The 1991 Census Basic Community profiles present 57 tables containing summary characteristics of persons and/or dwellings for Local Government Areas (LGA) in Australia. This table contains data relating to family type by number of dependent offspring (usually resident (a)) by annual parental income. Counts are of families with offspring, based on place of enumeration on census night which excludes adjustment for under-enumeration however in determining family and household type visitors to dwellings are excluded and usual residents who are temporarily absent are included. The data is by LGA 1991 boundaries. Periodicity: 5-Yearly. This data is ABS data (cat. no. 2101.0 & original geographic boundary cat. no. 1261.0.30.001) used with permission from the Australian Bureau of Statistics. The tabular data was processed and supplied to AURIN by the Australian Data Archives. The cleaned, high resolution 1991 geographic boundaries are available from data.gov.au. For more information please refer to the 1991 Census Dictionary. Please note: (a) A maximum of 3 temporarily absent dependent offspring can be counted in each household. (b) Comprises two parent families where a parent present did not state their income or a parent was temporarily absent. (c) Comprises cases where in a two parent family, both parents did not state their income or were temporarily absent; origin a one parent family, the parent did not state their income or was temporarily absent.

Household income statistics by household type (couple family, one-parent family, non-census family households) and household size for Canada, provinces and territories, census divisions and census subdivisions.

Three waves of data were collected, in addition to detailed information about program group members' participation and engagement in SHM services. The first wave of data was collected when families first enrolled in the SHM study, just prior to being randomly assigned. Husbands and wives were asked to complete a set of baseline instruments that capture socio-demographic and other characteristics such as employment, education, household composition, marital quality and satisfaction, and prior life experiences. The second wave of data was collected approximately 12 months after families first entered the study, through an adult follow-up survey and an observational study. All husbands and wives were asked to complete a follow-up survey (10,181 respondents). The survey includes measures of household composition, marital stability, marital quality, parental psychological well-being, parental employment and economic outcomes, material and financial hardship, social support and networks, coparenting relationship, parenting, father involvement, and child well-being and adjustment. A subsample of families was also selected to participate in a series of videotaped observations of couple, coparenting, and parent-child interactions (1,511 families responded). Observational measures include warmth and support, positive communication, and anger and hostility in the couple relationship, as well as positive responsive parenting, hostile-competitive parenting, measures of adolescents' warmth and support, adolescents' positive communication skills, and adolescents' anger and hostility, and infant behavioral measures. The third wave of data was collected approximately 30 months after families first entered the study, and included three types of data: an adult survey, a youth survey and direct child assessments. The 30-month adult survey (9,369 respondents) mirrored the 12-month survey to a large extent, but included an expanded set of child and parenting items. Focal children who were 2.5 to 8 years old at the follow-up point participated in a set of direct child assessments (2,539 respondents) measuring cognitive development and self regulation. Focal children who were 8.5 to 17 years old at the follow-up point participated in a youth survey (1,134 respondents) which measured youths' psychological adjustment, school engagement, academic achievement, parent-child relationship, perceptions of and reactivity to inter-parental conflict, dating and romantic relationships, and risky behaviors. The Supporting Healthy Marriage (SHM) evaluation was launched in 2003 to develop, to implement, and to test the effectiveness of a program aimed at strengthening low-income couples' marriages as one approach for supporting stable and nurturing family environments and parents' and children's well-being. The evaluation was led by MDRC and was sponsored by the Office of Planning, Research and Evaluation in the Administration for Children and Families, United States Department of Health and Human Services.The SHM program was a voluntary yearlong marriage education program for low-income married couples who had children or were expecting a child. The program provided a series of group workshops based on structured curricula designed to enhance couples' relationships; supplemental activities to build on workshop themes; and family support services to address participation barriers, connect families with other services, and reinforce curricular themes. The study sample consists of 6,298 couples (12,596 adult sample members) who were expecting a child or had a child under 18 years old at the time of study entry. The sample consists primarily of low-to-modest income, married couples with diverse racial and ethnic backgrounds. In each family, one child was randomly selected to be the focus of any child-related measures gathered in the data collection activities. These children ranged from pre-birth to 14 years old at the time of enrollment in the study. Follow-up interviews were conducted at 12 and 30 months after baseline data collection. More detail is provided in the study documentation. Datasets: DS0: Study-Level Files DS1: Baseline Data DS2: 12-Month Survey DS3: Management Information System (MIS) Extended Activities DS4: Management Information System (MIS) Family Support Coordinator Contacts DS5: Management Information System (MIS) Marriage Education Groups DS6: Management Information System (MIS) Payments DS7: Management Information System (MIS) Referrals DS8: Observational Study - Adult Dataset DS9: Observational Study - Child Dataset DS10: Observational Study - Inter-rater Reliability Dataset DS11: 30-Month Outcomes Dataset DS12: 30-Month Survey DS13: 30-Month Youth Survey Dataset DS14: Direct Child Assessment Dataset DS15: Child Longitudinal File DS16: Standardized Baseline Dataset ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates read...

