Americans increasingly confront policy messages not from high-profile political figures, but from everyday citizens. Much is known about the effects of racial source cues from well-known political figures with salient racial identities. Less is known about how subtle racial cues from non-recognizable sources affect Americans' support for policies that are race-targeted and those that are not. In this paper, I conduct a randomized experiment that varies a cue of the source's racial identity and the type of policy for which the source advocates. I uncover little evidence for the hypothesis that subtle racial source cues activate racial attitudes that lead Americans to racialize policies that are (at least explicitly) race-neutral. I find instead that subtle cues of a Black vs.~White source decrease support only for race-targeted policies. I reason that two mechanisms possibly driving this effect are: (1) subtle racial source cues become salient for only race-targeted policies, thereby activating racial stereotypes for these policies but not others and (2) Black sources are perceived as less objective policy messengers when the policy explicitly aims to rectify injustices against Black Americans. More generally, the paper's overall findings suggest that subtle racial cues of who advocates for race-targeted policies matter for whether such policies can garner the public support they presumably need to come to fruition.

Important notice

The Office for Statistics Regulation confirmed on 12/09/2024 that the gender identity estimates from Census 2021 are no longer accredited official statistics and are classified as official statistics in development.

For further information please see: Sexual orientation and gender identity quality information for Census 2021

This dataset provides Census 2021 estimates that classify usual residents aged 16 years and over in England and Wales by gender identity and ethnic group. The estimates are as at Census Day, 21 March 2021.

Some sub-populations have age and geographic profiles that may affect the relationships with other variables such as education, employment, health and housing. Take care when using this variable with others. We will publish more detailed commentary and guidance later this year. Read more about this quality notice.

Area type

Census 2021 statistics are published for a number of different geographies. These can be large, for example the whole of England, or small, for example an output area (OA), the lowest level of geography for which statistics are produced.

For higher levels of geography, more detailed statistics can be produced. When a lower level of geography is used, such as output areas (which have a minimum of 100 persons), the statistics produced have less detail. This is to protect the confidentiality of people and ensure that individuals or their characteristics cannot be identified.

Coverage

Census 2021 statistics are published for the whole of England and Wales. Data are also available in these geographic types:

• country - for example, Wales
• region - for example, London
• local authority - for example, Cornwall
• health area – for example, Clinical Commissioning Group
• statistical area - for example, MSOA or LSOA

Gender identity

Classifies people according to the responses to the gender identity question. This question was voluntary and was only asked of people aged 16 years and over.

Ethnic group

The ethnic group that the person completing the census feels they belong to. This could be based on their culture, family background, identity or physical appearance.

Respondents could choose one out of 19 tick-box response categories, including write-in response options.

The current study explored the associations between relationship stigma, Racial-ethnic Worldview (REW; a construct developed as a comprehensive assessment of individual's perceptions of race and ethnicity), and relationship quality among those in interracial relationships (i. e., participants indicated their race was different than the race of their partner). One type of REW (Color-blind Achieved) was especially susceptible to the negative consequences of stigma from family members. Other significant differences in relationship quality and relationship stigma were found based on REW. Most notable is that individuals who acknowledge institutional racism, have positive intergroup attitudes, and a positive ethnic identity reported better relationship quality than those who denied institutional racism and/or had less positive attitudes toward their own ethnic group. These results demonstrate the utility of REW in contextualizing the experiences of individuals in interracial relationships as it relates to perceived stigma and relationship quality. The study offers a critical account of how individuals understanding of the racial and ethnic social context shapes relationship outcomes for those in interracial relationships in the United States.

This dataset contains the yearly statistics on the race and ethnicity of known offenders by type of offense. Major categories of bias motivations include Race/Ethnicity/Ancestry, Religion, Sexual Orientation, Disability, Gender and Gender Identity. Here Known Offenders indicates that some aspects of the suspect are identified, thus distinguishing from an unknown offender.

