Dataset Card for Earnings 22

  Dataset Summary

Earnings-22 provides a free-to-use benchmark of real-world, accented audio to bridge academic and industrial research. This dataset contains 125 files totalling roughly 119 hours of English language earnings calls from global countries. This dataset provides the full audios, transcripts, and accompanying metadata such as ticker symbol, headquarters country, and our defined "Language Region".

  Supported Tasks and… See the full description on the dataset page: https://huggingface.co/datasets/distil-whisper/earnings22.

The Earnings 22 dataset ( also referred to as earnings22 ) is a 119-hour corpus of English-language earnings calls collected from global companies. The primary purpose is to serve as a benchmark for industrial and academic automatic speech recognition (ASR) models on real-world accented speech.

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 Vian. 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 2021

Based on our analysis ACS 2017-2021 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Vian, the median income for all workers aged 15 years and older, regardless of work hours, was $23,355 for males and $16,833 for females.

These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 28% between the median incomes of males and females in Vian. With women, regardless of work hours, earning 72 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thetown of Vian.

- Full-time workers, aged 15 years and older: In Vian, among full-time, year-round workers aged 15 years and older, males earned a median income of $39,183, while females earned $30,401, leading to a 22% gender pay gap among full-time workers. This illustrates that women earn 78 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.

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 Vian, showcasing a consistent income pattern irrespective of employment status.

https://i.neilsberg.com/ch/vian-ok-income-by-gender.jpeg" alt="Vian, OK gender based income disparity">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-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 2022
• 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 Vian median household income by gender. You can refer the same here

In 2024 men aged between 50 and 59 were the highest full-time earners in the United Kingdom among different gender and age groups, with men of different ages consistently earning more than women.

SES22 - Mean and Median Earnings per hour and Paid Weekly Hours. Published by Central Statistics Office. Available under the license Creative Commons Attribution 4.0 (CC-BY-4.0).Mean and Median Earnings per hour and Paid Weekly Hours...

These data were developed by the Research & Analytics Group at the Atlanta Regional Commission using data from the U.S. Census Bureau across all standard and custom geographies at statewide summary level where applicable. .
For a deep dive into the data model including every specific metric, see the ACS 2018-2022 Data Manifest. The manifest details ARC-defined naming conventions, field names/descriptions and topics, summary levels; source tables; notes and so forth for all metrics. Find naming convention prefixes/suffixes, geography definitions and user notes below.Prefixes:NoneCountpPercentrRatemMedianaMean (average)tAggregate (total)chChange in absolute terms (value in t2 - value in t1)pchPercent change ((value in t2 - value in t1) / value in t1)chpChange in percent (percent in t2 - percent in t1)sSignificance flag for change: 1 = statistically significant with a 90% CI, 0 = not statistically significant, blank = cannot be computedSuffixes:_e22Estimate from 2018-22 ACS_m22Margin of Error from 2018-22 ACS_e102006-10 ACS, re-estimated to 2020 geography_m10Margin of Error from 2006-10 ACS, re-estimated to 2020 geography_e10_22Change, 2010-22 (holding constant at 2020 geography)GeographiesAAA = Area Agency on Aging (12 geographic units formed from counties providing statewide coverage)ARC21 = Atlanta Regional Commission modeling area (21 counties merged to a single geographic unit)ARWDB7 = Atlanta Regional Workforce Development Board (7 counties merged to a single geographic unit)BeltLineStatistical (buffer)BeltLineStatisticalSub (subareas)Census Tract (statewide)CFGA23 = Community Foundation for Greater Atlanta (23 counties merged to a single geographic unit)City (statewide)City of Atlanta Council Districts (City of Atlanta)City of Atlanta Neighborhood Planning Unit (City of Atlanta)City of Atlanta Neighborhood Statistical Areas (City of Atlanta)County (statewide)Georgia House (statewide)Georgia Senate (statewide)HSSA = High School Statistical Area (11 county region)MetroWater15 = Atlanta Metropolitan Water District (15 counties merged to a single geographic unit)Regional Commissions (statewide)State of Georgia (single geographic unit)Superdistrict (ARC region)US Congress (statewide)UWGA13 = United Way of Greater Atlanta (13 counties merged to a single geographic unit)ZIP Code Tabulation Areas (statewide)The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent. The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2018-2022). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available. For further explanation of ACS estimates and margin of error, visit Census ACS website.Source: U.S. Census Bureau, Atlanta Regional CommissionDate: 2018-2022Data License: Creative Commons Attribution 4.0 International (CC by 4.0)Link to the data manifest: https://opendata.atlantaregional.com/documents/3b86ee614e614199ba66a3ff1ebfe3b5/about

