Draft dataset for Bay Area Census website prototype. Includes census 2020 population breakdown by age, sex and race.

Racial diversity is measured by a diversity index that is calculated using United States Census racial and ethnic population characteristics from the PL-94 data file. The diversity index is a quantitative measure of the distribution of the proportion of five major ethnic populations (non-Hispanic White, non-Hispanic Black, Asian and Pacific Islander, Hispanic, and Two or more races). The index ranges from 0 (low diversity meaning only one group is present) to 1 (meaning an equal proportion of all five groups is present). The diversity score for the United States in 2010 is 0.60. The diversity score for the San Francisco Bay Region is 0.84. Within the region, Solano (0.89) and Alameda (0.90) Counties are the most diverse and the remaining North Bay (0.55 - 0.64) Counties are the least diverse.

Draft dataset for Bay Area Census website prototype. Includes census 2000 population breakdown by age, sex and race.

Splitgraph serves as an HTTP API that lets you run SQL queries directly on this data to power Web applications. For example:

See the Splitgraph documentation for more information.

Relative concentration of the Northern California region's American Indian population. The variable AIANALN records all individuals who select American Indian or Alaska Native as their SOLE racial identity in response to the Census questionnaire, regardless of their response to the Hispanic ethnicity question. Both Hispanic and non-Hispanic in the Census questionnaire are potentially associated with American Indian / Alaska Native race alone. IMPORTANT: this self reported ancestry and Tribal membership are distinct identities and one does not automatically imply the other. These data should not be interpreted as a distribution of "Tribal people." Numerous Rancherias in the Northern California region account for the wide distribution of very to extremely high concentrations of American Indians outside the San Francisco Bay Area.

"Relative concentration" is a measure that compares the proportion of population within each Census block group data unit that identify as American Indian / Alaska Native alone to the proportion of all people that live within the 1,207 block groups in the Northern California RRK region that identify as American Indian / Alaska native alone. Example: if 5.2% of people in a block group identify as AIANALN, the block group has twice the proportion of AIANALN individuals compared to the Northern California RRK region (2.6%), and more than three times the proportion compared to the entire state of California (1.6%). If the local proportion is twice the regional proportion, then AIANALN individuals are highly concentrated locally.

Historical Dataset of Green Bay Area Public School District is provided by PublicSchoolReview and contain statistics on metrics:Comparison of Diversity Score Trends,Total Revenues Trends,Total Expenditure Trends,Average Revenue Per Student Trends,Average Expenditure Per Student Trends,Reading and Language Arts Proficiency Trends,Math Proficiency Trends,Science Proficiency Trends,Graduation Rate Trends,Overall School District Rank Trends,American Indian Student Percentage Comparison Over Years (1991-2023),Asian Student Percentage Comparison Over Years (1991-2023),Hispanic Student Percentage Comparison Over Years (1991-2023),Black Student Percentage Comparison Over Years (1993-2023),White Student Percentage Comparison Over Years (1991-2023),Two or More Races Student Percentage Comparison Over Years (2013-2023),Comparison of Students By Grade Trends

Estrogens play a significant role in breast cancer development and are not only produced endogenously, but are also mimicked by estrogen-like compounds from environmental exposures. We evaluated associations between estrogenic (E) activity, demographic factors and breast cancer risk factors in Non-Latina Black (NLB), Non-Latina White (NLW), and Latina women. We examined the association between E activity and Indigenous American (IA) ancestry in Latina women. Total E activity was measured with a bioassay in plasma samples of 503 women who served as controls in the San Francisco Bay Area Breast Cancer Study. In the univariate model that included all women with race/ethnicity as the independent predictor, Latinas had 13% lower E activity (p = 0.239) and NLBs had 35% higher activity (p = 0.04) compared to NLWs. In the multivariable model that adjusted for demographic factors, Latinas continued to show lower E activity levels (26%, p = 0.026), but the difference between NLBs and NLWs was no longer statistically significant (p = 0.431). An inverse association was observed between E activity and IA ancestry among Latina women (50% lower in 0% vs. 100% European ancestry, p = 0.027) consistent with our previously reported association between IA ancestry and breast cancer risk. These findings suggest that endogenous estrogens and exogenous estrogen-like compounds that act on the estrogen receptor and modulate E activity may partially explain racial/ethnic differences in breast cancer risk.