This article examined the mediating role of civic skill-acts and direct associations of group identity on intentions to engage in peaceful or radical protest actions (i.e. activism or radicalism intentions respectively). A sample of 526 university students in Hong Kong was surveyed. The findings suggested that political identity complementarily mediated the relationship between joining political activities and radicalism intentions. Religious identity and ethnic/racial identity each have an indirect-only mediation to activism as well as radicalism intentions when mediated by community activities and responding activities respectively. Finally, political identity and economic identity each have direct-only mediations to activism intentions respectively. These results suggest that although group identity and civic skill-acts uniquely contribute to protest intentions, the inter-relationship is complicated by the type of group identity, civic skill-act, and protest activity studied. Recommendations for future studies are discussed in light of the findings.

List price: $20

#1 NEW YORK TIMES BESTSELLER • From the National Book Award–winning author of Stamped from the Beginning comes a “groundbreaking” (Time) approach to understanding and uprooting racism and inequality in our society—and in ourselves.

“The most courageous book to date on the problem of race in the Western mind.”—The New York Times

NAMED ONE OF THE BEST BOOKS OF THE YEAR BY The New York Times Book Review • Time • NPR • The Washington Post • Shelf Awareness • Library Journal • Publishers Weekly • Kirkus Reviews

Antiracism is a transformative concept that reorients and reenergizes the conversation about racism—and, even more fundamentally, points us toward liberating new ways of thinking about ourselves and each other. At its core, racism is a powerful system that creates false hierarchies of human value; its warped logic extends beyond race, from the way we regard people of different ethnicities or skin colors to the way we treat people of different sexes, gender identities, and body types. Racism intersects with class and culture and geography and even changes the way we see and value ourselves. In How to Be an Antiracist, Kendi takes readers through a widening circle of antiracist ideas—from the most basic concepts to visionary possibilities—that will help readers see all forms of racism clearly, understand their poisonous consequences, and work to oppose them in our systems and in ourselves.

Kendi weaves an electrifying combination of ethics, history, law, and science with his own personal story of awakening to antiracism. This is an essential work for anyone who wants to go beyond the awareness of racism to the next step: contributing to the formation of a just and equitable society.

Praise for How to Be an Antiracist

“Ibram X. Kendi’s new book, How to Be an Antiracist, couldn’t come at a better time. . . . Kendi has gifted us with a book that is not only an essential instruction manual but also a memoir of the author’s own path from anti-black racism to anti-white racism and, finally, to antiracism. . . . How to Be an Antiracist gives us a clear and compelling way to approach, as Kendi puts it in his introduction, ‘the basic struggle we’re all in, the struggle to be fully human and to see that others are fully human.’ ”—NPR

“Kendi dissects why in a society where so few people consider themselves to be racist the divisions and inequalities of racism remain so prevalent. How to Be an Antiracist punctures the myths of a post-racial America, examining what racism really is—and what we should do about it.”—Time

ISBN: 9781984832214 Published: Aug 13, 2019 By: Ibram X. Kendi Read by: Ibram X. Kendi

©2019 Ibram X. Kendi (P)2019 Random House Audio

The purpose of this multicity, multiethnic, and multilingual survey was to provide a preliminary attempt to gauge the political attitudes and behavior of Asian Americans on a national scale. Major areas of investigation include ethnic identity, acculturation, homeland politics, voting and other types of political participation, political ideology, political partisanship, opinions on various social issues, social connectedness, racial integration, and group discrimination. Respondents were asked whether people of Asian descent had a great deal in common culturally, what they thought were the most important problems facing their own ethnic group, whether they belonged to any organization that represented the interest of their group, and their knowledge of the Wen Ho Lee case, the 8-20 Initiative, and other news stories and information about Asians in the United States. Political questions probed respondents' general interest in politics, whether and for whom they voted in the 2000 presidential election, their general knowledge of the presidential election process, the kinds of political activity in which they participated, their feelings about Asian-American candidates, their involvement with political parties, their level of trust in local, state, and federal government officials, self-identity with regard to a liberal vs. conservative stance on political matters, party affiliation, and how active they were in political parties or organizations in their home country if born outside of the United States. Respondents were also asked about their attitudes on such topics as immigration, affirmative action, job training, educational assistance, preferences in hiring and promotion, marriage outside of their ethnic group, and incidents of discrimination that they encountered. Demographic variables include language spoken in the home, religious preference, home ownership, ethnic origin of spouse, level of education, income, employment, age, and sex.

