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The 2010 Census Production Settings Demographic and Housing Characteristics Demonstration Noisy Measurement File (2023-04-03) is an intermediate output of the 2020 Census Disclosure Avoidance System (DAS) TopDown Algorithm (TDA) (as described in Abowd, J. et al [2022], and implemented in DAS 2020 Redistricting Production Code). The NMF was produced using the official "production settings," the final set of algorithmic parameters and privacy-loss budget allocations, that were used to produce the 2020 Census Redistricting Data (P.L. 94-171) Summary File and the 2020 Census Demographic and Housing Characteristics File. The NMF consists of the full set of privacy-protected statistical queries (counts of individuals or housing units with particular combinations of characteristics) of confidential 2010 Census data relating to the 2010 Demonstration Data Products Suite - Redistricting and Demographic and Housing Characteristics File - Production Settings (2023-04-03). These statistical queries, called "noisy measurements" were produced under the zero-Concentrated Differential Privacy framework (Bun, M. and Steinke, T [2016]; see also Dwork C. and Roth, A. [2014]) implemented via the discrete Gaussian mechanism (Cannone C., et al., [2023]), which added positive or negative integer-valued noise to each of the resulting counts. The noisy measurements are an intermediate stage of the TDA prior to the post-processing the TDA then performs to ensure internal and hierarchical consistency within the resulting tables. The Census Bureau has released these 2010 Census demonstration data to enable data users to evaluate the expected impact of disclosure avoidance variability on 2020 Census data. The 2010 Census Production Settings Demographic and Housing Characteristics (DHC) Demonstration Noisy Measurement File (2023-04-03) has been cleared for public dissemination by the Census Bureau Disclosure Review Board (CBDRB-FY22-DSEP-004).

The 2010 Census Production Settings Demographic and Housing Characteristics Demonstration Noisy Measurement File (2023-04-03) includes zero-Concentrated Differentially Private (zCDP) (Bun, M. and Steinke, T [2016]) noisy measurements, implemented via the discrete Gaussian mechanism. These are estimated counts of individuals and housing units included in the 2010 Census Edited File (CEF), which includes confidential data initially collected in the 2010 Census of Population and Housing. The noisy measurements included in this file were subsequently post-processed by the TopDown Algorithm (TDA) to produce the 2010 Census Production Settings Privacy-Protected Microdata File - Redistricting (P.L. 94-171) and Demographic and Housing Characteristics File (2023-04-03) (Demonstration Data Products Suite/2023-04-03/). As these 2010 Census demonstration data are intended to support study of the design and expected impacts of the 2020 Disclosure Avoidance System, the 2010 CEF records were pre-processed before application of the zCDP framework. This pre-processing converted the 2010 CEF records into the input-file format, response codes, and tabulation categories used for the 2020 Census, which differ in substantive ways from the format, response codes, and tabulation categories originally used for the 2010 Census.

The NMF provides estimates of counts of persons in the CEF by various characteristics and combinations of characteristics including their reported race and ethnicity, whether they were of voting age, whether they resided in a housing unit or one of 7 group quarters types, and their census block of residence after the addition of discrete Gaussian noise (with the scale parameter determined by the privacy-loss budget allocation for that particular query under zCDP). Noisy measurements of the counts of occupied and vacant housing units by census block are also included. Lastly, data on constraints--information into which no noise was infused by the Disclosure Avoidance System (DAS) and used by the TDA to post-process the noisy measurements into the 2010 Census Production Settings Privacy-Protected Microdata File - Redistricting (P.L. 94-171) and Demographic and Housing Characteristics File (2023-04-03) --are provided.

These data are available for download (i.e. not restricted access). Due to their size, they must be downloaded through the link on this metadata page and not through the standard ICPSR download. The link will take you to the Globus site where these data are housed. A README file is located in the Globus repository. Please refer to that for pertinent information. The Globus holding site requires users to create an account to access these data. Accounts can be created through existing institutional access and by personal access. Please see the Globus "How to get Started" page for more information.

