for the Dataset 1 (Interviews & Focus Groups) 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.

Over the past decades, more and more women have entered the labor market around the world. Today, over 40 percent of the global workforce are women. However, only one third are in senior roles, and less than 30 percent work within science, technology, engineering, and mathematics (STEM). The Global Gender Index benchmarks national gender gaps on economic, political, education, and health-based criteria. In 2025, the leading country was Iceland .

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.

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in United States. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In United States, the median income for all workers aged 15 years and older, regardless of work hours, was $48,138 for males and $32,546 for females.

These income figures highlight a substantial gender-based income gap in United States. Women, regardless of work hours, earn 68 cents for each dollar earned by men. This significant gender pay gap, approximately 32%, underscores concerning gender-based income inequality in the country of United States.

- Full-time workers, aged 15 years and older: In United States, among full-time, year-round workers aged 15 years and older, males earned a median income of $67,966, while females earned $54,999, leading to a 19% gender pay gap among full-time workers. This illustrates that women earn 81 cents for each dollar earned by men in full-time roles. This analysis indicates a widening gender pay gap, showing a substantial income disparity where women, despite working full-time, face a more significant wage discrepancy compared to men in the same roles.

Surprisingly, the gender pay gap percentage was higher across all roles, including non-full-time employment, for women compared to men. This suggests that full-time employment offers a more equitable income scenario for women compared to other employment patterns in United States.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for United States median household income by race. You can refer the same here

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.

Recent empirical evidence emphasizes the higher prevalence of overweight and obesity for women, especially in developing countries. However, the potential link between gender inequality and obesity has rarely been investigated. Using longitudinal data from India (IHDS 2005-11), we implement Hausman-Taylor and fixed-effect models to estimate the effect of different dimensions of gender inequalities on female overweight. This study demonstrates that the form of gender inequality or women’s mistreatment differently affects female bodyweight. Indeed, we show that some forms of women’s mistreatments (such as perceived community violence and age difference with husband) increase the risk of female overweight, whereas more severe forms of abuse such as child marriage increase the risk of underweight. Moreover, we also find that higher decision-making power and autonomy about outings are risk factors of weight gain and obesity, especially in urban settings, perhaps indicating a higher exposure to urban obesogenic lifestyles. To conclude, our results suggest that, although improving women’s status in society may be a key action to address the epidemic of obesity, policies must also target hazardous habits that emancipation may imply in urban (obesogenic) environments. These meta-data include: (i) the merged database from the two waves of IHDS we used in the study (.dta in Stata format); (ii) the codes used for data treatment and analysis (.do in Stata format). Original IHDS data are freely available on: https://ihds.umd.edu. Further details about our methods and results will be published soon in a scientific journal and will reference these meta-data.

Keywords: India; Gender inequality; Obesity; Hausman-Taylor estimations; Fixed effects estimations. JEL codes: I14 I15 J16

Gender Inequality Index (GII) The GII is an inequality index. It measures gender inequalities in three important aspects of human development—reproductive health, measured by maternal mortality ratio and adolescent birth rates; empowerment, measured by proportion of parliamentary seats occupied by females and proportion of adult females and males aged 25 years and older with at least some secondary education; and economic status, expressed as labour market participation and measured by labour force participation rate of female and male populations aged 15 years and older. The GII is built on the same framework as the IHDI—to better expose differences in the distribution of achievements between women and men. It measures the human development costs of gender inequality. Thus the higher the GII value the more disparities between females and males and the more loss to human development. The GII sheds new light on the position of women in 162 countries; it yields insights in gender gaps in major areas of human development. The component indicators highlight areas in need of critical policy intervention and it stimulates proactive thinking and public policy to overcome systematic disadvantages of women.A composite measure reflecting inequality in achievement between women and men in three dimensions: reproductive health, empowerment and the labour market. See Technical note 4 at http://hdr.undp.org/sites/default/files/hdr2020_technical_notes.pdf for details on how the Gender Inequality Index is calculated.

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Wheeling. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Wheeling, the median income for all workers aged 15 years and older, regardless of work hours, was $34,933 for males and $25,827 for females.

These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 26% between the median incomes of males and females in Wheeling. With women, regardless of work hours, earning 74 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thecity of Wheeling.

- Full-time workers, aged 15 years and older: In Wheeling, among full-time, year-round workers aged 15 years and older, males earned a median income of $55,684, while females earned $49,275, resulting in a 12% gender pay gap among full-time workers. This illustrates that women earn 88 cents for each dollar earned by men in full-time positions. While this gap shows a trend where women are inching closer to wage parity with men, it also exhibits a noticeable income difference for women working full-time in the city of Wheeling.

Interestingly, when analyzing income across all roles, including non-full-time employment, the gender pay gap percentage was higher for women compared to men. It appears that full-time employment presents a more favorable income scenario for women compared to other employment patterns in Wheeling.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Wheeling median household income by race. You can refer the same here

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 same experiment was run in three cities across different countries. Each session consists of 13 participants, who are undergraduate university students. The same design was applied in Barcelona (Spain), Amsterdam (the Netherlands), and Bologna (Italy)

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).