This dataset contains the yearly statistics on the victim types by bias motivation. Major categories of victim types include individuals, government, business/financial institution, religious organization, society/public and other or multiple victims. Major categories of bias motivations include Race/Ethnicity/Ancestry, Religion, Sexual Orientation, Disability, Gender and Gender Identity.

Persons of Turkish and Yugoslav nationality from the resident registries

The data consist of transcripts of interviews with 19 individuals from Brazil and 5 individuals from Colombia, who are all involved in Black and Indigenous activist organisations or in state agencies that are charged with promoting anti-racism and/or human rights. Each transcript begins with a paragraph giving contextual informationLatin America has often been held up as a region where racism is less of a problem than in regions such as the United States or Europe. Because most people are 'mestizos' (mixed race) and mixture is often seen as the essence of national identity, clear racial boundaries are blurred, resulting in comparatively low levels of racial segregation and a traditionally low public profile for issues of race. In Europe and the United States, the racial mixture and interaction across racial boundaries, which are typical of Latin America and are becoming more visible elsewhere, are heralded by some observers as leading towards a 'post-racial' reality, where anti-racism and multiculturalism - seen in this view as divisive policies that accentuate social differences - become unnecessary. Critics point out that mixture is not an antidote to racial inequality and racism in Latin America: they all coexist. This severely qualifies claims that mixture can lead to a 'post-racial' era. This project will investigate anti-racist practices and ideologies in Bolivia, Brazil, Colombia and Mexico. The project will contribute to conceptualising and addressing problems of racism, racial inequality and anti-racism in the region. We also propose that Latin America presents new opportunities for thinking about racism and anti-racism in a 'post-racial' world. Understanding how racism and anti-racism are conceived and practised in Latin America - in contexts in which mixture is pervasive - can help us to understand how to think about racism and anti-racism in other regions of the world, where notions of race have been changing in some respects towards Latin American patterns. It is also crucial to show the variety of ways in which mixture operates and co-exists with racism in Latin America - a region that is far from homogeneous. Research teams in each country, working with a range of organisations concerned with racism and discrimination, will explore how the organisations conceptualise and address key problems, which are becoming more salient in other regions, which confront similar scenarios. First, how to practice anti-racism when most people are mixed and when they may deny the importance of race and racism and themselves be both victims and the perpetrators of racism. Second, how to conceptualise and practice anti-racism when 'culture' seems to be the dominant discourse for talking about difference, but when physical difference (skin colour, hair type, etc.) remain powerful but often unacknowledged signs that move people to discriminate. Third, how to understand racism and combat it when race and class coincide to a great extent and make it easy to deny that race and racism are important factors. Fourth, how to make sure anti-racism addresses gender difference effectively, in a context in which mixture between white men and non-white women has been seen as the founding act of the nation. Fifth, how to pursue anti-racism when it is often claimed that there is little overt racist violence and that this is evidence of racial tolerance. We will explore how these elements structure - and may constrain - ideas about (anti-)racism within institutions, organisations and everyday practice. Our project will work with organisations in Bolivia, Brazil, Colombia and Mexico - countries that capture a good range of the region's diversity - to explore how racism and anti-racism are conceptualised and addressed in state and non-state circles, in legislation and the media, and in a variety of campaigns and projects. We aim to strengthen anti-racist practice in Latin America by feeding back our findings and by helping build networks; and to provide useful insights for understanding racism and anti-racism within and outside the region. The project carried out research in four countries, Brazil, Colombia, Ecuador and Mexico. We started by scoping out a broad range of organizations and individuals who were working in a direct or indirect fashion to challenge racism and racial inequality. We then selected seventeen case studies (over a third of which were Indigenous), with which we worked in depth, while also touching on about twenty other cases in a less intensive way. The cases were selected in order to include both Black and Indigenous organisations and cases, and to include a range of cases from government bodies to grassroots activist movements, plus some legal processes in which a variety of actors and organizations were involved. Our methods were mainly ethnography and interviews, undertaken principally by the four postdoctoral researchers, each of whom worked in one country. Some interviews were done with the assistance of a research assistant hired in the country. The interviews were conducted mostly in 2017, with some in 2018, in localities appropriate to the case study, such as an organization’s offices, an individual’s residence, or an agreed neutral location (e.g. a café, a village square, a classroom). Some interviews were informal conservations, but most were at least semi-structured. Common interview guides were not used, as each interview was specific to the case in question. Many interviews were audio-recorded (some were video-recorded) and selected interviews were transcribed in full or in part. Files with the original audio recordings and the transcripts are stored on a secure server in the University of Manchester. The files uploaded here are a selection of the transcribed interviews.

