About this dataset

Context

The dataset tabulates the Gay population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Gay across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Gay was 116, a 4.13% decrease year-by-year from 2022. Previously, in 2022, Gay population was 121, an increase of 5.22% compared to a population of 115 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Gay decreased by 37. In this period, the peak population was 153 in the year 2000. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Gay is shown in this column.
• Year on Year Change: This column displays the change in Gay population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. 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 Gay Population by Year. You can refer the same here

LGBT+ rights are human rights that all lesbian, gay, bisexual, transgender and other people outside traditional sexuality and gender categories have. But in practice, these rights are often not protected to the same extent as the rights of straight and cisgender people.

Among others, LGBT+ rights include: physical integrity rights, such as not being executed for their sexuality or gender and not being subjected to conversion therapies; social rights, such as changing their legal gender, being sexually intimate, marrying, and adopting children with people of the same sex; economic rights such as not being discriminated at work; and political rights, such as being able to advocate for themselves and their communities publicly.

The protection of these rights allows LGBT+ people to live the lives they want and to thrive in them.

On this page, you can find data and visualizations on how the protection of LGBT+ rights has changed over time, and how it differs across countries.

Sexual orientation in the UK by region, sex, age, legal partnership status, and ethnic group. These are official statistics in development.

Context

Rainbow Europe brings together both the legal index of LGBTI equality based on our Rainbow Europe Map and an overview of the social climate for LGBTI people in each country based on our Annual Review of the Human Rights Situation of Lesbian, Gay, Bisexual, Trans and Intersex People. Rainbow Europe ranks all 49 European countries on a scale between 0% (gross violations of human rights, discrimination) and 100% (respect of human rights, full equality). -From https://www.rainbow-europe.org/about

Content

This dataset contains all of the laws, policies and other deciding factors that Rainbow Europe uses to calculate their index, and whether they are applied in each country. It also contains the score contributions applied to calculate the index.

Score

Rainbow Europe weighs the conditions to get a 0-100% scale. The weights and criteria are on their "about page" linked above. The score percent field contains the weightings if the condition is applied, and 0 if it's not.

Update Frequency

I aim to update the dataset roughly at the end of each year and keep the previous versions to document the progress of LGBTQ+ rights in Europe.

Quick Reminder

Upvote if you like this dataset or find it useful!

About this dataset

Context

The dataset tabulates the Non-Hispanic population of Gay by race. It includes the distribution of the Non-Hispanic population of Gay across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of Gay across relevant racial categories.

Key observations

Of the Non-Hispanic population in Gay, the largest racial group is White alone with a population of 75 (98.68% of the total Non-Hispanic population).

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (for Non-Hispanic) for the Gay
• Population: The population of the racial category (for Non-Hispanic) in the Gay is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Gay total Non-Hispanic 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 Gay Population by Race & Ethnicity. You can refer the same here

20,000 Dear Abby Questions

1985-2017 Questions on Sex, LGBTQ Issues, Religion and Relationships

By Kelly Garrett [source]

About this dataset

This dataset contains 20,000+ questions submitted to the iconic advice columnist and agony aunt, Dear Abby. Drawing from articles published around the United States between 1985 to 2017, this data reveals a wealth of information about the anxieties and concerns of ordinary citizens during that time period.

The topics covered can be grouped into three main categories: sex education and relationships; LGBTQ issues; and religious queries. Questions regarding parents, children, friends, bosses, etc fill out the rest of our corpus. This data offers an interesting glimpse into the collective experiences of people living in America during these decades - showing how different issues have risen up over time or evolved in their representation - as well as offering insights on how people resorted to Dear Abby for advice on problems both mundane and extraordinary during these years.

If you're looking for meaningful datasets with conversations on human connection or seeking a better understanding of American history beyond current headlines - then this is your one-stop source! Explore all that this data has to offer by discovering trends within it. License information can be found here: LICENSE. Enjoy!

More Datasets

For more datasets, click here.

Featured Notebooks

• 🚨 Your notebook can be here! 🚨!

How to use the dataset

• Start by Familiarizing Yourself with The Dataset: Before diving too deep into the data it's important to take some time familiarize yourself with the columns available and their corresponding data. This includes year, month day and url which provide information about when and where the particular question was published; as well as title which provides overlap about when/where a question was published; and lastly question_only which includes only the text of each individual submitted question itself.

• Consider Your Topic: Think broadly about what you are most interested in exploring through this data as it gives us direct insight into topics that Americans have been struggling with over time (such as LGBTQ issues or religion). Some ideas for questions might include “how has anxiety around a certain topic changed over time?” or “what are people most struggling with today?” Also consider specific keywords related to your topic – Dear Abby discussions sex may include words such as sexual harassment or infidelity while keywords exploring LGBTQ issues may include transgender or same-sex marriage – since you’ll likely use them in your analysis moving forward!