Draft dataset for Bay Area Census website prototype. Includes census 2020 housing data. Contains housing by occupancy and vacancy status.

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/

This dataset tracks annual two or more races student percentage from 2013 to 2023 for Green Bay Area Public School District vs. Wisconsin

Population-adjusted prevalence of antibodies from COVID-19 vaccination in Round 3 within race/ethnicity and age groups and prevalence differences between non-White and White individuals.

Draft dataset for Bay Area Census website prototype. Includes census 2020 households data. Households by marriage, family, and ownership status, as well as householder sex and size.

Geographic coverage

The 1985 census covered the so-called white areas of South Africa, i.e. the areas in the former four provinces of the Cape, the Orange Free State, Transvaal, and Natal. It also covered the so-called National States of KwaZulu, Kangwane, Gazankulu, Lebowa, Qwaqwa, and Kwandebele. The 1985 South African census excluded the areas of the Transkei, Bophutatswana, Ciskei, and Venda.

The 1985 Census dataset contains 9 data files. These refer to Development Regions demarcated by the South African Government according to their socio-economic conditions and development needs. These Development Regions are labeled A to J (there is no Region I, presumably because Statistics SA felt an "I" could be confused with the number 1). The 9 data files in the 1985 Census dataset refer to the following areas:

DEV REGION AREA COVERED A Western Cape Province including Walvis Bay B Northern Cape C Orange Free State and Qwaqwa D Eastern Cape/Border E Natal and Kwazulu F Eastern Transvaal, KaNgwane and part of the Simdlangentsha district of Kwazulu G Northern Transvaal, Lebowa and Gazankulu H PWV area, Moutse and KwaNdebele J Western Transvaal

Analysis unit

The units of analysis under observation in the South African census 1985 are households and individuals

Universe

The South African census 1985 census covered the provinces of the Cape, the Orange Free State, Transvaal, and Nata and the so-called National States of KwaZulu, Kangwane, Gazankulu, Lebowa, Qwaqwa, and Kwandebele. The 1985 South African census excluded the areas of the Transkei, Bophutatswana, Ciskei, and Venda.

Kind of data

Census/enumeration data [cen]

Sampling procedure

Although the census was meant to cover all residents of the so called white areas of South Africa, in 88 areas door-to-door surveys were not possible and the population in these areas was enumerated by means of a sample survey conducted by the Human Sciences Research Council.

Mode of data collection

Face-to-face [f2f]

Research instrument

The1985 population census questionnaire was administered to each household and collected information on household and area type, and information on household members, including relationship within household, sex, age, marital status, population group, birthplace, country of citizenship, level of education, occupation, identity of employer and the nature of economic activities

Data appraisal

UNDER-ENUMERATION: The following under-enumeration figures have been calculated for the 1985 census. Estimated percentage distribution of undercount by race according to the HSRC: Percent undercount
Whites 7.6%
Blacks in the “RSA” 20.4% Blacks in the “National States” 15.1% Coloureds 1.0% Asians 4.6%

The Filipino American Community Epidemiological Study (FACES) is a research project of Asian American Recovery Services, Inc. of San Francisco, California. The four-year study, whose formal title is Alcohol-Related Problems among Filipino Americans, was concluded in 1999. It provides information and data about the health of Filipino Americans of the San Francisco Bay Area and the City and County of Honolulu. The interview asked randomly chosen Filipino American respondents in these two geographic areas about their health, alcohol consumption, mood state, physical symptoms, cultural background and sociodemographic information. The purpose of FACES was to study alcohol and stress-related behaviors of Filipino Americans. Demographic variables include gender, age, race, education level, marital status, household income, military service, and religious preference.

