Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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Context
This list ranks the 1 cities in the San Francisco County, CA by Non-Hispanic Black or African American population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:
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/.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the population of San Francisco by race. It includes the population of San Francisco across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of San Francisco across relevant racial categories.
Key observations
The percent distribution of San Francisco population by race (across all racial categories recognized by the U.S. Census Bureau): 40.49% are white, 5.09% are Black or African American, 0.66% are American Indian and Alaska Native, 34.97% are Asian, 0.38% are Native Hawaiian and other Pacific Islander, 7.75% are some other race and 10.66% are multiracial.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-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 San Francisco Population by Race & Ethnicity. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the Non-Hispanic population of San Francisco County by race. It includes the distribution of the Non-Hispanic population of San Francisco County across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of San Francisco County across relevant racial categories.
Key observations
Of the Non-Hispanic population in San Francisco County, the largest racial group is White alone with a population of 313,559 (44.60% of the total Non-Hispanic population).
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-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 San Francisco County Population by Race & Ethnicity. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the population of San Francisco township by race. It includes the population of San Francisco township across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of San Francisco township across relevant racial categories.
Key observations
The percent distribution of San Francisco township population by race (across all racial categories recognized by the U.S. Census Bureau): 89.67% are white, 1.36% are Black or African American, 0.52% are Asian and 8.46% are multiracial.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-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 San Francisco township Population by Race & Ethnicity. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the median household income across different racial categories in San Francisco township. 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 San Francisco township population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 89.67% of the total residents in San Francisco township. Notably, the median household income for White households is $129,375. Interestingly, White is both the largest group and the one with the highest median household income, which stands at $129,375.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-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 San Francisco township median household income by race. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the South San Francisco Hispanic or Latino population. It includes the distribution of the Hispanic or Latino population, of South San Francisco, by their ancestries, as identified by the Census Bureau. The dataset can be utilized to understand the origin of the Hispanic or Latino population of South San Francisco.
Key observations
Among the Hispanic population in South San Francisco, regardless of the race, the largest group is of Mexican origin, with a population of 11,435 (57.90% of the total Hispanic population).
https://i.neilsberg.com/ch/south-san-francisco-ca-population-by-race-and-ethnicity.jpeg" alt="South San Francisco Non-Hispanic population by race">
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Origin for Hispanic or Latino population 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 South San Francisco Population by Race & Ethnicity. You can refer the same here
ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
License information was derived automatically
A. SUMMARY This dataset includes San Francisco COVID-19 tests by race/ethnicity and by date. This dataset represents the daily count of tests collected, and the breakdown of test results (positive, negative, or indeterminate). Tests in this dataset include all those collected from persons who listed San Francisco as their home address at the time of testing. It also includes tests that were collected by San Francisco providers for persons who were missing a locating address. This dataset does not include tests for residents listing a locating address outside of San Francisco, even if they were tested in San Francisco.
The data were de-duplicated by individual and date, so if a person gets tested multiple times on different dates, all tests will be included in this dataset (on the day each test was collected). If a person tested multiple times on the same date, only one test is included from that date. When there are multiple tests on the same date, a positive result, if one exists, will always be selected as the record for the person. If a PCR and antigen test are taken on the same day, the PCR test will supersede. If a person tests multiple times on the same day and the results are all the same (e.g. all negative or all positive) then the first test done is selected as the record for the person.
The total number of positive test results is not equal to the total number of COVID-19 cases in San Francisco.
When a person gets tested for COVID-19, they may be asked to report information about themselves. One piece of information that might be requested is a person's race and ethnicity. These data are often incomplete in the laboratory and provider reports of the test results sent to the health department. The data can be missing or incomplete for several possible reasons:
• The person was not asked about their race and ethnicity.
• The person was asked, but refused to answer.
• The person answered, but the testing provider did not include the person's answers in the reports.
• The testing provider reported the person's answers in a format that could not be used by the health department.
For any of these reasons, a person's race/ethnicity will be recorded in the dataset as “Unknown.”