One in four families in Toronto does not have the income necessary to live a healthy life and participate fully in their community. Inequality can be based on geography; some neighbourhoods experience greater poverty than others. People from Aboriginal and racialized communities, newcomers to Canada, people with disabilities, youth and children, lone parents, and others are dealing with the biggest challenges. Many people work more than one job, yet still have low incomes. Having an education is not proving to be a pathway to well-paid jobs for almost 1/4 of graduates. More than 1 million visits to food banks in Toronto means families, especially with children, are unable to put food on the table every day. Housing costs can take more than 70% of household income, yet can be poorly maintained or inadequate for the size of the family. The Phase 1 engagement (November, 2014 to February, 2015) of the Toronto Poverty Reduction Strategy aimed to seek feedback in four key areas: The drivers of poverty in Toronto; A vision for the kind of Toronto we want; What we are doing that helps address poverty and what else could be done; and, An engagement plan for the next phase of the work. The data contained in the Excel file titled Phase 1 Questionnaire Responses, was collected through an online questionnaire. The information recorded in the PDF file, titled Phase 1 Community Conversations was collected by community members using a PDF Facilitation Guide developed by City staff. The information recorded in the PDF file, titled Phase 1 Multisector Dialogue was collected by staff and table facilitators at a full day workshop on November 28, 2014. Phase 2 engagement (February, 2015 to April, 2015) built on community input from Phase 1 and gathered public feedback on key actions for various themes, (Access to Services; Child Care; Employment and Income, Food Access; Housing; and Transportation), and on principles that should guide City decisions. The Phase Two data includes two Excel files: The Days of Dialogue data that was transcribed into Excel from the ten community meetings. The Online Feedback data that was collected through an online feedback form. For more information visit TOProsperity <w:LsdException Locked="false" Priority="48

This dataset contains replication files for "The Fading American Dream: Trends in Absolute Income Mobility Since 1940" by Raj Chetty, David Grusky, Maximilian Hell, Nathaniel Hendren, Robert Manduca, and Jimmy Narang. For more information, see https://opportunityinsights.org/paper/the-fading-american-dream/. A summary of the related publication follows. One of the defining features of the “American Dream” is the ideal that children have a higher standard of living than their parents. We assess whether the U.S. is living up to this ideal by estimating rates of “absolute income mobility” – the fraction of children who earn more than their parents – since 1940. We measure absolute mobility by comparing children’s household incomes at age 30 (adjusted for inflation using the Consumer Price Index) with their parents’ household incomes at age 30. We find that rates of absolute mobility have fallen from approximately 90% for children born in 1940 to 50% for children born in the 1980s. Absolute income mobility has fallen across the entire income distribution, with the largest declines for families in the middle class. These findings are unaffected by using alternative price indices to adjust for inflation, accounting for taxes and transfers, measuring income at later ages, and adjusting for changes in household size. Absolute mobility fell in all 50 states, although the rate of decline varied, with the largest declines concentrated in states in the industrial Midwest, such as Michigan and Illinois. The decline in absolute mobility is especially steep – from 95% for children born in 1940 to 41% for children born in 1984 – when we compare the sons’ earnings to their fathers’ earnings. Why have rates of upward income mobility fallen so sharply over the past half-century? There have been two important trends that have affected the incomes of children born in the 1980s relative to those born in the 1940s and 1950s: lower Gross Domestic Product (GDP) growth rates and greater inequality in the distribution of growth. We find that most of the decline in absolute mobility is driven by the more unequal distribution of economic growth rather than the slowdown in aggregate growth rates. When we simulate an economy that restores GDP growth to the levels experienced in the 1940s and 1950s but distributes that growth across income groups as it is distributed today, absolute mobility only increases to 62%. In contrast, maintaining GDP at its current level but distributing it more broadly across income groups – at it was distributed for children born in the 1940s – would increase absolute mobility to 80%, thereby reversing more than two-thirds of the decline in absolute mobility. These findings show that higher growth rates alone are insufficient to restore absolute mobility to the levels experienced in mid-century America. Under the current distribution of GDP, we would need real GDP growth rates above 6% per year to return to rates of absolute mobility in the 1940s. Intuitively, because a large fraction of GDP goes to a small fraction of high-income households today, higher GDP growth does not substantially increase the number of children who earn more than their parents. Of course, this does not mean that GDP growth does not matter: changing the distribution of growth naturally has smaller effects on absolute mobility when there is very little growth to be distributed. The key point is that increasing absolute mobility substantially would require more broad-based economic growth. We conclude that absolute mobility has declined sharply in America over the past half-century primarily because of the growth in inequality. If one wants to revive the “American Dream” of high rates of absolute mobility, one must have an interest in growth that is shared more broadly across the income distribution.