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 Winslow. 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 Winslow, the median income for all workers aged 15 years and older, regardless of work hours, was $28,438 for males and $22,292 for females.

These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 22% between the median incomes of males and females in Winslow. With women, regardless of work hours, earning 78 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thecity of Winslow.

- Full-time workers, aged 15 years and older: In Winslow, among full-time, year-round workers aged 15 years and older, males earned a median income of $42,292, while females earned $33,125, leading to a 22% gender pay gap among full-time workers. This illustrates that women earn 78 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.

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

Annual estimates of paid hours worked and earnings for UK employees by sex, and full-time and part-time, by four-digit Standard Industrial Classification 2007.

This statistic shows the median household income in the United States from 1990 to 2023 in 2023 U.S. dollars. The median household income was 80,610 U.S. dollars in 2023, an increase from the previous year. Household incomeThe median household income depicts the income of households, including the income of the householder and all other individuals aged 15 years or over living in the household. Income includes wages and salaries, unemployment insurance, disability payments, child support payments received, regular rental receipts, as well as any personal business, investment, or other kinds of income received routinely. The median household income in the United States varies from state to state. In 2020, the median household income was 86,725 U.S. dollars in Massachusetts, while the median household income in Mississippi was approximately 44,966 U.S. dollars at that time. Household income is also used to determine the poverty line in the United States. In 2021, about 11.6 percent of the U.S. population was living in poverty. The child poverty rate, which represents people under the age of 18 living in poverty, has been growing steadily over the first decade since the turn of the century, from 16.2 percent of the children living below the poverty line in year 2000 to 22 percent in 2010. In 2021, it had lowered to 15.3 percent. The state with the widest gap between the rich and the poor was New York, with a Gini coefficient score of 0.51 in 2019. The Gini coefficient is calculated by looking at average income rates. A score of zero would reflect perfect income equality and a score of one indicates a society where one person would have all the money and all other people have nothing.

NSA22 - Mean and Median Hourly Earnings. Published by Central Statistics Office. Available under the license Creative Commons Attribution 4.0 (CC-BY-4.0).Mean and Median Hourly Earnings...

GP Earnings and Expenses Estimates, 2022/23 presents earnings and expenses information for full and part-time GPs working in the UK as either a contractor or salaried GP during the 2022/23 financial year. The findings in this report are based upon anonymised tax data from HM Revenue and Customs' Self Assessment tax records and cover both NHS/Health Service and private income. Earnings and expenses information is published for contractor, salaried and combined (contractor and salaried) GPs at country level, with a regional breakdown where available. Figures are also given by contract type for GPs working under a General Medical Services (GMS) or a Primary Medical Services (PMS) contract as well as combined (GPMS). The report is primarily used as evidence in remuneration negotiations and by the Review Body for Doctors' and Dentists' Remuneration (DDRB). It has been agreed by the Technical Steering Committee (TSC), which is chaired by NHS England and has representation from the four UK Health Departments and, representing the interests of GPs, the British Medical Association. The Covid-19 pandemic is likely to have impacted on earnings and expenses during 2020/21 and 2021/22. Please refer to the reports for these years for further details of Covid-19 arrangements.

The net income of 22Nd Century Group with headquarters in the United States amounted to ****** million U.S. dollars in 2024. The reported fiscal year ends on December 31.Compared to the earliest depicted value from 2020 this is a total increase by approximately **** million U.S. dollars. The trend from 2020 to 2024 shows, however, that this increase did not happen continuously.

Graph and download economic data for Average Hourly Earnings of All Employees, Total Private (CES0500000003) from Mar 2006 to Jun 2025 about earnings, average, establishment survey, hours, wages, private, employment, and USA.

