Summary: Exploring Oregon's Heritage Resources in Latinx CommunitiesStorymap metadata page: URL forthcoming Possible K-12 Next Generation Science standards addressed:Grade level(s) 5: Standard 5-ESS3-1 - Earth and Human Activity - Obtain and combine information about ways individual communities use science ideas to protect the Earth’s resources and environment.Grade level(s) 9-12: Standard HS-LS2-1 - Ecosystems: Interactions, Energy, and Dynamics - Use mathematical and/or computational representations to support explanations of factors that affect carrying capacity of ecosystems at different scalesMost frequently used words:historiccommunitiesoregonlatinxcommunityApproximate Flesch-Kincaid reading grade level: 10.2. The FK reading grade level should be considered carefully against the grade level(s) in the NGSS content standards above.

This dataset tracks annual diversity score from 2013 to 2023 for Oregon 4k vs. Wisconsin and Oregon School District

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 Oregon. The dataset can be utilized to gain insights into gender-based income distribution within the Oregon population, aiding in data analysis and decision-making..

Key observations

• Employment patterns: Within Oregon, among individuals aged 15 years and older with income, there were 1.60 million men and 1.55 million women in the workforce. Among them, 807.21 thousand men were engaged in full-time, year-round employment, while 593.67 thousand women were in full-time, year-round roles.
• Annual income under $24,999: Of the male population working full-time, 6.21% fell within the income range of under $24,999, while 8.15% of the female population working full-time was represented in the same income bracket.
• Annual income above $100,000: 30.22% of men in full-time roles earned incomes exceeding $100,000, while 19.73% 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 Oregon median household income by race. You can refer the same here

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 Oregon. The dataset can be utilized to gain insights into gender-based income distribution within the Oregon population, aiding in data analysis and decision-making..

Key observations

• Employment patterns: Within Oregon, among individuals aged 15 years and older with income, there were 4,018 men and 4,082 women in the workforce. Among them, 2,963 men were engaged in full-time, year-round employment, while 1,873 women were in full-time, year-round roles.
• Annual income under $24,999: Of the male population working full-time, 1.96% fell within the income range of under $24,999, while 1.98% of the female population working full-time was represented in the same income bracket.
• Annual income above $100,000: 42.49% of men in full-time roles earned incomes exceeding $100,000, while 20.82% 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 Oregon median household income by race. You can refer the same here

This dataset tracks annual diversity score from 2022 to 2023 for Oregon Connections Academy vs. Oregon and Prairie City SD 4 School District

This dataset tracks annual diversity score from 2013 to 2023 for Oregon Trail Academy vs. Oregon and Oregon Trail SD 46 School District

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 Oregon town. The dataset can be utilized to gain insights into gender-based income distribution within the Oregon town population, aiding in data analysis and decision-making..

Key observations

• Employment patterns: Within Oregon town, among individuals aged 15 years and older with income, there were 1,152 men and 1,072 women in the workforce. Among them, 749 men were engaged in full-time, year-round employment, while 468 women were in full-time, year-round roles.
• Annual income under $24,999: Of the male population working full-time, none fell within the income range of under $24,999, while 1.28% of the female population working full-time was represented in the same income bracket.
• Annual income above $100,000: 31.38% of men in full-time roles earned incomes exceeding $100,000, while 36.54% 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 Oregon town median household income by race. You can refer the same here

About this dataset

Context

The dataset presents the median household income across different racial categories in Oregon. 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 Oregon population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 80.69% of the total residents in Oregon. Notably, the median household income for White households is $76,846. Interestingly, despite the White population being the most populous, it is worth noting that Asian households actually reports the highest median household income, with a median income of $104,214. This reveals that, while Whites may be the most numerous in Oregon, Asian households experience greater economic prosperity in terms of median household income.

https://i.neilsberg.com/ch/oregon-median-household-income-by-race.jpeg" alt="Oregon 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) 2022 1-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 Oregon.
• 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 Oregon median household income by race. You can refer the same here

This dataset tracks annual diversity score from 1991 to 2023 for Oregon City Senior High School vs. Oregon and Oregon City SD 62 School District

This dataset tracks annual diversity score from 2019 to 2023 for Oregon Family School vs. Oregon and Harney County SD 4 School District

This dataset tracks annual diversity score from 2004 to 2023 for Imnaha Elementary School vs. Oregon and Joseph SD 6 School District

This dataset tracks annual diversity score from 1991 to 2023 for Oregon School District vs. Wisconsin

This dataset tracks annual diversity score from 2013 to 2023 for Roosevelt High School vs. Oregon and Portland SD 1j School District

This dataset tracks annual diversity score from 1991 to 2023 for Parkrose High School vs. Oregon and Parkrose SD 3 School District

This dataset tracks annual diversity score from 2016 to 2023 for Insight School Of Oregon Painted Hills vs. Oregon and Mitchell SD 55 School District

This dataset tracks annual diversity score from 2007 to 2023 for Oregon Connections Academy vs. Oregon and Scio School District 95

This dataset tracks annual diversity score from 2013 to 2023 for Oregon Virtual Education - West vs. Oregon and Gaston School District 511j

This dataset tracks annual diversity score from 1998 to 2023 for Oregon Department Of Education School District vs. Oregon

This dataset tracks annual diversity score from 1993 to 2023 for Oregon Jr/sr High School vs. Illinois and Oregon CUSD 220 School District

This dataset tracks annual diversity score from 2009 to 2023 for Oregon School For The Deaf vs. Oregon and Oregon Department Of Education School District