This dataset provides Census 2021 estimates that classify usual residents in England and Wales by their national identity. The estimates are as at Census Day, 21 March 2021.

The increase since the 2011 Census in people identifying as “British” and fall in people identifying as “English” may partly reflect true changes in self-perception. It is also likely to reflect that “British” replaced “English” as the first response option listed on the questionnaire in England.

Read more about this quality notice.

Area type

Census 2021 statistics are published for a number of different geographies. These can be large, for example the whole of England, or small, for example an output area (OA), the lowest level of geography for which statistics are produced.

For higher levels of geography, more detailed statistics can be produced. When a lower level of geography is used, such as output areas (which have a minimum of 100 persons), the statistics produced have less detail. This is to protect the confidentiality of people and ensure that individuals or their characteristics cannot be identified.

Coverage

Census 2021 statistics are published for the whole of England and Wales. Data are also available in these geographic types:

• country - for example, Wales
• region - for example, London
• local authority - for example, Cornwall
• health area – for example, Clinical Commissioning Group
• statistical area - for example, MSOA or LSOA

National identity (17 categories)

Someone’s national identity is a self-determined assessment of their own identity, it could be the country or countries where they feel they belong or think of as home. It is not dependent on ethnic group or citizenship.

Respondents could select more than one national identity.

This dataset contains summary table data of information from the provincial Use of Force Reports and occurrences that resulted in an enforcement action. The data used to produce these summary data comes from two sources: a) information about enforcement actions, such as calls for service types and occurrence categories, come from the Service's Records Management System and b) information related to reported use of force, such as highest types of force and perceived weapons, comes from the provincial use of force reports. The data counts unique occurrences which resulted in a police enforcement action or incidents of reported use of force. Hence, there may be more than one person and more than one officer involved in enforcement action incident or reported use of force incident. Since the summary tables are of incidents, where there was more than one person, descriptors such as perceived race refer to the composition of person(s) involved in the enforcement action incident. For example, if the incident involved more than one person, each perceived to be of a different race or gender group, then the incident is categorized as a “multiple race group.” For the purpose of the race-based data analysis, the data includes all incidents which resulted in a police enforcement action and excludes other police interactions with the public, such as taking victim reports, routine traffic or pedestrian stops, or outreach events. Enforcement actions are occurrences where person(s) involved were arrested resulting in charges (including released at scene) or released without charges; received Provincial Offences Act Part III tickets; summons; cautions; diversions; apprehensions, mental health-related incidents as well as those identified as “subject” or “suspect” in an incident to which an officer attended. Reported use of force incident are those in which a Toronto Police Service officer used force and are required to submit a report under the Police Services Act, 1990. For the purposes of the race-based data analysis, it excludes reportable incidents in which force was used against animals, team reports, and incidents where an officer unintentionally discharged a Service weapon during training. Each reported use of force incident is counted once, regardless of the number of officers or subjects involved.

The main topics of the year 2003 survey covered national consciousness, national identity and attitudes towards home country and immigrants. Respondents were asked which groups are important to them in describing who they are. Pertaining to national identity, respondents were asked how close they felt to their municipality of residence, region, Finland and Europe. Views were probed on which things are important for being Finnish. Feelings of solidarity towards Finland were assessed. Respondents evaluated the degree of national pride they feel towards Finland's accomplishments in the following areas: democracy, international political influence, economic achievements, social security, science and technology, sports, arts and literature, armed forces, history, equality. The survey carried a set of attitudinal questions relating to Finland's relations to other countries, free trade, the power of international bodies, purchase of land by foreigners, national programs and films on television, and the Internet. Some statements charted respondents' opinions on whether ethnic and racial minorities should preserve their own customs and traditions. Attitudes towards immigrants and immigration were also studied. Respondents' citizenship and the citizenship of their parents were surveyed. One theme pertained to who should have the right to Finnish citizenship. Overall national pride, and languages spoken at home were charted. EU issues were studied by asking how much respondents know about the European Union, and does Finland benefit from its membership, should the country comply with EU decisions even when in disagreement, should EU have more power than the national governments, and whether respondents would vote for or against Finland's membership at that moment. Background variables included respondent's sex, year of birth, marital status, education, occupation, employment status, hours worked, trade union membership, employer type, industry of employment, political identification, religious activity, membership in a church or other religious community, social class, household and personal income, household size and composition and type of neighbourhood. Background variables included also the spouse's education, occupation, hours worked, employer type, and industry of employment.