Car Insurance Dataset

This dataset contains information about customers and their car insurance details. It includes the following columns:

• id: Customer's record ID
• birthdate: Customer's birthday (mm/dd/yyyy)
• marital_status: Customer's marital status
• car_use: Reason for having a car: private, commercial
• gender: Customer's gender
• kids_driving: Number of kids driving the same car as the customer
• parent: Whether the customer is a parent
• education: Customer's education level
• car_make: Car's manufacturer
• car_model: Car's model
• car_color: Car's color
• car_year: Year of car manufacture
• claim_freq: Number of times customer has claimed insurance
• coverage_zone: Coverage zone for insurance policy
• claim_amt: Amount claimed in insurance
• household_income: Household income

This dataset can be used for various analyses and predictions related to car insurance, including customer segmentation, claim prediction, and risk assessment.

Abstract copyright UK Data Service and data collection copyright owner.

This dataset, comprising a subset of a large-scale longitudinal study, the British Household Panel Survey (BHPS) (held at the UK Data Archive under SN 5151), was created as part of a study that examined the life course of the entrepreneur. Variables from the BHPS that were of interest in studying various aspects of accumulation and application of resources over the life course of the entrepreneur, their household and their business, were compiled and studied in relation to transition into and income/earnings from self-employment/entrepreneurship. A final dataset was created by merging data from Waves 1-18 of BHPS, using the BHPS person identification number (PID). In order to integrate individual and household life course events and resources, original BHPS household data files were also merged with the individual level data following a match of the PID and the BHPS household identification number (XHID). This merged file will benefit research into entrepreneurship and self-employment that takes a life course approach.

Further information may be found on the ESRC Income from Self-employment: Development of an Innovative Life Course Model award webpage. Further information on the BHPS may be found on the Institute for Social and Economic Research BHPS website.


Main Topics:

The merged dataset includes variables covering individual, household and business life courses. These include individual childhood resources (e.g. parents social class, education and employment backgrounds, childhood education), respondents' education, employment, health, life styles, wealth, household composition, household resources and responsibilities and business/self-employment details, including the size of the business, earnings from the business, ownership structures, etc. Also included are demographic/household characteristics including ethnic group, age, gender, social class and socio-economic status.

The aim of this study is to throw light on why inequality in the distribution of income in Sweden fell from the mid-1920s to the second part of the 1950s. For this reason the project decided to collect income information referring to different years from a sample of households for one Swedish city. A database was created by coding tax records and other documents for the city of Göteborg, the second largest city in Sweden.

The determination of which years to investigate was critical. For analysing changes over time it was thought as essential to have roughly equal numbers of years between years studied. Further, it was thought advisable to avoid years with too much macroeconomic turmoil as well as the years of the two World Wars. Balancing the resources for the data collection between the size of a sub sample and the number of subsamples, it was decided to assemble data for four years. The years 1925, 1936, 1947 and 1958 was chosen to investigate. It should be pointed out that the year 1947 was preferred to the following years as large social insurance reforms leading to increases in pension benefits and the introduction of child allowances were put in effect in 1948.