• Perform Your Analysis: Now that you know what columns matter most & what questions you want answered; it’s time to start performing your analysis! In order to get meaningful results out of your findings be sure make sure measure several points (e.g., mean values) along larger trends over different timelines throughout history such as 5 year intervals or looking at specific decades on their own). You can also manually group questions into categories when appropriate so that navigating complex topics becomes easier & more streamlined from an end user perspective (or further pursue techniques like t-SNE).

• Visualize Your Findings: Use any form of visualization tools (such trends graphs/charts) – e specially those available through Kaggle – for easier consumption of whatever insights its pulled out form these 20k submissions! As mentioned before these visualizations will allow you understand macro (& micro!) trends between a given topic an countless other social ones without having read even 1 entire single letter yourself .

5 . Share Your Insights : It isn't just enough knowing how Americans felt during certain

Research Ideas

• Social and Cultural Trends Analysis: This data can be used to analyze the changes in social and cultural trends over the 30-year period, such as identifying topics that were more prominent at certain times.
• Characterization of Reader Demographics: By analysing this dataset, we can gain insight into the demographics of Dear Abby's readers (e.g., age groupings, gender, location).
• Building a Natural Language Understanding Model: The data can be used to create a natural language understanding model that could accurately predict answers based on questions submitted by readers

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

See the d...

SPSS Dataset and Codebook for survey of LGBT people conducted December 22, 2021 - January 17, 2022. The survey was approved by California Polytechnic State University IRB on November 14, 2021. IRB #2021-221-OL. Funding to conduct this survey was awarded through the California Polytechnic State University Research Scholarly and Creative Activities (RSCA) Grant Program administered by the Cal Poly division of Research, Economic Development & Graduate Education. The material contained in this collection include an anonymized dataset and codebook, a methodological appendix, statistical appendix, and supplemental online appendix for the book Yes Gawd! How Faith Shapes LGBT Identity and Politics (Temple University Press).

Cities are in constant competition for residents, businesses, and employees, and inclusiveness is a crucial factor that attracts all three. The Municipal Equality Index (MEI) specifically measures laws and policies of municipalities to examine how inclusive cities are of LGBTQ (Lesbian, Gay, Bisexual, Transgender, and Questioning) people.Administered by the Human Rights Campaign, the MEI scorecard criteria annually evaluate a municipality on six categories, with bonus points available: Non-Discrimination Laws: This category evaluates whether discrimination based on sexual orientation and gender identity is prohibited by city, county, or state in areas of employment m housing, and public accommodations.Relationship Recognition: Marriage, civil unions, and comprehensive domestic partnerships are matters of state policy; cities and counties have only the power to create domestic partner registries.Municipality as Employer: By offering equivalent benefits and protections to LGBTQ employees, and by awarding contracts to fair-minded businesses, municipalities commit themselves to treating LGBTQ employees equally.Municipal Services: The section assesses the efforts of the city to ensure LGBTQ constituents are included in city services and programs.Law Enforcement: Fair enforcement of the law includes responsible reporting of hate crimes and engaging with the LGBTQ community in a thoughtful and respectful way.Relationship with the LGBTQ Community: This category measures the city leadership’s commitment to fully include the LGBTQ community and to advocate for full equality. Additional information available at hrc.org/meiThis page provides data for the Municipality Equality Index performance measure. The performance measure dashboard is available at 3.12 Municipal Equality Index. Additional Information Source: Contact: Wydale HolmesContact E-Mail: wydale_holmes@tempe.govData Source Type: ExcelPreparation Method: Publish Frequency: Annually, OctoberPublish Method: ManualData Dictionary

This table presents a socio-demographic and socio-economic statistical profile of the population aged 15 and older by sexual orientation, geographic region, sex and age group. The characteristics included are: marital status, presence of children under 12 in the household, education, employment, household income, Indigenous identity, belonging to a population group designated as a visible minority, language(s) spoken at home, and place of residence (urban/rural). These estimates are obtained from Canadian Community Health Survey, 2015 to 2018 pooled data.

The survey asked lesbian, gay, bisexual and transgender (LGBT) people whether they had experienced discrimination, violence, verbal abuse or hate speech on the grounds of their sexual orientation or gender identity. The results reflect the experiences of more than 93,000 individuals who completed the online survey across Europe.

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 Gay. 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 Gay, the median income for all workers aged 15 years and older, regardless of work hours, was $38,558 for males and $33,750 for females.

Based on these incomes, we observe a gender gap percentage of approximately 12%, indicating a significant disparity between the median incomes of males and females in Gay. Women, regardless of work hours, still earn 88 cents to each dollar earned by men, highlighting an ongoing gender-based wage gap.