Mean and Median Earnings per hour and Paid Weekly Hours

Explore the progression of average salaries for graduates in Computer Science (Conferred On 05/22/2015) from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of Computer Science (Conferred On 05/22/2015) relative to other fields. This data is essential for students assessing the return on investment of their education in Computer Science (Conferred On 05/22/2015), providing a clear picture of financial prospects post-graduation.

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 University Park. 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 University Park, the median income for all workers aged 15 years and older, regardless of work hours, was $139,583 for males and $30,533 for females.

These income figures highlight a substantial gender-based income gap in University Park. Women, regardless of work hours, earn 22 cents for each dollar earned by men. This significant gender pay gap, approximately 78%, underscores concerning gender-based income inequality in the city of University Park.

- Full-time workers, aged 15 years and older: In University Park, among full-time, year-round workers aged 15 years and older, males earned a median income of $250,001, while females earned $120,335, leading to a 52% gender pay gap among full-time workers. This illustrates that women earn 48 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 University Park, 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 University Park median household income by race. You can refer the same here

Explore the progression of average salaries for graduates in Computer Science (Conferred 08/22/2014) from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of Computer Science (Conferred 08/22/2014) relative to other fields. This data is essential for students assessing the return on investment of their education in Computer Science (Conferred 08/22/2014), providing a clear picture of financial prospects post-graduation.

Earnings-21, a 39-hour corpus of earnings calls containing entity-dense speech from nine different financial sectors. This corpus is intended to benchmark ASR (Automatic Speech Recognition) systems in the wild with special attention towards named entity recognition.

See notice below about this dataset

This dataset provides the average annual earnings by industry per district.

Wage records are obtained from the Massachusetts Department of Unemployment Assistance (DUA) using a secure, anonymized matching process with limitations. For details on the process and suppression rules, please visit the Employment and Earnings of High School Graduates dashboard.

This dataset is one of three containing the same data that is also published in the Employment and Earnings of High School Graduates dashboard: Average Earnings by Student Group Average Earnings by Industry College and Career Outcomes

List of Industries

• 00 - All Students
• 11 - Agriculture, Forestry, Fishing and Hunting
• 21 - Mining, Quarrying, and Oil and Gas Extraction
• 22 - Utilities
• 23 - Construction
• 31 - Manufacturing
• 42 - Wholesale Trade
• 44 - Retail Trade
• 48 - Transportation and Warehousing
• 51 - Information
• 52 - Finance and Insurance
• 53 - Real Estate and Rental and Leasing
• 54 - Professional, Scientific, and Technical Services
• 55 - Management of Companies and Enterprises
• 56 - Administrative and Support and Waste Management and Remediation Services
• 61 - Educational Services
• 62 - Health Care and Social Assistance
• 71 - Arts, Entertainment, and Recreation
• 72 - Accommodation and Food Services
• 81 - Other Services (except Public Administration)
• 92 - Public Administration
• 0 - No Industry Reported

2025 Update on DESE Data on Employment and Earnings 

The data link between high school graduates and future earnings makes it possible to follow students beyond high school and college into the workforce, enabling long-term evaluation of educational programs using workforce outcomes.

While DESE has published these data in the past, as of June 2025 we are temporarily pausing updates due to an issue conducting the link that was brought to our attention in 2023 by a team of researchers. The issue impacts the earnings information for students who never attended a postsecondary institution or who only attended private or out-of-state colleges or universities, beginning with the 2017 high school graduation cohort, with growing impact in each successive high school graduation cohort.

The issue does not impact the earnings information for students who attended a Massachusetts public institution of higher education, and earnings data for those students will continue to be updated.

Once a solution is found, the past cohorts of data with low match rates will be updated. DESE and partner agencies are exploring linking strategies to maximize the utility of the information.

More detailed information can be found in the attached memo provided by the research team from the Annenberg Institute. We thank them for calling this issue to our attention.

In 2023 in the United States, the median hourly rate of a worker's wage between 20 and 24 years old was 16.4 current U.S. dollars. Workers between the ages of 35 and 44 years old had the highest hourly wage in that year, at 21.2 current U.S. dollars.