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In the United States presidential election of November 2000, approximately 180,000 ballots in Florida's 67 counties were uncertified because they failed to register a "valid" vote for president. These ballots included those in which no vote was recorded (undervotes) and those in which people voted for more than one candidate (overvotes). The 2000 Florida Ballots Project examined the undervotes and overvotes. The goal of the project was not to declare a "winner," but rather to carefully examine the ballots to assess the relative reliability of the three major types of ballot systems used in Florida. The results of this assessment may help state legislatures, other decision-makers, and developers of ballot systems to work toward more reliable ballot systems in the future.

This collection contains seven separate data sets. The first data set is the "Raw Data File" which contains one record for each ballot examined. In addition to ballot information, each record includes county name, FIPS code, ballot system and other identifying information. The unique identifier for each record is recorded in the variable BALNUM, and can be used to link the data sets. The second data set is the "Aligned Data File." This data set matches the Raw Data File with the exception of the variables associated with the candidates. All chad-level data (including chads that represent a particular candidate) are presented in the raw file. In the aligned data file, only those data that apply to candidate chads are included - data from three coding systems are contained in the same variable for each candidate. The third data set is the "Recode Data File." At random intervals, after coding a group of ballots, the coders were instructed to recode the same ballots as a check on intra-coder reliability (or consistency within a coder). These second codings are contained in the recode data file. The difference between variables in the recode data and file and the aligned data file is variables with the suffix C1, C2, or C3 in the aligned data has R1, R2, and R3, respectively, in the recode data. The fourth data file is the "Comment Data File." The comments data file is a ballot-level file containing all comments made by coders during the coding of ballots. The data file contains one record for each ballot for which at least one of the three coders recorded a comment; 5,407 ballots had at least one coder comment and are contained in this file. The fifth data file is the "Coder Demographic Data File." The Coder Demographic data file contains the results of a questionnaire given to each coder employed by NORC for the Florida Ballots Project. This file contains one record for each coder and includes information such as the sex, marital status, age, income level, ethnicity, and political affiliation of each coder. The ID field contains the identification number of the coder which can be used as a link to the raw and aligned data files. The sixth and seventh data sets are the "Orange County Raw Data File" and "Orange County Aligned Data File." These two data sets are identical to the structures of the raw and aligned data files, respectively. Each file has 417 records. These data files are being made available because the 966 undervotes and 1,383 overvotes reported by Orange County on election day (that ultimately informed the tally of certified totals) could not be segregated by county officials responsible for producing the ballots for NORC review. The NORC coders were initially shown only 640 undervotes and 1,197 overvotes. At the time of initial coding, more than 400 of the ballots rejected by machines on election day simply could not be distinguished from ballots that were accepted and certified on election day.

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 Chicago Surveys are part of a long-running series of public opinion surveys conducted by The Chicago Council on Global Affairs every two years. This study is the 2012 Chicago Council Survey, designed to investigate the opinions and attitudes of the general public on matters related to foreign policy, and to define the parameters of public opinion within which decision-makers must operate.

The 2012 Chicago Council Survey focuses on respondents' opinions of the United States' leadership role in the world and the challenges the country faces domestically and internationally.

The survey covers the following international topics: relations with other countries, role in foreign affairs, possible threats to vital interests in the next ten years, foreign policy goals, benefits or drawbacks of globalization, situations that might justify the use of United States troops in other parts of the world, the number and location of United States military bases overseas, respondent feelings toward people of other countries, opinions on the influence of other countries in the world and how much influence those countries should have, United States participation in potential treaties, the United States' role in the United Nations and NATO, which side the United States should take in the Israeli-Palestinian conflict, what measures should be taken to deal with Iran's nuclear program, the military effort in Afghanistan, opinions on efforts to combat terrorism, and the rise of China as a global power.

Domestic issues include economic prospects for American children when they become adults, funding for government programs, the fairness of the current distribution of income in the United States, climate change, greenhouse gas emissions, and United States dependence on foreign energy sources.

Demographic and other background information include age, gender, race/ethnicity, marital status, left-right political self-placement, political affiliation, employment status, highest level of education, and religious preference. Also included are household size and composition, whether the respondent is head of household, household income, housing type, ownership status of living quarters, household Internet access, Metropolitan Statistical Area (MSA) status, and region and state of residence.

The purpose of the 2015 Local Arts Agency (LAA) Census was to characterize the different ways that LAAs perform their vital roles in every community. LAAs share the goals of enabling diverse forms of arts and culture to thrive locally, ensuring broad accessibility to the public, and building healthier communities through the arts.