Population monitoring is essential to assess, manage and protect threatened species. Although the South Pacific loggerhead turtle subpopulation is classified as critically endangered by the IUCN, monitoring data are scarce. This study reports the results of the first long-term monitoring of the nesting population of loggerhead turtles held by Bwärä Tortues Marines on La Roche Percée beach, New Caledonia. From 2006 to 2020, Capture Mark Recapture was used to identify nesting individuals. Time and nesting success were recorded on site. A total of 452 different females were observed and tagged over 14 years. The number of different nesting individuals observed each year showed a significant increase along the timeframe of the study. A remigration interval of 3.34 years was observed and the overall nesting success was 59.02%. This study also reports the inter-nesting intervals, monthly and hourly variabilities in the visits at the nesting site. The conservation actions led by Bwärä Tortues Marines seem to be correlated with a higher nesting success. This study provides encouraging results and highlights the need to pursue the monitoring and conservation actions implemented by Bwärä Tortues Marines. Further management recommendations are also provided. Methods Overview Over 14 years (2006-2020), daily patrols were implemented throughout each nesting season (from November to March). The timing and activities of the loggerhead turtles were monitored. Study site The study was conducted on La Roche Percée, a sandy beach in the Bay of La Roche Percée, New Caledonia (-21.612831, 165.463286). This site is included in a marine protected area registered under the natural reserve status (Decree n° 33-1993/APS 1993 and 293-99/PS, 1999). The beach is oriented South-west and is 2.5 km in length starting from a stand-up rock at the North-western end, to the mouth of the Néra river at the South-eastern end. The Néra river brings dark sediments directly to the beach of La Roche Percée resulting in darker sand compared to nearby beaches. La Roche Percée bay faces a large break in the barrier reef surrounding the area, allowing waves but also marine megafauna to enter the lagoon. At high tide, the beach is 20m (meters) wide in the middle and 100m wide at the northern and southern ends. During the hot and humid season (November to March) the beach can be submerged by water due to extreme weather events. The only access to La Roche Percée is a road over a dam on its northern shore – blocking the northern bank of the Nera river. Vegetation near the road partially protects the beach from anthropogenic light sources (cars and houses) and there are no street lights in this area. Sand replenishment work took place in 2011 (during the time of this study but not during the nesting season) at the vegetation margin to widen the beach and counter beach erosion. The sand was taken from the Néra river but was not washed and sieved causing its compaction on some parts of the beach, resulting in the inability of turtles to dig in these areas. This compacted area was high on the beach at the margin of the vegetation and was partially covered with sand and vines (Ipomoea pescaprae). The bay is also famous for being one of the most important surf spots in New Caledonia and is one of the main leisure sites, attracting many locals and tourists all year long. Although pets are prohibited inside the reserve following a government decree put in place in 2009, dogs are regularly seen on the beach. In the bay, a second beach named La Baie des Tortues (i.e. Turtle Bay, -21.60655, 165.45478, 280m in length = 1/5 of La Roche Percée) is located 100m north of La Roche Percée beach. The beaches are separated by a high rocky spit. This beach was not monitored during the night as the steep and slippery path leading to it would represent a safety hazard for the team working without light. Monitoring and data collection The walking patrol covered the 2.5km of the study site, walking back and forth between the two ends of the beach. Each turtle activity on the beach of La Roche Percée was recorded from November 2006 to March 2020 (14 nesting seasons) by members of Bwärä Tortues Marines. Two patrol sessions were conducted on the beach every day during the nesting seasons: (1) in the evening, usually conducted from 8 pm to 1 am (i.e. night shift), which enabled monitoring of the nesting females encountered on the beach, (2) in the morning (i.e. morning shift) starting at dawn, for 2 to 5 hours, and allowing an exhaustive count of all nesting activities throughout the night. The duration of a patrol could vary if a turtle or a track was detected by a member of Bwärä Tortues Marine before or after the usual hours. For example, if a turtle was spotted at 00:50 am the patrol team stayed on site until the female completed her nesting cycle. Sometimes, turtles crawled on the beach one after the other and the patrol team had to work until dawn. Only extreme weather conditions such as rain downpours or cyclonic alerts led to the cancellation of a patrol (on average eight patrols per year).