The 2020 Census Demographic and Housing Characteristics Noisy Measurement File is an intermediate output of the 2020 Census Disclosure Avoidance System (DAS) TopDown Algorithm (TDA) (as described in Abowd, J. et al [2022], and implemented in DAS_2020_DHC_Production_Code/das_decennial/programs/engine/primitives.py at main uscensusbureau/DAS_2020_DHC_Production_Code (github.com) The 2020 Census Demographic and Housing Characteristics Noisy Measurement File includes zero-Concentrated Differentially Private (zCDP) (Bun, M. and Steinke, T [2016]) noisy measurements, implemented via the discrete Gaussian mechanism (Cannone C., et al., [2023] ), which added positive or negative integer-valued noise to each of the resulting counts. These are estimated counts of individuals and housing units included in the 2020 Census Edited File (CEF), which includes confidential data collected in the 2020 Census of Population and Housing.

The noisy measurements included in this file were subsequently post-processed by the TopDown Algorithm (TDA) to produce the Census Demographic and Housing Characteristics Summary File. In addition to the noisy measurements, constraints based on invariant calculations --- counts computed without noise --- are also included (with the exception of the state-level total populations, which can be sourced separately from data.census.gov).

The Noisy Measurement File was produced using the official "production settings," the final set of algorithmic parameters and privacy-loss budget allocations that were used to produce the 2020 Census Redistricting Data (P.L. 94-171) Summary File and the 2020 Census Demographic and Housing Characteristics File.

The noisy measurements are produced in an early stage of the TDA. Afterward, these noisy measurements are post-processed to ensure internal and hierarchical consistency within the resulting tables. The Census Bureau has released these noisy measurements to enable data users to evaluate the impact of disclosure avoidance variability on 2020 Census data. The 2020 Census Demographic and Housing Characteristics (DHC) Noisy Measurement File has been cleared for public dissemination by the Census Bureau Disclosure Review Board (CBDRB-FY22-DSEP-004).

These data are available for download (i.e. not restricted access). Due to their size, they must be downloaded through the link on this metadata page and not through the standard ICPSR download. The link will take you to the Globus site where these data are housed. A README file is located in the Globus repository. Please refer to that for pertinent information.

The Globus holding site requires users to create an account to access these data. Accounts can be created through existing institutional access and by personal access.

Please see the Globus "How to get Started" page for more information.

The 2020 Census Redistricting Data (P.L. 94-171) Noisy Measurement File is an intermediate output of the 2020 Census Disclosure Avoidance System (DAS) TopDown Algorithm (TDA) (as described in Abowd, J. et al [2022] https://doi.org/10.1162/99608f92.529e3cb9, and implemented in the DAS 2020 Redistricting Production Code). The 2020 Redistricting NMF was an intermediate output of the DAS during the execution of the algorithm to produce the 2020 Census Redistricting Data (P.L. 94-171) Summary File. The NMFs are intermediate privacy-protected outputs of the DAS; they were generated using the Census Bureau's implementation of the Discrete Gaussian Mechanism, calibrated to satisfy zero-Concentrated Differential Privacy with bounded neighbors. The NMF values, called "noisy measurements" are the output of applying the Discrete Gaussian Mechanism to counts from the 2020 Census Edited File (CEF). They are generally inconsistent with one another (for example, in a county composed of two tracts, the noisy measurement for the county's total population may not equal the sum of the noisy measurements of the two tracts' total population), and frequently negative (especially when the population being measured was small), but are integer-valued. The NMF was later post-processed as part of the DAS code to take the form of microdata and to satisfy various constraints. The NMF documented here contains both the noisy measurements themselves as well as the data needed to represent the DAS constraints; thus, the NMF could be used to reproduce the steps taken by the DAS code to produce microdata from the noisy measurements by applying the production code base.