B. NOTE ON RACE/ETHNICITY The different values for Race/Ethnicity in this dataset are "Asian;" "Black or African American;" "Hispanic or Latino/a, all races;" "American Indian or Alaska Native;" "Native Hawaiian or Other Pacific Islander;" "White;" "Multi-racial;" "Other;" and “Unknown."
The Race/Ethnicity categorization increases data clarity by emulating the methodology used by the U.S. Census in the American Community Survey. Specifically, persons who identify as "Asian," "Black or African American," "American Indian or Alaska Native," "Native Hawaiian or Other Pacific Islander," "White," "Multi-racial," or "Other" do NOT include any person who identified as Hispanic/Latino at any time in their testing reports that either (1) identified them as SF residents or (2) as someone who tested without a locating address by an SF provider. All persons across all races who identify as Hispanic/Latino are recorded as “"Hispanic or Latino/a, all races." This categorization increases data accuracy by correcting the way “Other” persons were counted. Previously, when a person reported “Other” for Race/Ethnicity, they would be recorded “Unknown.” Under the new categorization, they are counted as “Other” and are distinct from “Unknown.”
If a person records their race/ethnicity as “Asian,” “Black or African American,” “American Indian or Alaska Native,” “Native Hawaiian or Other Pacific Islander,” “White,” or “Other” for their first COVID-19 test, then this data will not change—even if a different race/ethnicity is reported for this person for any future COVID-19 test. There are two exceptions to this rule. The first exception is if a person’s race/ethnicity value is reported as “Unknown” on their first test and then on a subsequent test they report “Asian;” "Black or African American;" "Hispanic or Latino/a, all races;" "American Indian or Alaska Native;" "Native Hawaiian or Other Pacific Islander;" or "White”, then this subsequent reported race/ethnicity will overwrite the previous recording of “Unknown”. If a person has only ever selected “Unknown” as their race/ethnicity, then it will be recorded as “Unknown.” This change provides more specific and actionable data on who is tested in San Francisco.
The second exception is if a person ever marks “Hispanic or Latino/a, all races” for race/ethnicity then this choice will always overwrite any previous or future response. This is because it is an overarching category that can include any and all other races and is mutually exclusive with the other responses.
A person's race/ethnicity will be recorded as “Multi-racial” if they select two or more values among the following choices: “Asian,” “Black or African American,” “American Indian or Alaska Native,” “Native Hawaiian or Other Pacific Islander,” “White,” or “Other.” If a person selects a combination of two or more race/ethnicity answers that includes “Hispanic or Latino/a, all races” then they will still be recorded as “Hispanic or Latino/a, all races”—not as “Multi-racial.”
C. HOW THE DATASET IS CREATED COVID-19 laboratory test data is based on electronic laboratory test reports. Deduplication, quality assurance measures and other data verification processes maximize accuracy of laboratory test information.
D. UPDATE PROCESS Updates automatically at 5:00AM Pacific Time each day. Redundant runs are scheduled at 7:00AM and 9:00AM in case of pipeline failure.
E. HOW TO USE THIS DATASET San Francisco population estimates for race/ethnicity can be found in a view based on the San Francisco Population and Demographic Census dataset. These population estimates are from the 2016-2020 5-year American Community Survey (ACS).
Due to the high degree of variation in the time needed to complete tests by different labs there is a delay in this reporting. On March 24, 2020 the Health Officer ordered all labs in the City to report complete COVID-19 testing information to the local and state health departments.
In order to track trends over time, a user can analyze this data by sorting or filtering by the "specimen_collection_date" field.
Calculating Percent Positivity: The positivity rate is the percentage of tests that return a positive result for COVID-19 (positive tests divided by the sum of positive and negative tests). Indeterminate results, which could not conclusively determine whether COVID-19 virus was present, are not included in the calculation of percent positive. When there are fewer than 20 positives tests for a given race/ethnicity and time period, the positivity rate is not calculated for the public tracker because rates of small test counts are less reliable.