During the night shift, one or two teams composed of an eco-guard and trained volunteers walked without light alongside the high-water line, searching for turtle tracks. The number of teams deployed depended on the number of volunteers available. When a track was noticed, the team stopped and remained immobile while trying to locate the individual. The team followed the track in a way which meant they were unnoticed by the turtle (e.g., crawling). Observers were able to determine the precise nesting phase by seeing or hearing the turtle. The nesting phases include: ascending the beach, making a body pit (multiple body pit attempts could be undertaken before the next stage), digging the egg chamber, laying eggs, filling the egg chamber, covering the body pit, and returning to the surf (for precise descriptions of the nesting phases see Hailman & Elowson, 1992). To avoid disturbance, the turtles were approached after the beginning of the egg-laying phase, from the back and without light. During the data collection, a red light was eventually used for a short time only and never toward the head of the turtle. If the individual was found returning to the sea, the data were gathered while the turtle stopped to breathe. Data collection included: individual identification and carapace length measure, date, time, location, and nesting phase. The morning shift consisted mainly of recording all the activities that happened during the late part of the night. It always started at dawn to maximize the chances of meeting the last turtles of the night, to protect those individuals from potential disturbances (i.e. beach visitors or dogs), and to be sure to record all turtle activities. A later start could have led to the loss of data due to rising tides, strong winds, or beach users who could have erased the tracks. Activities were defined using the sand cues as above. The date, time, and location of the activity were recorded. Each track (crawling tracks, body pit, and mound) was then wiped off so as not to count it a second time during the following night and to hide the nest. Individuals were identified using Capture-Mark-Recapture (CMR). Every studied individual was tagged with a titanium tag (Titanium Turtle Tag, Stockbrands, Australia) on the trailing edge of the front flipper, in the skin between the first and the second scales adjacent to the axilla following recommendations published in Limpus (1992). During the first five seasons, most of the individuals were tagged on both left and right front flippers, following which it was reduced to one tag, placed on the left flipper, to minimize individuals' stress. Following the CMR protocol, if turtles did not have a tag, they were tagged and considered as Captures (C). Individuals already tagged were considered as Recaptures (R). Individuals could be recaptured from earlier in the same nesting season or from previous nesting seasons. Individual tags were read at the end of the egg-laying phase or during the next phases to minimize disturbance. A few turtles were tagged before this study and observed between 2006 and 2020 (n=9, Limpus, Boyle & Sunderland, 2006). They were included as recaptures in the results. In 2011/2012, the titanium tags were substituted with Passive Integrated Transponder (PIT) tags (Animal Electronic I.D. Systems, Australia). After one season the PIT tag project was considered too intrusive and no longer used. Only one female was tagged with a titanium tag during this season. Each individual studied by the team was measured using the minimum Curved Carapace Length method (Wyneken, 2001) and physical anomalies were recorded. The location of the nest or the nesting attempt was recorded during night and morning sifts. A triangulation method was used to record location from the season 2006/2007 to the season 2016/2017. First, electric poles along the road allowed the team to obtain an approximate location of the nest. Then, precise location of the nest was obtained using triangulation made with salient field cues (e.g., tree, rocks). Since 2017/2018 onwards GPS were used. If the turtle had already left the beach (i.e. back to the sea), its activity was recorded using visual cues on the sand. The activity was considered a “nesting success” when the pit was filled with disturbed sand, indicating that the individual went through all the nesting phases and laid its eggs (Hailman & Elowson, 1992). The activity was considered as an aborted nesting attempt (also called “false crawl”) when the cues showed either (1) an attempt: the individual went through the first phases of the nesting process but stopped before laying its egg, during either the body pit or the digging of the chamber steps, or (2) a turnaround: the individual ascended the beach, stopped, turned around and returned to the sea (continuous

Forecasts for Year 2010 through 2040 containing values for Households by Inc. Quartile; Households; Jobs; Population by Gender, Age; Units; Employed Residents; Population by Age; Population for jurisdictions in the nine county San Francisco Bay Area region.

This dataset tracks annual two or more races student percentage from 2013 to 2023 for Lombardi Middle School vs. Wisconsin and Green Bay Area Public School District