This multi-phase study was conducted to discover and learn more about the services offered to victims of identity theft and to evaluate the effect of these services on those who experienced this crime. The first phase of this study focused on the effects of identity theft services on its direct victims. This was accomplished by combining available data from the Identity Theft Supplement (ITS) with survey data associated with the Identity Theft Resource Center (ITRC). The second phase of this study was conducted as multiple focus groups where qualitative data was collected to help in understanding more about identity crime victimization. The participants that attended these focus groups were organizations and individuals who provided insight on the type of interactions within these identity crime services. The third phase of this study was to examine the level of efficiency of the ITRC victim call center by performing interviews with the victims. Demographic variables include gender, race, age, ethnicity, education, marital status, and income.

CrowS-Pairs (Social biases in MLMs)

CrowS-Pairs: A Challenge Dataset for Measuring Social Biases in Masked LM

By [source]

About this dataset

The CrowS-Pairs dataset is a collection of 1,508 sentence pairs that cover nine types of biases: race/color, gender/gender identity, sexual orientation, religion, age, nationality, disability, physical appearance, and socioeconomic status. Each sentence pair is a minimal edit of the first sentence: The only words that change between them are those that identify the group. The first sentence can demonstrate or violate a stereotype. The other sentence is a minimal edit of the first sentence: The only words that change between them are those that identify the group. Each example has the following information:

Columns:,**sent_more**,sent_less,**stereo_antistereo**,bias_type,**annotations**,,anon_writer,,anon_annotators,,prompt,,source

The CrowS-Pairs dataset is a collection of 1,508 sentence pairs that cover nine types of biases: race/color, gender/gender identity, sexual orientation, religion, age

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How to use the dataset

The CrowS-Pairs dataset is a collection of 1,508 sentence pairs that cover nine types of biases: race/color, gender/gender identity, sexual orientation, religion, age, nationality, disability, physical appearance, and socioeconomic status. Each sentence pair is a minimal edit of the first sentence: The only words that change between them are those that identify the group. The first sentence can demonstrate or violate a stereotype. The other sentence is a minimal edit of the first sentence: The only words that change between them are those that identify the group. Each example has the following information:

Columns:,**sent_less**sent_more,,stereo_antistereo,,bias_type,,annotations,,anon_writer,,anon_annotators,,,,prompt,,source

This dataset can be used to measure social biases in MLMs by training models on it and evaluating their performance

Research Ideas

• Measuring the ability of MLMs to identify and avoid social biases;
• Developing new methods for reducing social biases in MLMs; and
• Investigating the impact of social biases on downstream tasks such as reading comprehension or question answering

Acknowledgements

If you use this dataset in your research, please credit the original authors.

Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: crows_pairs_anonymized.csv | Column name | Description | |:----------------------|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------| | sent_more | The first sentence in the pair, which can demonstrate or violate a stereotype. (String) | | sent_less | The second sentence in the pair, which is a minimal edit of the first sentence. The only words that change between them are those that identify the group. (String) | | stereo_antistereo | Whether the first sentence demonstrates or violates a stereotype. (String) | | bias_type | The type of bias represented in the sentence pair. (String) | | annotations | The annotations made by the crowdworkers on the sentence pair. (String) | | anon_writer | The anonymous writer of the sentence pair. (String) | | anon_annotators | The anonymous annotators of the sentence pair. (String) |

File: prompts.csv | Column name | Descripti...

