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 Little Canada. 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 Little Canada, the median income for all workers aged 15 years and older, regardless of work hours, was $49,764 for males and $40,129 for females.

These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 19% between the median incomes of males and females in Little Canada. With women, regardless of work hours, earning 81 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thecity of Little Canada.

- Full-time workers, aged 15 years and older: In Little Canada, among full-time, year-round workers aged 15 years and older, males earned a median income of $69,643, while females earned $59,934, resulting in a 14% gender pay gap among full-time workers. This illustrates that women earn 86 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 Little Canada.

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 Little Canada.

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

About this dataset

Context

The dataset presents the mean household income for each of the five quintiles in New Canada, Maine, as reported by the U.S. Census Bureau. The dataset highlights the variation in mean household income across quintiles, offering valuable insights into income distribution and inequality.

Key observations

• Income disparities: The mean income of the lowest quintile (20% of households with the lowest income) is 15,315, while the mean income for the highest quintile (20% of households with the highest income) is 187,307. This indicates that the top earners earn 12 times compared to the lowest earners.
• *Top 5%: * The mean household income for the wealthiest population (top 5%) is 324,073, which is 173.02% higher compared to the highest quintile, and 2116.05% higher compared to the lowest quintile.

Content

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

Income Levels:

• Lowest Quintile
• Second Quintile
• Third Quintile
• Fourth Quintile
• Highest Quintile
• Top 5 Percent

Variables / Data Columns

• Income Level: This column showcases the income levels (As mentioned above).
• Mean Household Income: Mean household income, in 2022 inflation-adjusted dollars for the specific income level.

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 New Canada town median household income. You can refer the same here

Average hourly and weekly wage rate, and median hourly and weekly wage rate by North American Industry Classification System (NAICS), type of work, gender, and age group.

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 New Canada town. 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 New Canada town, the median income for all workers aged 15 years and older, regardless of work hours, was $52,250 for males and $27,500 for females.

These income figures highlight a substantial gender-based income gap in New Canada town. Women, regardless of work hours, earn 53 cents for each dollar earned by men. This significant gender pay gap, approximately 47%, underscores concerning gender-based income inequality in the town of New Canada town.

- Full-time workers, aged 15 years and older: In New Canada town, among full-time, year-round workers aged 15 years and older, males earned a median income of $63,125, while females earned $51,375, 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 New Canada town.

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 New Canada town median household income by race. You can refer the same here

Under the Public Service Compensation Disclosure Policy, compensation, including salary, benefit, and severance amounts for government employees with base salaries or severance payments of equal to or greater than the identified annual threshold, are available in the linked dataset.

Wages in Manufacturing in Canada increased to 32.16 CAD/Hour in April from 31.55 CAD/Hour in March of 2025. This dataset provides - Canada Average Hourly Wages in Manufacturing - actual values, historical data, forecast, chart, statistics, economic calendar and news.

This table is part of a series of tables that present a portrait of Canada based on the various census topics. The tables range in complexity and levels of geography. Content varies from a simple overview of the country to complex cross-tabulations; the tables may also cover several censuses.

Data on teachers' salaries in US dollars are presented.

A dataset that explores Green Card sponsorship trends, salary data, and employer insights for canada in the U.S.

This table contains 2144 series, with data for years 1991 - 2000 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (13 items: Canada; Prince Edward Island; Nova Scotia; Newfoundland and Labrador ...), North American Industry Classification System (NAICS) (366 items: Industrial aggregate excluding unclassified businesses; Goods producing industries; Forestry; logging and support ...).

This table contains 2144 series, with data for years 1991 - 2000 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (13 items: Canada; Prince Edward Island; Newfoundland and Labrador; Nova Scotia ...), North American Industry Classification System (NAICS) (366 items: Industrial aggregate excluding unclassified businesses; Goods producing industries; Forestry; logging and support ...).

A dataset that explores Green Card sponsorship trends, salary data, and employer insights for little canada, mn in the U.S.

This table contains 2144 series, with data for years 1991 - 2000 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (13 items: Canada; Prince Edward Island; Nova Scotia; Newfoundland and Labrador ...), North American Industry Classification System (NAICS) (366 items: Industrial aggregate excluding unclassified businesses; Forestry; logging and support; Goods producing industries ...).

This powerful dataset represents a meticulously curated snapshot of the United States job market throughout 2021, sourced directly from CareerBuilder, a venerable employment website founded in 1995 with a formidable global footprint spanning the US, Canada, Europe, and Asia. It offers an unparalleled opportunity for in-depth research and strategic analysis.

Dataset Specifications:

• Source: CareerBuilder.com (US Listings)
• Crawled by: Crawl Feeds in-house team
• Volume: Over 422,000 unique job records
• Timeliness: Last crawled in May 2021, providing a critical historical benchmark for post-pandemic labor market recovery and shifts.
• Format: Compressed ZIP archive containing structured JSON files, designed for seamless integration into databases, analytical platforms, and machine learning pipelines.
• Accessibility: Published and available immediately for acquisition.