Calculating Testing Rates: To calculate the testing rate per 10,000 residents, divide the total number of tests collected (positive, negative, and indeterminate results) for the specified race/ethnicity by the total number of residents who identify as that race/ethnicity (according to the 2016-2020 American Community Survey (ACS) population estimate), then multiply by 10,000. When there are fewer than 20 total tests for a given race/ethnicity and time period, the testing rate is not calculated for the public tracker because rates of small test counts are less reliable.
Read more about how this data is updated and validated daily: https://sf.gov/information/covid-19-data-questions
F. CHANGE LOG
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the Non-Hispanic population of San Francisco township by race. It includes the distribution of the Non-Hispanic population of San Francisco township across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of San Francisco township across relevant racial categories.
Key observations
Of the Non-Hispanic population in San Francisco township, the largest racial group is White alone with a population of 855 (93.65% of the total Non-Hispanic population).
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-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 San Francisco township Population by Race & Ethnicity. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the median household incomes over the past decade across various racial categories identified by the U.S. Census Bureau in San Francisco township. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. It also showcases the annual income trends, between 2013 and 2023, providing insights into the economic shifts within diverse racial communities.The dataset can be utilized to gain insights into income disparities and variations across racial categories, 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.
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 San Francisco township median household income by race. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the San Francisco township Hispanic or Latino population. It includes the distribution of the Hispanic or Latino population, of San Francisco township, by their ancestries, as identified by the Census Bureau. The dataset can be utilized to understand the origin of the Hispanic or Latino population of San Francisco township.
Key observations
Among the Hispanic population in San Francisco township, regardless of the race, the largest group is of other Hispanic or Latino origin, with a population of 14 (77.78% of the total Hispanic population).
https://i.neilsberg.com/ch/san-francisco-township-mn-population-by-race-and-ethnicity.jpeg" alt="San Francisco township Non-Hispanic population by race">
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Origin for Hispanic or Latino population 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 San Francisco township Population by Race & Ethnicity. You can refer the same here
ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
License information was derived automatically
Note: As of March 2022, the race/ethnicity label changed from Native American to American Indian or Alaska Native to align with the Census.
Note: As of April 16, 2021, this dataset will update daily with a five-day data lag.
Note: As of February 2022, the way race/ethnicity is categorized has been changed. See Section B for additional information.
A. SUMMARY This dataset includes San Francisco COVID-19 tests by race/ethnicity and by date. This dataset represents the daily count of tests collected, and the breakdown of test results (positive, negative, or indeterminate). Tests in this dataset include all those collected from persons who listed San Francisco as their home address at the time of testing. It also includes tests that were collected by San Francisco providers for persons who were missing a locating address. This dataset does not include tests for residents listing a locating address outside of San Francisco, even if they were tested in San Francisco.
The data were de-duplicated by individual and date, so if a person gets tested multiple times on different dates, all tests will be included in this dataset (on the day each test was collected). If a person tested multiple times on the same date, only one test is included from that date. When there are multiple tests on the same date, a positive result, if one exists, will always be selected as the record for the person. If a PCR and antigen test are taken on the same day, the PCR test will supersede. If a person tests multiple times on the same day and the results are all the same (e.g. all negative or all positive) then the first test done is selected as the record for the person.
The total number of positive test results is not equal to the total number of COVID-19 cases in San Francisco. Each positive test result is investigated by the health department. While the city tries to only report on tests for San Francisco residents (or tests in San Francisco for those with no locating address listed), some test results purported to be for San Francisco residents are actually for people living outside the city. This can be discovered during a case investigation or data quality assurance. In such an instance, the test would be counted as a positive test in the SF data but would not be counted as a COVID-19 case in San Francisco. If a person tests positive for COVID-19 on different dates, they would be included each of those times in the testing data but only one case. To track the number of cases by race/ethnicity, see this dashboard: https://sf.gov/data/covid-19-population-characteristics#race-or-ethnicity-
When a person gets tested for COVID-19, they may be asked to report information about themselves. One piece of information that might be requested is a person's race and ethnicity. These data are often incomplete in the laboratory and provider reports of the test results sent to the health department. The data can be missing or incomplete for several possible reasons:
• The person was not asked about their race and ethnicity.
