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TwitterWe study the effect of physician workforce diversity on the demand for preventive care among African American men. In an experiment in Oakland, California, we randomize black men to black or non-black male medical doctors. We use a two-stage design, measuring decisions before (pre-consultation) and after (post-consultation) meeting their assigned doctor. Subjects select a similar number of preventives in the pre-consultation stage, but are much more likely to select every preventive service, particularly invasive services, once meeting with a racially concordant doctor. Our findings suggest black doctors could reduce the black-white male gap in cardiovascular mortality by 19 percent.
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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 Oakland. The dataset can be utilized to gain insights into gender-based income distribution within the Oakland population, aiding in data analysis and decision-making..
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income brackets:
Variables / Data Columns
Employment type classifications include:
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.
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/.
This dataset is a part of the main dataset for Oakland median household income by race. You can refer the same here
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This dataset tracks annual diversity score from 1991 to 2023 for Oakland High School vs. California and Oakland Unified School District
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This dataset tracks annual diversity score from 2019 to 2023 for Oakland School For The Arts vs. California and Oakland School For The Arts School District
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Context
The dataset presents the median household income across different racial categories in Oakland. 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 Oakland population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 33.45% of the total residents in Oakland. Notably, the median household income for White households is $157,169. Interestingly, White is both the largest group and the one with the highest median household income, which stands at $157,169.
https://i.neilsberg.com/ch/oakland-ca-median-household-income-by-race.jpeg" alt="Oakland median household income diversity across racial categories">
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2022 1-Year Estimates.
Racial categories include:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Oakland median household income by race. You can refer the same here
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset tracks annual diversity score from 2019 to 2023 for Oakland Unity High School District vs. California
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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This dataset tracks annual diversity score from 2009 to 2023 for West Oakland Middle School vs. California and Oakland Unified School District
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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This dataset tracks annual diversity score from 2005 to 2023 for East Oakland Leadership Academy vs. California and Oakland Unified School District
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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This dataset tracks annual diversity score from 2019 to 2023 for Oakland Charter High School vs. California and Oakland Charter High School District
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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This dataset tracks annual diversity score from 2019 to 2023 for Lps Oakland R & D Campus vs. California and Lps Oakland R & D Campus School District
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TwitterComprehensive demographic dataset for Central Oakland, Pittsburgh, PA, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.
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This dataset tracks annual diversity score from 1991 to 2023 for Oakland High School vs. Oregon and Oakland School District 1
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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This dataset tracks annual diversity score from 1998 to 2023 for Oakland High School vs. Illinois and Oakland Community Unit School District 5
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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This dataset tracks annual diversity score from 1991 to 2023 for Oakland Technical High School vs. California and Oakland Unified School District
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset tracks annual diversity score from 1996 to 2023 for Oakland Middle School vs. Missouri and Columbia 93 School District
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This dataset tracks annual diversity score from 2013 to 2023 for W-a-y Oakland vs. Michigan and Oakland Schools
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This dataset tracks annual diversity score from 1994 to 2023 for Oakland Elementary School vs. Illinois and Antioch Community Consolidated School District 34
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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This dataset tracks annual diversity score from 2014 to 2023 for Oakland County Academy Of Media Technology vs. Michigan and Oakland County Academy Of Media & Technology School District
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset tracks annual diversity score from 1990 to 2023 for Oakland High School vs. Tennessee and Rutherford County School District
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset tracks annual diversity score from 2019 to 2023 for North Oakland Community Charter vs. California and North Oakland Community Charter School District
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TwitterWe study the effect of physician workforce diversity on the demand for preventive care among African American men. In an experiment in Oakland, California, we randomize black men to black or non-black male medical doctors. We use a two-stage design, measuring decisions before (pre-consultation) and after (post-consultation) meeting their assigned doctor. Subjects select a similar number of preventives in the pre-consultation stage, but are much more likely to select every preventive service, particularly invasive services, once meeting with a racially concordant doctor. Our findings suggest black doctors could reduce the black-white male gap in cardiovascular mortality by 19 percent.