The census provides details about LAA staffing and oversight, services and programs, partnerships and collaborations in the community, grantmaking, diversity within staff/volunteers/board and diversity in programming, marketing and communications practices, arts education, services for the military, and operating revenues and expenditures, and more. For a more detailed listing of question groups, please refer to the Description of Variables below.

This study contains data from the two forms of the surveys (Full and Abbreviated--a subset of the Full survey). These surveys were distributed online to 4,377 individual Local Arts Agencies in the United States which were known to Americans for the Arts in 2015. A total of 1,127 LAAs responded to the census survey. 641 submitted the Full survey; 486 completed the Abbreviated survey. The overall response rate was 26%.

The data is contained in two separate datasets comprising results from the two surveys. The Full Survey (dataset 1) contains data from the 641 respondents who completed the long survey. The Combined Surveys (dataset 2) contains responses from both the 486 respondents of the abbreviated survey as well the corresponding 641 responses from the full survey for a total of 1,127 respondents. The rate of response from large and mid-sized LAAs was very high, while small and volunteer-driven LAAs were underrepresented in the survey respondents.

The 2015 U.S. Transgender Survey (USTS) was conducted by the National Center for Transgender Equality (NCTE) to examine the experiences of transgender adults in the United States. The USTS questionnaire was administered online and data were collected over a 34-day period in the summer of 2015, between August 19 and September 21. The final sample included respondents from all fifty states, the District of Columbia, American Samoa, Guam, Puerto Rico, and U.S. military bases overseas. The USTS Public Use Dataset (PUDS) features survey results from 27,715 respondents and details the experiences of transgender people across a wide range of areas, such as education, employment, family life, health, housing, and interactions with police and prisons.

The survey instrument had thirty-two sections that covered a broad array of topics, including questions related to the following topics (in alphabetical order): accessing restrooms; airport security; civic participation; counseling; family and peer support; health and health insurance; HIV; housing and homelessness; identity documents; immigration; intimate partner violence; military service; police and incarceration; policy priorities; public accommodations; sex work; sexual assault; substance use; suicidal thoughts and behaviors; unequal treatment, harassment, and physical attack; and voting.

Demographic information includes age, racial and ethnic identity, sex assigned at birth, gender and preferred pronouns, sexual orientation, language(s) spoken at home, education, employment, income, religion/spirituality, and marital status.

There are no publicly available data files for this study. The naming conventions were maintained from the original pre-ICPSR release and the PUDS file is restricted use along with the qualitative data (MS Excel) file.

Before applying for access to these data please refer to the Approved Requests for USTS Data. These abstracts describe work currently in progress, and we provide them to help reduce the risk of duplication of research efforts.

The 2016 Latino Immigrant National Election Study (LINES) is a panel study of Latino foreign-born residents of the United States, with telephone surveys of nationally representative samples of respondents fielded in 3 waves over 2016-2017.

The first survey in the 2016 LINES took place during the general election campaign (August and September of 2016). Interviews (N = 1,800) were conducted in English and Spanish, although nearly all respondents opted for Spanish. Because many of the initial telephone numbers dialed were either out of service or otherwise unusable, the American Association for Public Opinion Research (AAPOR) "Response Rate 1" calculation is low (.034). However, in cases when an eligible immigrant was identified based on the initial screening questions, only 12 percent opted not to complete the survey. On average, an interview that fall lasted approximately 25 minutes.

After the 2016 election, 576 immigrants took part in the second survey wave, which was fielded during the presidential transition period (a 32 percent re-contact rate). At this time, an additional fresh sample of 260 Latino immigrants was added to the study, again to help gauge and ameliorate any potential respondent attrition biases. Finally, in the summer of 2017 (July through early-September), a third wave was conducted, with all 1,800 immigrants from the pre-election baseline survey being eligible for interviewing. In this period, 31 percent of these immigrants (N = 554) were surveyed; this included 321 respondents who had taken part in the second wave and 233 who had not. To increase the sample size at this time and address attrition over time, 500 fresh immigrants were surveyed. In total, 2,560 immigrants took part in the 2016-2017 LINES: 1,800 from before the election, 260 during the presidential transition period, and 300 in the summer of 2017.

The questionnaire instrumentation used in the study was largely adapted from item wordings in the 2012 American National Election Study (ANES). The survey focuses on immigrant civic engagement and political socialization, including items on immigrant attitudes, opinions and electoral and non-electoral political behavior.