Surprisingly, within the subset of full-time workers, women earn a higher income than men, earning 1.34 dollars for every dollar earned by men. This suggests that within full-time roles, womens median incomes significantly surpass mens, contrary to broader workforce trends.

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 Gay median household income by race. You can refer the same here

Sexual identity estimates by occupation 2014. This is presented at a UK level, and broken down by England, Wales, Scotland and Northern Ireland.

Bills in US State Legislatures with that target negative impacts specifically to folks in the LGBTQ community. I have not done any of the data gathering for this, data set is sourced from the ACLU https://www.aclu.org/legislative-attacks-on-lgbtq-rights?state=

This paper is a systematic review and meta-analysis on sexual orientation identity development milestones among people who are lesbian, gay, bisexual, or another sexual minority identity (LGB+). Common milestones measured in the 30 studies reviewed were becoming aware of queer attractions, questioning one’s sexual orientation, self-identifying as LGB+, coming out to others, engaging in sexual activity, and initiating a romantic relationship. Milestones occurred in different sequences, although attraction was almost always first, often followed by self-identification and/or sexual activity; coming out and initiating a romantic relationship often followed these milestones. Meta-analysis results showed that the mean effect sizes and 95% confidence intervals varied by milestone: attraction [Mage=12.7 (10.1, 15.3)], questioning one’s orientation [Mage=13.2 [12.8, 13.6]), self-identifying [Mage=17.8 (11.6, 24.0)], sexual activity [Mage=18.1 (17.6, 18.6)], coming out [Mage=19.6 (17.2, 22.0)], and romantic relationship [Mage=20.9 (13.2, 28.6)]. Nonetheless, results also showed substantial heterogeneity in the mean effect sizes. Additional meta-analyses showed that milestone timing varied by sex, sexual orientation, race/ethnicity, and birth cohort. Although patterns were found in LGB+ identity development, there was considerable diversity in milestone trajectories.

Abstract This article discusses the adoption of the abbreviation LGBT (lesbian, gay, bisexual, transvestite, and transsexual), questioning the representativeness of the groups contained in this acronym in Administration research. Some authors in Brazil state that, although there is the intention to construct a field of research on the subject, the agenda is mostly aimed at research on gay people (CARRIERI, SOUZA and AGUIAR, 2014). Therefore, the research question is: Is it possible to treat identity categories that are so different under the same prism? The article is grounded on (1) a historical version of the constitution of LGBT groups, showing how they are organized and fragmented in Brazil (FACCHINI, 2005); (2) a discussion on the adoption of the LGBT acronym as a universal category, based on the debate about contingent identities (BUTLER, 1998); (3) a literature review of Brazilian Administration using the SPELL database. A total of 34 articles approaching LGBT groups were found. Research on gays predominates while groups of lesbians, transvestites, and transsexuals are underrepresented. It is perceived that, although there are similarities from the point of view that all the identity categories are targets of discrimination and violence (which is justified because they are categories considered deviant), the articles mark the differences between them. It is in these differences that there are possibilities for Administration research to question the adoption of acronyms, such as LGBT, as a universally representative and unified concept.

About this dataset

Context

The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within Gay. The dataset can be utilized to gain insights into gender-based income distribution within the Gay population, aiding in data analysis and decision-making..

Key observations

• Employment patterns: Within Gay, among individuals aged 15 years and older with income, there were 51 men and 43 women in the workforce. Among them, 41 men were engaged in full-time, year-round employment, while 17 women were in full-time, year-round roles.
• Annual income under $24,999: Of the male population working full-time, 17.07% fell within the income range of under $24,999, while 5.88% of the female population working full-time was represented in the same income bracket.
• Annual income above $100,000: 12.20% of men in full-time roles earned incomes exceeding $100,000, while none of women in full-time positions earned within this income bracket.
• Refer to the research insights for more key observations on more income brackets ( Annual income under $24,999, Annual income between $25,000 and $49,999, Annual income between $50,000 and $74,999, Annual income between $75,000 and $99,999 and Annual income above $100,000) and employment types (full-time year-round and part-time)

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Income brackets:

• $1 to $2,499 or loss
• $2,500 to $4,999
• $5,000 to $7,499
• $7,500 to $9,999
• $10,000 to $12,499
• $12,500 to $14,999
• $15,000 to $17,499
• $17,500 to $19,999
• $20,000 to $22,499
• $22,500 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $54,999
• $55,000 to $64,999
• $65,000 to $74,999
• $75,000 to $99,999
• $100,000 or more

Variables / Data Columns

• Income Bracket: This column showcases 20 income brackets ranging from $1 to $100,000+..
• Full-Time Males: The count of males employed full-time year-round and earning within a specified income bracket
• Part-Time Males: The count of males employed part-time and earning within a specified income bracket
• Full-Time Females: The count of females employed full-time year-round and earning within a specified income bracket
• Part-Time Females: The count of females employed part-time and earning within a specified income bracket

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.