The census is undertaken by the Office for National Statistics every 10 years and gives us a picture of all the people and households in England and Wales. The most recent census took place in March of 2021.The census asks every household questions about the people who live there and the type of home they live in. In doing so, it helps to build a detailed snapshot of society. Information from the census helps the government and local authorities to plan and fund local services, such as education, doctors' surgeries and roads.Key census statistics for Leicester are published on the open data platform to make information accessible to local services, voluntary and community groups, and residents. There is also a dashboard published showcasing various datasets from the census allowing users to view data for Leicester and compare this with national statistics.Further information about the census and full datasets can be found on the ONS website - https://www.ons.gov.uk/census/aboutcensus/censusproductsEthnicityThis dataset provides Census 2021 estimates that classify usual residents in England and Wales by ethnic group. The estimates are as at Census Day, 21 March 2021.Definition: The ethnic group that the person completing the census feels they belong to. This could be based on their culture, family background, identity or physical appearance.Respondents could choose one out of 19 tick-box response categories, including write-in response options.This dataset includes data relating to Leicester City and England overall.

Children and youth who belong to a racially minoritized group commonly experience multiple and complex forms of discrimination and health disparities. The purpose of this review was to explore racial disparities in health care and health outcomes among children and youth with physical disabilities. Six international databases (Ovid Medline, Healthstar, Embase, PsycINFO, Scopus, and Web of Science) were searched and screened for inclusion. A narrative synthesis was used to identify the common trends. Thirty-seven articles met the inclusion criteria, which involved 218 555 children and youth with various types of physical disabilities spanning over 29 years. We noted the following trends: (1) racial disparities in accessing or receiving care; (2) racial disparities in health outcomes and mortality rates; and (3) factors affecting racial disparities. Most studies reported at least one finding indicating that racially minoritized youth had differential access to care and/or disparities in health outcomes compared to white youth. Our findings highlight the concerning racial disparities among children and youth with physical disabilities within health care. There is an urgent need for advocacy and interventions at multiple levels to address the perpetual racism and racial disparities that racially minoritized youth with physical disabilities experience.Implications for rehabilitationThere is an urgent need for health care leaders and health care providers to address the systemic health inequalities in rehabilitation for racially minoritized children and youth with physical disabilities.Health care leaders and clinicians should recognize the racial disparities that racially minoritized youth with physical disabilities encounter in accessing or receiving care in addition to health outcomes.Health care leaders and decision-makers should advocate for policy change to optimize equitable and inclusive health care to enhance the well-being of racially minoritized children with disabilities.Health care providers should engage in training to understand how to recognize and address how intersectional forms of a child’s identity such as disability, race, and socio-economic status can influence health care experiences and health outcomes. There is an urgent need for health care leaders and health care providers to address the systemic health inequalities in rehabilitation for racially minoritized children and youth with physical disabilities. Health care leaders and clinicians should recognize the racial disparities that racially minoritized youth with physical disabilities encounter in accessing or receiving care in addition to health outcomes. Health care leaders and decision-makers should advocate for policy change to optimize equitable and inclusive health care to enhance the well-being of racially minoritized children with disabilities. Health care providers should engage in training to understand how to recognize and address how intersectional forms of a child’s identity such as disability, race, and socio-economic status can influence health care experiences and health outcomes.

Donald Trump initiated his run for president by framing the United States as a nation in descent. Adopting the slogan “Make America great again,” he set his campaign against a backdrop of loss and declared a mission for reclamation. Numerous analysts claim that his candidacy and rhetoric galvanized White voters who feel left behind by changing times, but few have been able to provide direct evidence of a racialized sense of disadvantage, and most polls were not prepared to ask such specific questions prior to the Iowa Caucus. Using data from the National Study of Color- Blindness and Race-Consciousness—a unique nationally-sampled dataset fielded two weeks before the beginning of the 2016 primary election season—this article demonstrates that Trump was not only the most popular candidate among White voters, but that he was especially supported by Whites who think that their racial group fares worse in the job market than do Black Americans; who feel that being White has been personally detrimental to their job prospects; who believe that there are generally more disadvantages to being White than there are advantages; and who disagree with the notion that systemic racism mainly benefits Whites. The present analysis argues that how Whites think about Whiteness mattered for their likelihood to support Donald Trump.

A. SUMMARY This archived dataset includes data for population characteristics that are no longer being reported publicly. The date on which each population characteristic type was archived can be found in the field “data_loaded_at”.

B. HOW THE DATASET IS CREATED Data on the population characteristics of COVID-19 cases are from:  * Case interviews  * Laboratories  * Medical providers    These multiple streams of data are merged, deduplicated, and undergo data verification processes.  