The 2020 Census Redistricting Data (P.L. 94-171) Noisy Measurement File includes zero-Concentrated Differentially Private (zCDP) (Bun, M. and Steinke, T [2016]) noisy measurements, implemented via the discrete Gaussian mechanism. These are estimated counts of individuals and housing units included in the 2020 Census Edited File (CEF), which includes confidential data initially collected in the 2020 Census of Population and Housing. The noisy measurements included in this file were subsequently post-processed by the TopDown Algorithm (TDA) to produce the 2020 Census Redistricting Data (P.L. 94-171) Summary File.

The NMF provides estimates of counts of persons in the CEF by various characteristics and combinations of characteristics including their reported race and ethnicity, whether they were of voting age, whether they resided in a housing unit or one of 7 group quarters types, and their census block of residence after the addition of discrete Gaussian noise (with the scale parameter determined by the privacy-loss budget allocation for that particular query under zCDP). Noisy measurements of the counts of occupied and vacant housing units by census block are also included. Lastly, data on constraints--information into which no noise was infused by the Disclosure Avoidance System (DAS) and used by the TDA to post-process the noisy measurements into the 2020 Census Redistricting Data (P.L. 94-171) Summary File --are provided.

These data are available for download (i.e. not restricted access). Due to their size, they must be downloaded through the link on this metadata page and not through the standard ICPSR download. The link will take you to the Globus site where these data are housed. A README file is located in the Globus repository. Please refer to that for pertinent information.

The Globus holding site requires users to create an account to access these data. Accounts can be created through existing institutional access and by personal access.

Please see the Globus "How to get Started" page for more information.

The American Community Survey (ACS) Summary File is a set of comma-delimited text files that contain all of the Detailed Tables for the ACS data releases. Summary File estimates, margins of error, and geography files for each release are available.

The Detailed Tables are stored in a series of files with only the data from the tables and without such information as the table title, description of the rows, or geographic identifiers. That information is located in other files that the user must merge with the data files to reproduce full tables. Starting with the 2009-2013 ACS 5-year data release, block groups, the lowest level of geography published by the ACS, are available at data.census.gov. For earlier years, block groups are available only in the ACS 5-year Summary File.

The Americans' Changing Lives (ACL) survey series is an ongoing, nationally representative, longitudinal study focusing especially on differences between Black and White Americans in middle and late life. These data constitute the first, second, third, fourth, fifth, and sixth waves in a panel survey covering a wide range of sociological, psychological, mental, and physical health items. Wave I of the study began in 1986 with a nation face-to-face survey of 3,617 adults ages 25 and up, with Black Americans and people aged 60 and over over-sampled at twice the rate of the others. Wave II constitutes face-to-face re-interviews in 1989 of those still alive. Survivors have been re-interviewed by telephone, and when necessary face-to-face, in 1994 (Wave III), 2001/02 (Wave IV), 2011 (Wave V), and 2019/21 (Wave VI).

Please note that for Wave VI, the majority of data collection occurred in 2019, with only a small subset (n=39) of participants surveyed in 2021.

ACL was designed and sought to investigate the following: (1) The ways in which a wide range of activities and social relationships that people engage in are broadly "productive," (2) how individuals adapt to acute life events and chronic stresses that threaten the maintenance of health, effective functioning, and productive activity, and (3) sociocultural variations in the nature, meaning, determinants, and consequences of productive activity and relationships. Among the topics covered are interpersonal relationships (spouse/partner, children, parents, friends), sources and levels of satisfaction, social interactions and leisure activities, traumatic life events (physical assault, serious illness, divorce, death of a loved one, financial or legal problems), perceptions of retirement, health behaviors (smoking, alcohol consumption, overweight, rest), and utilization of health care services (doctor visits, hospitalization, nursing home institutionalization, bed days). Also included are measures of physical health, psychological well-being, and indices referring to cognitive functioning.

Demographic information provided for individuals includes household composition, number of children and grandchildren, employment status, occupation and work history, income, family financial situation, religious beliefs and practices, ethnicity, race, education, sex, and region of residence.