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 Gay median household income by race. You can refer the same here

The EU LGBTI II survey is a large-scale web-administered survey of the experiences and views of lesbian, gay, bisexual, transgender and intersex (LGBTI) individuals, using an anonymous online questionnaire. The survey was conducted between 27 May and 22 July 2019 via the platform www.lgbtisurvey.eu and collected valid responses from 139 799 participants from the European Union (EU) Member States, North Macedonia and Serbia. The survey provides comparative evidence on how LGBTI people in the EU experience discrimination, violence and harassment in various areas of life, including employment, education, healthcare, housing and other services.

This research project examined the experiences of Irish lesbian, gay, bisexual and transgendered (LGBT) people living in London. There is a long history of Irish migration to the UK, particularly London. This has coincided historically with many Irish LGBT people feeling compelled to emigrate in search of a more supportive social climate. The appeal of global cities to LGBT people has long been acknowledged. Metropolitan centres are associated with tolerance of sexual diversity and established queer communities. This study will explore Irish queer migrants' reasons for moving to London and experiences there. The research questions will focus on notions of home, identity, belonging, familial relationships and subjectivity. By exploring the relationship between sexuality, ethnicity and diaspora, the study intended to uncover the ways in which contemporary sexual citizenship, migration and queer imaginaries of the metropolis are mutually implicated in complex ways. A qualitative dataset is produced containing interviews with 38 Irish LGBT participants who have been living in London for at least five years. In addition to generating new theoretical work on sexuality and migration, the research findings will be used to inform policy and debate regarding processes of social exclusion.

This project uses data on same-gendered households (via the 2016 Australian Census) and cohabitation rates (via behavioural population surveys) to estimate the total number and prevalence of gay men and lesbian women living across Australia and in each postcode. The data and code for generating relevant outputs and analyses are contained here.(i) Stock datasets [Files: remoteness2012.dta; postcode_clusters.dta] This item contains files required to organize the Australian Census data: (i) the 'remoteness' classifications per the Australian Statistical Geography Standard (Australian Bureau of Statistics, 2011), and (ii) clustering of those postcodes with base total populations of less than 200 people. The clustering process was undertaken manually by reviewing postcodes in that bracket and combining them with neighboring postcodes within the same jurisdictions and remoteness classification until the threshold of 200 was met. Preference was given for clustering postcodes that shared the largest geographic border and/or with the smallest population sizes.(ii) Underlying datasets [Files: pop_sex_0-9.xlsx; pop_sex_10-19.xlsx; pop_sex_18.xlsx; pop_sex_19.xlsx; pop_sex_20-24.xlsx; pop_sex_25-29.xlsx; pop_sex_all.xlsx; ss_couples_all.xlsx]This item contains tables created by and extracted from the Australian Bureau of Statistics 'TableBuilder' platform, which allows access to and organization of aggregate data from the 2016 Australian Census. The tables exist in two groups (i) total number of Census participants, stratified by postcode, age group and gender, and (ii) total number of same-gendered households, stratified by postcode and gender.(iii) Organizational code [File: generate dataset and analysis.do]This file contains the code (Stata, version 15.0) to organize the 'underlying datasets' and combine them with information collated from behavioral survey data. To account for remoteness classification via the Australian Statistical Geography Standard, it merges by postcode on a separate 'stock dataset' (remoteness2012). To account for clustering of postcodes with small overall populations, it merges by postcode on a separate 'stock dataset' (postcode_clusters). The code additionally produces outcomes of descriptive analyses and relevant tables, and generates a final dataset of, by-postcode, population sizes and prevalences.(iv) Final dataset [File: Appendix B - dataset.xlsx]This final dataset contains organized, merged and interpreted outcomes, presented as variables of, by-postcode, the estimated absolute number and prevalence of gay men and lesbian women in Australia. A data dictionary is included.

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 Fort Gay. 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 Fort Gay, the median income for all workers aged 15 years and older, regardless of work hours, was $18,125 for males and $21,071 for females.

Contrary to expectations, women in Fort Gay, women, regardless of work hours, earn a higher income than men, earning 1.16 dollars for every dollar earned by men. This analysis indicates a significant shift in income dynamics favoring females.

Contrary to expectations, in Fort Gay, women, earn a higher income than men, earning 1.13 dollars for every dollar earned by men. This analysis showcase a consistent trend of women outearning men, when working full-time or part-time in the town of Fort Gay.

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 Fort Gay median household income by race. You can refer the same here