Race/ethnicity * We include all race/ethnicity categories that are collected for COVID-19 cases. * The population estimates for the "Other" or “Multi-racial” groups should be considered with caution. The Census definition is likely not exactly aligned with how the City collects this data. For that reason, we do not recommend calculating population rates for these groups.

Gender * The City collects information on gender identity using these guidelines.

Skilled Nursing Facility (SNF) occupancy * A Skilled Nursing Facility (SNF) is a type of long-term care facility that provides care to individuals, generally in their 60s and older, who need functional assistance in their daily lives.  * This dataset includes data for COVID-19 cases reported in Skilled Nursing Facilities (SNFs) through 12/31/2022, archived on 1/5/2023. These data were identified where “Characteristic_Type” = ‘Skilled Nursing Facility Occupancy’.

Sexual orientation * The City began asking adults 18 years old or older for their sexual orientation identification during case interviews as of April 28, 2020. Sexual orientation data prior to this date is unavailable. * The City doesn’t collect or report information about sexual orientation for persons under 12 years of age. * Case investigation interviews transitioned to the California Department of Public Health, Virtual Assistant information gathering beginning December 2021. The Virtual Assistant is only sent to adults who are 18+ years old. https://www.sfdph.org/dph/files/PoliciesProcedures/COM9_SexualOrientationGuidelines.pdf">Learn more about our data collection guidelines pertaining to sexual orientation.

Comorbidities * Underlying conditions are reported when a person has one or more underlying health conditions at the time of diagnosis or death.

Homelessness Persons are identified as homeless based on several data sources: * self-reported living situation * the location at the time of testing * Department of Public Health homelessness and health databases * Residents in Single-Room Occupancy hotels are not included in these figures. These methods serve as an estimate of persons experiencing homelessness. They may not meet other homelessness definitions.

Single Room Occupancy (SRO) tenancy * SRO buildings are defined by the San Francisco Housing Code as having six or more "residential guest rooms" which may be attached to shared bathrooms, kitchens, and living spaces. * The details of a person's living arrangements are verified during case interviews.

Transmission Type * Information on transmission of COVID-19 is based on case interviews with individuals who have a confirmed positive test. Individuals are asked if they have been in close contact with a known COVID-19 case. If they answer yes, transmission category is recorded as contact with a known case. If they report no contact with a known case, transmission category is recorded as community transmission. If the case is not interviewed or was not asked the question, they are counted as unknown.

C. UPDATE PROCESS This dataset has been archived and will no longer update as of 9/11/2023.

D. HOW TO USE THIS DATASET Population estimates are only available for age groups and race/ethnicity categories. San Francisco po

This dataset contains summary table data of information from the provincial Use of Force Reports and occurrences that resulted in an enforcement action. The data used to produce these summary data comes from two sources: a) information about enforcement actions, such as calls for service types and occurrence categories, come from the Service's Records Management System and b) information related to reported use of force, such as highest types of force and perceived weapons, comes from the provincial use of force reports. The data counts unique occurrences which resulted in a police enforcement action or incidents of reported use of force. Hence, there may be more than one person and more than one officer involved in enforcement action incident or reported use of force incident. Since the summary tables are of incidents, where there was more than one person, descriptors such as perceived race refer to the composition of person(s) involved in the enforcement action incident. For example, if the incident involved more than one person, each perceived to be of a different race or gender group, then the incident is categorized as a “multiple race group.” For the purpose of the race-based data analysis, the data includes all incidents which resulted in a police enforcement action and excludes other police interactions with the public, such as taking victim reports, routine traffic or pedestrian stops, or outreach events. Enforcement actions are occurrences where person(s) involved were arrested resulting in charges (including released at scene) or released without charges; received Provincial Offences Act Part III tickets; summons; cautions; diversions; apprehensions, mental health-related incidents as well as those identified as “subject” or “suspect” in an incident to which an officer attended. Reported use of force incident are those in which a Toronto Police Service officer used force and are required to submit a report under the Police Services Act, 1990. For the purposes of the race-based data analysis, it excludes reportable incidents in which force was used against animals, team reports, and incidents where an officer unintentionally discharged a Service weapon during training. Each reported use of force incident is counted once, regardless of the number of officers or subjects involved.