Richness of Detail (22 Comprehensive Fields):

The true analytical power of this dataset stems from its 22 granular data points per job listing, offering a multi-faceted view of each employment opportunity:

1. Core Job & Role Information:

   • id: A unique, immutable identifier for each job posting.
   • title: The specific job role (e.g., "Software Engineer," "Marketing Manager").
   • description: A condensed summary of the role, responsibilities, and key requirements.
   • raw_description: The complete, unformatted HTML/text content of the original job posting – invaluable for advanced Natural Language Processing (NLP) and deeper textual analysis.
   • posted_at: The precise date and time the job was published, enabling trend analysis over daily or weekly periods.
   • employment_type: Clarifies the nature of the role (e.g., "Full-time," "Part-time," "Contract," "Temporary").
   • url: The direct link back to the original job posting on CareerBuilder, allowing for contextual validation or deeper exploration.

2. Compensation & Professional Experience:

   • salary: Numeric ranges or discrete values indicating the compensation offered, crucial for salary benchmarking and compensation strategy.
   • experience: Specifies the level of professional experience required (e.g., "Entry-level," "Mid-senior level," "Executive").

3. Organizational & Sector Context:

   • company: The name of the employer, essential for company-specific analysis, competitive intelligence, and brand reputation studies.
   • domain: Categorizes the job within broader industry sectors or functional areas, facilitating industry-specific talent analysis.

4. Skills & Educational Requirements:

   • skills: A rich collection of keywords, phrases, or structured tags representing the specific technical, soft, or industry-specific skills sought by employers. Ideal for identifying skill gaps and emerging skill demands.
   • education: Outlines the minimum or preferred educational qualifications (e.g., "Bachelor's Degree," "Master's Degree," "High School Diploma").

5. Precise Geographic & Location Data:

   • country: Specifies the country (United States for this dataset).
   • region: The state or province where the job is located.
   • locality: The city or town of the job.
   • address: The specific street address of the workplace (if provided), enabling highly localized analysis.
   • location: A more generalized location string often provided by the job board.
   • postalcode: The exact postal code, allowing for granular geographic clustering and demographic overlay.
   • latitude & longitude: Geospatial coordinates for precise mapping, heatmaps, and proximity analysis.

6. Crawling Metadata:

   • crawled_at: The exact timestamp when each individual record was acquired, vital for understanding data freshness and chronological analysis of changes.

Expanded Use Cases & Analytical Applications:

This comprehensive dataset empowers a wide array of research and commercial applications:

• Deep Labor Market Trend Analysis:

  • Identify the most in-demand job titles, skills, and educational backgrounds across different US regions and industries in 2021.
  • Analyze month-over-month or quarter-over-quarter hiring trends to understand recovery patterns or shifts in specific sectors post-pandemic.
  • Spot emerging job roles or skill combinations that gained prominence during the dataset's period.
  • Assess the volume of remote vs. in-person job postings and their distribution.

• Strategic Talent Acquisition & HR Analytics:

  • Benchmark job requirements, salary ranges, and desired experience levels against market averages for specific roles.
  • Optimize job descriptions by identifying common keywords and phrases used by top employers for similar positions.
  • Understand the competitive landscape for talent in specific geographic areas or specialized skill sets.
  • Develop data-driven recruitment strategies by identifying where and how competitors are hiring.

• Compensation & Benefits Research:

  • Conduct detailed salary analysis broken down by job title, industry, location (state, city, even postal code), experience level, and required skills.
  • Identify potential salary premiums or discrepancies for niche skills or hard-to-fill roles.
  • Support robust compensation planning and negotiation strategies.

• Educational & Workforce Development Planning:

  • Universities and vocational schools can align curriculum with real-world employer demand by analyzing required skills and education fields.
  • Government agencies can identify areas for workforce retraining or development programs based on skill gaps revealed in job postings.
  • Career counselors can advise job seekers on in-demand skills and promising career paths.

• Economic Research & Forecasting:

  • Economists can use the volume and nature of job postings as a leading indicator for economic activity and regional growth.
  • Analyze the impact of economic policies or global events on specific industries' hiring patterns.
  • Study labor mobility and migration patterns based on job locations.

• Competitive Intelligence for Businesses:

  <li

This statistic depicts the median annual family income in Canada in 2021, distinguished by province. In 2021, the median annual family income in Alberta was 106,960 Canadian dollars.

Average weekly earnings by North American Industry Classification System (NAICS), type of employee and overtime status, last 5 years.

About this dataset

Context

The dataset presents the median household income across different racial categories in New Canada town. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.

Key observations

Based on our analysis of the distribution of New Canada town population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 77.53% of the total residents in New Canada town. Notably, the median household income for White households is $74,988. Interestingly, White is both the largest group and the one with the highest median household income, which stands at $74,988.

https://i.neilsberg.com/ch/new-canada-me-median-household-income-by-race.jpeg" alt="New Canada town median household income diversity across racial categories">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 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 of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in New Canada town.
• Median household income: Median household income, adjusting for inflation, presented in 2022-inflation-adjusted dollars

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 New Canada town median household income by race. You can refer the same here

Indexes of real expenditure per capita in the United States relative to those in Canada for categories of gross domestic income (GDI), Canada=100, on an International Comparison Project Classification (ICP) basis.

Families of tax filers; Single-earner and dual-earner census families by number of children (final T1 Family File; T1FF).

This dataset provides values for HOUSEHOLDS DEBT TO INCOME reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.