This study examines two counties in Oregon (Multnomah and Yamhill) that have utilized a pre-adjudication risk assessment (PAA) to inform criminal case negotiation since 2014. This study seeks to answer these core questions:

• has the introduction of a PAA into the court decision-making process impacted racial and ethnic disparities in sentencing outcomes over time in each county;
• does one PAA process appear to produce more promising results in impacting racial/ethnic disparities;
• using interviews and visual observations, how does the PAA influence case discussion and negotiation, decision-making, and workgroup norms and culture;
• does validation of the PAA tool yield significant mean score differences across racial groups and/or predictive biases?

A number of jurisdictions have turned to pre-adjudication risk assessments (PAA) as a tool to potentially lower or stabilize incarceration rates by identifying the best suitable cases for community-based supervision. Questions have been raised about using risk assessment tools to help with the negotiation of sentencing outcomes in the pre-adjudication stages of criminal cases, particularly the potential for exacerbating disparate racial/ethnic sentencing outcomes.

These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed.

This project sought to study the District Attorney of New York's (DANY) current practices by addressing the complex relationship between prosecutorial decision making and racial and ethnic justice in felony and misdemeanor cases closed in New York County in 2010-2011. Using a mixed-methods approach, administrative records from the DANY case-management systems and prosecutorial interviews were examined to study case acceptance for prosecution, pretrial detention and bail determination, case dismissal, plea offers, and sentencing. Researchers developed five hypotheses for the data collected:

1. Blacks and Latinos are more likely to have their cases accepted for prosecution than similarly situated white defendants.
2. Blacks and Latinos are more likely to be held in pretrial detention and less likely to be released on bail.
3. Blacks and Latinos are less likely to have cases dismissed.
4. Blacks and Latinos are less likely to receive a plea offer to a lesser charge and more likely to receive custodial sentence offers.
5. Blacks and Latinos are more likely to be sentenced to custodial punishments.

All criminal activity of the defendant was examined, as well as their demographics and prior history, the location of the crime. Information on the Assistant District Attorney (ADA) was examined as well, including their demographics and caseload in order to more thoroughly understand the catalysts and trends in decision making.

The purpose of the Census of Juveniles on Probation (CJP) was to collect individual-level data about youth on probation, including their numbers and characteristics. The CJP survey asked respondents to report the total number of juveniles on formal probation within their reporting jurisdiction on the reference date of October 24, 2012.

For each youth on probation, responding agencies were asked to provide the following information: sex, date of birth, race, most serious offense, state and county where most serious offense was committed, and the state and county where the juvenile resided on the census reference date.

This data collection contains the national data.

This data collection contains sample data from the 1990 Census weighted to represent the total population. Data items covered by the collection include age of householder, number of rooms and bedrooms, condominium status, contract rent, educational attainment of householder, gross rent, house heating fuel, household income, household type, presence and age of children, kitchen facilities, marital status, meals included in rent, means of transportation to work, mortgage status, number of persons in unit, persons per room, plumbing facilities, poverty status, presence of nonrelatives, selected monthly owner costs, telephone in unit, housing tenure, travel time to work, number of units in structure, value of housing unit, vehicles available, workers in household, year householder moved into unit, and year structure was built. In addition, the file contains 100-percent counts and unweighted sample counts for total persons and total housing units. The information is presented in 323 tables that are tabulated for every geographic unit represented in the data. There is one variable per table cell, plus additional variables with geographic information. Almost all of the tables are iterated by race and Hispanic origin: White, Black, American Indian, Eskimo or Aleut, Asian or Pacific Islander, Hispanic origin (of any race), and White, not of Hispanic origin.

All of the tables are shown for six levels of observation: United States, regions, divisions, states, Metropolitan Statistical Areas (MSA)/Consolidated Metropolitan Statistical Areas (CMSA), and Primary Metropolitan Statistical Areas. The data were supplied in eight data files, each with a portion of the cases. In addition, ICPSR produced a combined file with all of the cases.