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3 Results
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A. SUMMARY
The Department of Public Health and the Mayor’s Office of Housing and Community Development, with support from the Planning Department, created these 41 neighborhoods by grouping 2010 Census tracts, using common real estate and residents’ definitions for the purpose of providing consistency in the analysis and reporting of socio-economic, demographic, and environmental data, and data on City-funded programs and services. These neighborhoods are not codified in Planning Code nor Administrative Code, although this map is referenced in Planning Code Section 415 as the “American Community Survey Neighborhood Profile Boundaries Map.
The Department of Public Health and the Mayor’s Office of Housing and Community Development, with support from the Planning Department, created these 41 neighborhoods by grouping 2010 Census tracts, using common real estate and residents’ definitions for the purpose of providing consistency in the analysis and reporting of socio-economic, demographic, and environmental data, and data on City-funded programs and services. These neighborhoods are not codified in Planning Code nor Administrative Code, although this map is referenced in Planning Code Section 415 as the “American Community Survey Neighborhood Profile Boundaries Map.
Note: These are NOT statistical boundaries as they are not controlled for population size. This is also NOT an official map of neighborhood boundaries in SF but an aggregation of Census tracts and should be used in conjunction with other spatial boundaries for decision making.
B. HOW THE DATASET IS CREATED
This dataset is produced by assigning Census tracts to neighborhoods based on existing neighborhood definitions used by Planning and MOHCD. A qualitative assessment is made to identify the appropriate neighborhood for a given tract based on understanding of population distribution and significant landmarks. Once all tracts have been assigned a neighborhood, the tracts are dissolved to produce this dataset, Analysis Neighborhoods.
This dataset is produced by assigning Census tracts to neighborhoods based on existing neighborhood definitions used by Planning and MOHCD. A qualitative assessment is made to identify the appropriate neighborhood for a given tract based on understanding of population distribution and significant landmarks. Once all tracts have been assigned a neighborhood, the tracts are dissolved to produce this dataset, Analysis Neighborhoods.
C. UPDATE PROCESS
This dataset is static. Changes to the analysis neighborhood boundaries will be evaluated as needed by the Analysis Neighborhood working group led by DataSF and the Planning department and includes staff from various other city departments. Contact us
for any questions.
This dataset is static. Changes to the analysis neighborhood boundaries will be evaluated as needed by the Analysis Neighborhood working group led by DataSF and the Planning department and includes staff from various other city departments. Contact us
for any questions.
D. HOW TO USE THIS DATASET
Downloading this dataset and opening it in Excel may cause some of the data values to be lost or not display properly (particularly the Analysis Neighborhood column). For a simple list of Analysis Neighborhoods without geographic coordinates, click here: https://data.sfgov.org/resource/xfcw-9evu.csv?$select=nhood
Downloading this dataset and opening it in Excel may cause some of the data values to be lost or not display properly (particularly the Analysis Neighborhood column). For a simple list of Analysis Neighborhoods without geographic coordinates, click here: https://data.sfgov.org/resource/xfcw-9evu.csv?$select=nhood
E. RELATED DATASETS
2020 Census tracts assigned a neighborhood
2010 Census tracts assigned a neighborhood
2020 Census tracts assigned a neighborhood
2010 Census tracts assigned a neighborhood
Updated
December 5 2022
Views
30,563
The Department of Public Health and the Mayor’s Office of Housing and Community Development, with support from the Planning Department, created 41 neighborhoods by grouping 2010 Census tracts, using common real estate and residents’ definitions for the purpose of providing consistency in the analysis and reporting of socio-economic, demographic, and environmental data, and data on City-funded programs and services. They are not codified in Planning Code nor Administrative Code.
This dataset is produced by assigning Census tracts to neighborhoods based on existing neighborhood definitions used by Planning and MOHCD. A qualitative assessment is made to identify the appropriate neighborhood for a given tract based on an understanding of population distribution and significant landmarks. Once all tracts have been assigned a neighborhood, the tracts are combined to produce Analysis Neighborhoods which is available at https://data.sfgov.org/d/p5b7-5n3h
Updated
September 6 2019
Views
8,110
These geographic designations were created to define geographic areas within San Francisco that have a higher density of vulnerable populations. These geographic designations will be used for the Health Care Services Master Plan and DPH's Community Health Needs Assessment.
aov_fin - 1 = YES
aov_fin - 0 = NO
aov_fin - 0 = NO
AOV's were defined using 2012-2016 ACS data at the census tract level and the following criteria:
1) Top 1/3rd for < 200% poverty or < 400% poverty & top 1/3rd for persons of color OR
2) Top 1/3rd for < 200% poverty or < 400% poverty & top 1/3rd for youth or seniors (65+) OR
3) Top 1/3rd for < 200% poverty or < 400% poverty & top 1/3rd for 2 other categories (unemployment, high school or less, limited English proficiency persons, linguistically isolated households, or disability)
2) Top 1/3rd for < 200% poverty or < 400% poverty & top 1/3rd for youth or seniors (65+) OR
3) Top 1/3rd for < 200% poverty or < 400% poverty & top 1/3rd for 2 other categories (unemployment, high school or less, limited English proficiency persons, linguistically isolated households, or disability)
Tracts that had unstable data for an indicator were automatically given zero credit for that indicator. That is why two language variables are included in the bonus group, because there tend to be a high number of tracts with unstable data for language variables.
Updated
September 6 2019
Views
4,156
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