From the project website: https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/FXXLTS

To what extent do countries protect the rights of transgender people? How does this differ from legal protections countries offer sexual orientation minorities? What conditions are beneficial for advancing trans rights? Limitations in data availability and accessibility make answering these types of trans-specific questions difficult. To address this shortcoming, this article introduces a new dataset. The Trans Rights Indicator Project (TRIP) provides insight into the legal situations transgender people faced in 173 countries from 2000 to 2021. The dataset currently includes 14 indicators that capture the presence or absence of laws related to criminalization, legal gender recognition, and anti-discrimination protections. The article then uses this data to discuss the global status of transgender rights throughout the period and compares these trends to sexual orientation rights. Finally, the article concludes with a preliminary analysis of three institutional and cultural factors that may help explain variation in transgender rights throughout the world.

CONTENT

Gender Inequality Index: 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/hdr2022_technical_notes.pdf for details on how the Gender Inequality Index is calculated.

Maternal mortality ratio: Number of deaths due to pregnancy-related causes per 100,000 live births.

Adolescent birth rate: Number of births to women ages 15–19 per 1,000 women ages 15–19.

Share of seats in parliament: Proportion of seats held by women in the national parliament expressed as a percentage of total seats For countries with a bicameral legislative system, the share of seats is calculated based on both houses.

Population with at least some secondary education: Percentage of the population ages 25 and older that has reached (but not necessarily completed) a secondary level of education.

The World Bank's Gender Data Portal makes the latest gender statistics accessible through compelling narratives and data visualizations to improve the understanding of gender data and facilitate analyses that inform policy choices.

They include:

• Population
• SDGs
• Children 0-14
• Youth 15-24
• Assets
• Education
• Employment and Time Use
• Entrepreneurship
• Environment
• Health
• Leadership
• Norms and Decision-making
• Technology
• Violence

About this dataset

Context

The dataset tabulates the population of Globe by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Globe. The dataset can be utilized to understand the population distribution of Globe by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Globe. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Globe.

Key observations

Largest age group (population): Male # 20-24 years (347) | Female # 50-54 years (433). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Globe population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Globe is shown in the following column.
• Population (Female): The female population in the Globe is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Globe for each age group.

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 Globe Population by Gender. You can refer the same here

About this dataset

Context

The dataset tabulates the population of White Earth by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for White Earth. The dataset can be utilized to understand the population distribution of White Earth by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in White Earth. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for White Earth.

Key observations

Largest age group (population): Male # 10-14 years (17) | Female # 40-44 years (13). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the White Earth population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the White Earth is shown in the following column.
• Population (Female): The female population in the White Earth is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in White Earth for each age group.

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 White Earth Population by Gender. You can refer the same here

This dataset is a comprehensive resource for analyzing key socio-economic and health indicators related to gender across various countries worldwide. It serves as an example dataset for the R programming package 'genderstat'. The dataset encompasses crucial metrics including life expectancy, education, gross national income per capita, maternal mortality rates, adolescent birth rates, and labor force participation. It has been meticulously curated from reputable sources such as the UNDP Human Development Reports and the World Bank Gender Data Portal.

Gender Info 2007 is a global database of gender statistics and indicators on a wide range of policy areas, including: population, families, health, education, work, and political participation. It can be used by governments, international organizations, advocacy groups, researchers and others in need of statistics for planning, analysis, advocacy and awareness-raising. Users will find in Gender Info an easy-to-use tool to shed light on gender issues through customizable tables, graphs and maps. It is an initiative of the United Nations Statistics Division, produced in collaboration with the United Nations Children’s Fund (UNICEF) and the United Nations Population Fund (UNFPA).

This dataset was last updated in 2008. If you need a more current version of the data please visit http://unstats.un.org/unsd/gender/data.html for other Gender Statistics.

Acknowledgements

This dataset was kindly published by the United Nations on the UNData site. You can find the original dataset here.

License

Per the UNData terms of use: all data and metadata provided on UNdata’s website are available free of charge and may be copied freely, duplicated and further distributed provided that UNdata is cited as the reference.