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 2021-2022 Study of Family and Staff Experiences in AIAN Head Start FACES Programs (2021-2022 Study) builds on the American Indian and Alaska Native Head Start Family and Child Experiences Survey (AIAN FACES), which has been a source of national information on children and families enrolled in Head Start programs operated by federally recognized tribes (known as Region XI AIAN Head Start) since 2015. The motivation and goals of the Study of Family and Staff Experiences in AIAN FACES Programs (the 2021-2022 study) came from a need that arose as the COVID-19 pandemic continued into another year of affecting Region XI Head Start families' and staff's lives--and from recognizing the disproportionate impact of the pandemic on AIAN communities.

The 2021-2022 study included a nonrepresentative sample of Region XI Head Start programs and the children and families they serve. Although a nationally representative sample of Region XI Head Start programs, centers, teachers, and children were selected, fewer of them participated than expected, despite an extension of the planned parental consent collection and data collection windows.

The 2021-2022 Study of Family and Staff Well-Being in Head Start FACES Programs (2021-2022 study), builds on the Head Start Family and Child Experiences Survey (FACES), which has been a source of national information about Head Start programs and participants since 1997. The motivation and goals of the Study of Family and Staff Well-Being in Head Start Family and Child Experiences Survey Programs (the 2021-2022 study) came from a need that arose as the COVID-19 pandemic continued into another year of affecting Head Start families' and staff's lives.

The 2021-2022 study included two components. Firstly, the Program, Staff, and Family Study, was conducted in 60 programs, and included the collection of parent surveys and Teacher Child Reports (TCRs) in fall 2021 and spring 2022, as well as a teacher survey in fall 2021. Secondly, the Program and Staff Study, conducted in the 60 programs participating in the Program, Staff, and Family Study plus an additional 120 programs, included the collection of program director, center director, and teacher surveys in spring 2022.

The 2021-2022 study aimed to describe the national population of Head Start programs, centers, teachers, classrooms, and children during the 2021-2022 program year. However, the Data Producers were unable to fully meet this goal because of challenges related to the COVID-19 pandemic. A nationally representative sample of Head Start programs was selected. However, fewer of the programs participated than expected. Probability samples of centers, teachers, and children within the participating programs were selected. Weights are available for analysis to account for the probability that children and their teachers, centers, and programs were selected for the study. This lessens the risk of bias due to study non-participation and survey nonresponse; and provide results that represent, to the extent possible, all programs, centers, teachers, classrooms, and children in Head Start. The responding sample may not fully represent the population due to higher-than-expected non-response that may not have been adequately addressed with weighting adjustments.

Despite these limitations, the 2021-2022 study sample design supports many analyses for programs and teachers, as well as children. The data from the programs in the Program, Staff, and Family Study can address questions about the children and parents who participate in the program, including about children's development across one year in the Head Start program for both newly entering children and those returning for a second year. The study also supports research questions related to subgroups of interest, such as families with low income and specific racial/ethnic groups, as well as policy issues that emerge during the study. In addition, the research questions investigate the characteristics of Head Start programs, centers, and teachers, and the classrooms they teach. Users can use the same data to answer questions about the relationships between program and classroom characteristics and child and family well-being. The data from the larger sample of programs in the Program and Staff Study are most useful for answering questions about Head Start programs, classrooms, teachers, and program and center directors.

Over half of public school buildings across the country fail to provide adequate conditions for students to learn and school staff to work. Prior research has established an evidence base of associations between high-quality school building facilities and student, staff, school, and community health and education outcomes. Recognizing this research and the need for facility improvements, Maryland has approved the 21st Century School Buildings Program, which is paid for by Baltimore City Public Schools (City Schools), the State of Maryland, and the City of Baltimore. The program will invest close to $1 billion to renovate or replace over two dozen school buildings. City Schools, with support from the Fund for Educational Excellence, selected the RAND Corporation to study the impact of new school buildings on student, staff, school, and community outcomes.

The goal of this first phase was to collect data prior to the start of the Baltimore 21st Century Building Program and conduct initial exploratory analyses of data from treatment schools (i.e., schools slated for renovation or rebuilding) and comparison schools (i.e., schools with similar student and school characteristics but not slated for renovation or rebuilding). The data compiled here are audits of the street segments immediately surrounding those target schools. These observations from Spring 2016 were collected in an effort to document the conditions and features of the neighborhoods prior to school building renovations.

This data collection describes baseline neighborhood characteristics prior to the 21st Century Buildings School Program. For more information about the Baltimore City Schools and the 21st Century School Building Program, please visit the 21st Century Schools website.