• The person was asked, but refused to answer.
• The person answered, but the testing provider did not include the person's answers in the reports.
• The testing provider reported the person's answers in a format that could not be used by the health department.
For any of these reasons, a person's race/ethnicity will be recorded in the dataset as “Unknown.”
B. NOTE ON RACE/ETHNICITY The different values for Race/Ethnicity in this dataset are "Asian;" "Black or African American;" "Hispanic or Latino/a, all races;" "American Indian or Alaska Native;" "Native Hawaiian or Other Pacific Islander;" "White;" "Multi-racial;" "Other;" and “Unknown."
On February 10, 2022, the method for which race/ethnicity is categorized was updated for the sake of data accuracy, clarity, and stability. The new categorization increases data clarity by emulating the methodology used by the U.S. Census in the
The dataset includes three separate excel spreadsheets which provides waterbird (and predator) observations within individual survey units during the May 2019 breeding waterbird survey of south San Francisco Bay (2019WaterbirdSurveyFullData.xlsx), the total number of American avocets, black-necked stilts, and Forster's terns within each pond unit surveyed during the May 2019 survey (2019WaterbirdSurveyPondModel.xlsx), and the annual total number of nests for American avocets, black-necked stilts, and Forster's terns in south San Francisco between 2005 and 2019 (SouthBayWaterbirdNests2005-2019.xlsx).
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset tracks annual black student percentage from 1991 to 2023 for San Francisco Unified School District vs. California
This dataset contains counts of live births for California counties based on information entered on birth certificates. Final counts are derived from static data and include out of state births to California residents, whereas provisional counts are derived from incomplete and dynamic data. Provisional counts are based on the records available when the data was retrieved and may not represent all births that occurred during the time period.
The final data tables include both births that occurred in California regardless of the place of residence (by occurrence) and births to California residents (by residence), whereas the provisional data table only includes births that occurred in California regardless of the place of residence (by occurrence). The data are reported as totals, as well as stratified by parent giving birth's age, parent giving birth's race-ethnicity, and birth place type. See temporal coverage for more information on which strata are available for which years.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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This dataset provides census-block level estimates of outdoor air pollutant concentrations averaged over a 32-month period spanning from May 2015 through December 2017. Measurements were taken using mobile monitoring along every street of 13 cities, towns, and urban districts (93 km2) distributed through four counties of the San Francisco Bay Area, comprising over 2,100 hours of sampling. Two Google Street View cars equipped with the Aclima mobile platform repeatedly measured city block air quality, providing estimates of outdoor air pollution for a year-2010 population of ~450,000 individuals. This dataset includes measurements of four pollutants:NO (units: ppb)NO2 (units:ppb)BC (black carbon, units: µg/m3)UFP (ultrafine particle count, units: #x103/cm3)For the purposes of quality control, the set includes:a count of the unique days each block was visited while each of the monitoring instruments were operational (uniqueDays_xx, with xx representing the relevant pollutant), the total visits to the census block (visits_xx), and the cumulative sampling time in seconds (samplingTime_xx).The dataset includes the population data from the US census (TotalPop.x) and populations divided by census-based self-identified race and ethnicity. The categories include:-Hispanic or Latino (HispLat)-Not Hispanic or Latino: White alone or in combination with one or more other races (WhiteNH)-Not Hispanic or Latino: Black or African American alone or in combination with one or more other races (BlackNH)-Not Hispanic or Latino: Asian alone or in combination with one or more other races (AsianNH)-Not Hispanic or Latino: American Indian and Alaska Native alone or in combination with one or more other races (NativeNH)-Not Hispanic or Latino: Native Hawaiian and Other Pacific Islander alone or in combination with one or more other races (PacIsl)-Not Hispanic or Latino: Some Other Race alone or in combination with one or more other races (OtherNH)Consistent with Chambliss et al. 2021, there is a grouping of "OtherRace" which is the sum of the last three categories.Additional methodological details can be found in Chambliss et al. 2021 (https://chemrxiv.org/engage/chemrxiv/article-details/60f731b1880443777ae27104).Data are provided as a table that may be joined to GIS data from the US census using the unique "GISJOIN" identifier matching 2010 census block geographic units. Such GIS data is available online from several sources, including https://www.nhgis.org/
Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
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This data set includes the locations of all known seabird colonies along the coast of British Columbia, and provides a compilation of the population estimates of seabirds breeding at those colonies since 1980, and historical estimates prior to 1980 for some colonies. It does not include an estimate of the numbers of juvenile birds or non-breeders in the population. The rationale for developing this inventory was the recognized need for a product that could assist with: coastal zone and conservation area planning; emergency response to environmental emergencies and identifying areas of potential interactions between seabirds and anthropogenic activities. In addition, the data used to develop the document provides a baseline to compare with future seabird population estimates in order to measure the impacts of shifts in composition, abundance and/or distribution of prey, and climatic and oceanographic changes. The database is not a substitute for on-site surveys usually required for environmental assessment. Here we present data on the breeding colony population estimates of the 15 species of seabirds (including two storm petrels, three cormorants, one gull and nine alcids) and one shorebird (Black Oystercatcher Haematopus bachmani) that breed on the coast of British Columbia. Over 5.5 million colonial birds are currently estimated to nest at 627 sites, based on surveys primarily conducted in the 1980’s. Five species (Cassin's Auklets Ptychoramphus aleuticus, Fork-tailed Storm-petrels Oceanodroma furcata, Leach's Storm-petrels Oceanodroma leucorhoa, Rhinoceros Auklets Cerorhinca monocerata, and Ancient Murrelets Synthliboramphus antiquus) comprise the vast majority of that population, although Glaucous-winged Gulls (Larus glaucescens) and Pigeon Guillemots (Cepphus columba) nest at the most sites. Marbled Murrelets (Brachyramphus marmoratus), which nest on the mossy limbs of mature and old-growth trees within the coastal forests, are not included in this database, due to their dispersed nesting habit. The population estimates presented in this database are compiled from the results of several surveys. Many of the seabird breeding colonies in British Columbia have been known for more than 50 years, but because of the remoteness of the sites, visits to them have been rare. The majority of the data are the results of a comprehensive inventory of colonial nesting seabirds along the British Columbia coastline conducted between 1980 and 1989 by the Canadian Wildlife Service of Environment and Climate Change Canada. The goal of that program was to establish baseline estimates of breeding seabird populations in BC using standardized survey techniques to allow future comparisons and monitoring of those populations. A few colonies on small remote islands were not visited during that survey. Therefore, for some colonies the most current population estimates are from the first complete survey of the BC coastline, carried out by the Royal British Columbia Museum in the mid 1970’s. That survey identified colony sites and provided rough assessments of the population sizes of breeding seabirds. Since 1989, surveys have been conducted on some alcid, cormorant and gull colonies along the BC coast, and results have been included in the dataset (data entry ongoing). As well as data from Canadian Wildlife Service surveys, we have attempted to obtain recent data from all other sources including Parks Canada, the Ministry of Forests, Lands, Natural Resource Operations and Rural Development, the Bamfield Marine Station and the Laskeek Bay Conservation Society. Since 2000, inventories of nesting Black Oystercatchers have been conducted in some regions of the coast by Parks Canada and partners (Gulf Islands National Park Reserve, Pacific Rim National Park Reserve, and Gwaii Haanas National Park Reserve) and results have been included in the dataset (data entry ongoing). A long time series of nesting Black Oystercatcher data collected by Laskeek Bay Conservation Society in the Laskeek Bay area of the East Coast of Moresby Island has also been included in this dataset.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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Context
This list ranks the 1 cities in the San Francisco County, CA by Non-Hispanic Black or African American population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:
Variables / Data Columns
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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/.