Gender Disaggregated Labor Database (GDLD) is a global micro labor force database based on World Bank household survey collection and other public resources. This database has harmonized the economic activities and occupation categories from local classification to international comparable classifications. It fills an important information gap in global sex statistics by providing detailed accounts on education, employment levels, wages, labor income, and employment status at very disaggregated economic activity level and occupation category than is usually available.

Humans Gender

## Overview

Humans Gender is a dataset for object detection tasks - it contains Man Woman annotations for 1,012 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

The Gender Statistics database is a comprehensive source for the latest sex-disaggregated data and gender statistics covering demography, education, health, access to economic opportunities, public life and decision-making, and agency. For further details, please refer to https://datacatalog.worldbank.org/search/dataset/0037654/gender-statistics

The Dataset was collected from Worldbank dataset.

You can download by using the filters. here: https://databank.worldbank.org/databases.aspx?fname=PolskaStats.html

This dataset compiles the first version of the worldwide gender-name dictionary (WGND) including 6.2 million names for 182 different countries to disambiguate the gender. (2016-11)

This dataset offers insights into gender diversity on a global scale, encompassing ten industries and seven regions.

About this dataset

Context

The dataset tabulates the population of Black Earth town by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Black Earth town across both sexes and to determine which sex constitutes the majority.

Key observations

There is a slight majority of male population, with 52.11% of total population being male. Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Black Earth town is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Black Earth town total population. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Black Earth town Population by Gender. You can refer the same here

Processed version of https://figshare.com/articles/Gender_statistics_from_World_Bank_-_CSV_-_September_2017/9904979This version is a much-reduced and rearranged version. It has been tidied to have one row per country, and has a few variables, mainly relating to expenditure, fertility, mortality. The data are an average of the values from 2012 through 2016.This version stores the population value in millions of people rather than numbers of people.See https://github.com/matthew-brett/datasets/tree/90626ae3/gender_stats for source and processing.Please attribute to the World Bank Data Catalogue with the this URL: https://datacatalog.worldbank.org/dataset/gender-statistics.Data dictionary at https://github.com/matthew-brett/datasets/blob/90626ae39f4f6f70bf43ed98c39197e8fe4d768c/gender_stats/processed/gender_stats_data_dict.md

This dataset revisits the first World Gender Name Dictionary (WGND 1.0), allowing to disambiguate the gender in data naming physical persons (Lax Martínez et al., 2016). We discuss its advantages and limitations and propose an expansion based on updated data and additional sources. By including more than 26 million records linking given names and 195 different countries and territories, the resulting WGND 2.0 substantially increases the international coverage of its processor. As a result, it is particularly designed to be applied to intellectual property unit-record data naming inventors, designers, individual applicants and other creators disclosed in these data.

Context

Human Development Reports published by the United Nations Development Programme include two datasets on gender development and inequality. These datasets provide statistics on differences between the two genders by country for in factors such as health, education and economic status.

More information and further datasets related to human development can be found at the UNDP Human Development Reports website.

Content

The datasets contain data for 188 countries for 2015.

Acknowledgements

The Human Development Reports are published by the United Nations Development Programme.

Main CSV file extracted from zip file download of World Bank gender statistics file.Copy of data as of 25th September 2019.

The WORLD Policy Analysis Center (WORLD) is committed to improving the quantity and quality of globally comparative data available to policymakers, citizens, civil society, and researchers on laws and policies that work to support human rights, including economic opportunity, social and civic engagement, human health, development, well-being, and equity. The WORLD Constitutions 2022 dataset was created to assess progress on constitutional rights that matter to equal opportunities through a systematic review of national constitutions across all 193 UN countries as of January 2022. The dataset covers equality and non-discrimination across race and/or ethnicity, gender and sex, migrants and refugees, religion and belief, disability status, socioeconomic status, sexual orientation, and gender identity, as well as the right to education, health, decent working conditions and non-discrimination in employment, and social protection.

Access data, visualizations, and stories that portray results of the IMF's research on gender and economics or create your own charts and analysis. This dataset includes gender inequality and development indices.

For further details, please see https://data.imf.org/?sk=388DFA60-1D26-4ADE-B505-A05A558D9A42&sId=1479329132316