The 500 Family Study was designed to obtain in-depth information on middle class, dual-career families living in the United States. To understand the complex dynamics of today's families and the strategies they use to balance the demands of work and family, over 500 families from 8 cities across the United States were studied. To address different issues facing parents with older and younger children, families with adolescents and families with kindergartners were included in the sample. Working mothers and fathers are now splitting their time between their responsibilities to their family, and to their respective occupations. This study of 500 families explores how work affects the lives and well-being of parents and their children.

The study's data allows researchers to explore a broad range of questions:

• How do dual-career families manage and organize their resources and time between family and work?
• How do work conditions, including characteristics of the job and workplace environment, affect the quality of relationships among household members?
• How do dual career parents manage the moral and social development and learning experiences of their children?
• How do the work-related responsibilities of working parents affect their child's moral, social, and educational development?
• What effect is consumerism and technology having on how working families direct the moral and social development of their children?
• What do parents believe is their role regarding the child-care of their children and how they should fulfill that role both in terms of time and in the allocation of economic and social resources? What are some of the resources in the community that parents use to supervise their children?
• How do families regard the "free time" of adolescents and how they allocate adolescent "free time" in maintenance of the household?
• What is the quality of relationships among family members?

To obtain a detailed picture of work and family life, mothers, fathers, and their children were asked to complete a series of instruments including surveys, in-depth interviews, and time diaries. These instruments were designed to provide information about work, marriage, child care and parental supervision, management of household tasks, time allocations, coping strategies, and psychological well-being.

The four datasets associated with this data collection are summarized below:

1. The Cortisol Data contains information for a subsample of families that elected to participate in a study of psychological stress. Parents and teenagers who agreed to participate completed an additional two days of ESM data collection. The health survey that was administered reported on a variety of health and lifestyle issues that might affect cortisol (stress hormone) levels such as medication use, consumption of caffeine and alcohol, use of nicotine, timing of menstrual cycle, pregnancy, presence of chronic illness, and respondent's height and weight. Additionally, parents reported on the health of the children (teenagers and kindergartners) participating in the study.
2. The Experience Sampling Method (ESM) Data contains a variety of information related to how individuals spend their time, who they spent it with, and what activities they were engaged in over the course of a typical week. Respondents wore programmed wrist watches that emitted signals (beeps) throughout the day. When possible, family members were placed on identical signaling schedules to provide information on a range of family activities. At the time of each beep, participants were asked to complete a self-report form which asked them to answer a number of open-ended questions about their location, activities, who they were with, and psychological states. Several Likert and semantic-differential scales were used to assess participants' psychological states.
3. The Parent Data contains basic demographic information from respondents as well as detailed information about parents' occupation job duties, income, work schedule, benefits (e.g., medical care, flexible work schedules, and family leave), and the consequences of their jobs (e.g. long hours, job stress, having to work weekends). Additionally, the data contain information about the extent to which parents experienced work-family conflict and what changes might help with better balance of the demands of work and family (e.g., more flexible work hours, more help from spouses with household and child care responsibilities, improved child care, and after-school care arrangements). Parental attitudes toward traditional arrangements, how household tasks were actually divided among family members, and how often the family paid for services (e.g., cleaning, yard work, meal preparation) were also captured. The data also contain information about how children are socialized in families with two working parents. Topics about the frequency with which parents engaged in various activities with their children (e.g., talking, eating meals together, attending religious services), how frequently parents monitored their teenager's activities, and how often they talked with their teenager about school activities, plans for college, career plans, friendships, and peer pressure.
4. The Adolescent Data contains data for sixth through twelfth graders, which focuses on family relationships and experiences, school experiences, paid work, psychological well-being and behavioral problems, and plans for the future (e.g., college, career, and marriage -- including expectations regarding spouses' sharing of responsibility for child care, cooking, chores, and paid work). To allow for comparison of parents' and adolescents' responses to similar questions, several items appear in both the adolescent and parent data. These items include the frequency with which parents and adolescents discuss school events, college and career plans, participation in religious and other activities, gender role attitudes and the division of household tasks within the family, and items measuring depression, stress, and anxiety.

Qualitative Data -- Interviews The main purpose of the interviews was to explore topics addressed in the parent and adolescent surveys in greater detail. Parent interviews were designed to examine how working parents cope with the demands of work and family life. Adolescent interviews touched on similar themes but altered questions to gauge the adolescent's perceptions of their parents work and family lives. Kindergartner interviews were brief and focused on children's after-school and child care arrangements and time spent with parents.