Household is defined from registers kept in the archives (Mantalslängder). A household is defined as persons with the same surname living in the same apartment or single-family house. This means that there can be people belonging to more than two generations in the same household; siblings living together can make up a household as well. Foster children are included as long as they are registred at the same address. Adult children are considered to be living in the household of their parents as long as they are registred at the same address. In almost all cases, servants and tenants not belonging to the household are treated as separate households.

Purpose:

The aim of this study is to throw light on why inequality in the distribution of income in Sweden fell from the mid-1920s to the second part of the 1950s

The aim of this study is to throw light on why inequality in the distribution of income in Sweden fell from the mid-1920s to the second part of the 1950s. For this reason the project decided to collect income information referring to different years from a sample of households for one Swedish city. A database was created by coding tax records and other documents for the city of Göteborg, the second largest city in Sweden.

The determination of which years to investigate was critical. For analysing changes over time it was thought as essential to have roughly equal numbers of years between years studied. Further, it was thought advisable to avoid years with too much macroeconomic turmoil as well as the years of the two World Wars. Balancing the resources for the data collection between the size of a sub sample and the number of subsamples, it was decided to assemble data for four years. The years 1925, 1936, 1947 and 1958 was chosen to investigate. It should be pointed out that the year 1947 was preferred to the following years as large social insurance reforms leading to increases in pension benefits and the introduction of child allowances were put in effect in 1948.

Household is defined from registers kept in the archives (Mantalslängder). A household is defined as persons with the same surname living in the same apartment or single-family house. This means that there can be people belonging to more than two generations in the same household; siblings living together can make up a household as well. Foster children are included as long as they are registred at the same address. Adult children are considered to be living in the household of their parents as long as they are registred at the same address. In almost all cases, servants and tenants not belonging to the household are treated as separate households.

Purpose:

The aim of this study is to throw light on why inequality in the distribution of income in Sweden fell from the mid-1920s to the second part of the 1950s

This dataset contains student responses to each item on the Views of Climate and Learning (VOCAL) survey since 2018. These responses are aggregated at the state level by grade and student group to protect student privacy.

The VOCAL survey is designed to provide information on student perceptions of school climate. There are two reports with different types of data: responses to individual items and aggregate index scaled scores that combine item responses. For more information about the VOCAL survey, please visit the VOCAL home page.

This dataset is one of two containing the same data that is also published in the VOCAL state dashboard: VOCAL Index Scaled Scores and Favorability VOCAL Item Response Scores

List of Items by Index and Topic

Engagement - Cultural Competence

• ENGCLC1: Adults working at this school treat all students respectfully, regardless of a student's race, culture, family income, religion, sex, or sexual orientation.
• ENGCLC2: Teachers at this school accept me for who I am.
• ENGCLC3: My textbooks or class materials include people and examples that reflect my race, cultural background and/or identity.
• ENGCLC4: Within school, I am encouraged to take upper level courses (honors, AP).
• ENGCLC5: Students from different backgrounds respect each other in our school, regardless of their race, culture, family income, religion, sex, or sexual orientation.
• ENGCLC6: Students like to have friends who are different from themselves (for example, boys and girls, rich and poor, or classmates of different color).
• ENGCLC7: Students are open to having friends who come from different backgrounds (for example, friends from different races, cultures, family incomes, or religions, or friends of a different sex, or sexual orientation).
• ENGCLC8: I read books in class that include people who are similar to me (for example, we look the same, speak the same, or live in similar neighborhoods).
• ENGCLC9: Adults working at this school treat all students with respect.
• ENGCLC10: In my academic classes, I work with groups of students who are from different backgrounds (for example, students from different races, cultures, family incomes, or religions, or students of a different sex or sexual orientation).

Engagement - Participation

• ENGPAR1: I get the chance to take part in school events (for example, science fairs, art or music shows).
• ENGPAR2: My parents feel respected when they participate at our school (e.g., at parent-teacher conferences, open houses).
• ENGPAR3: I feel welcome to participate in extra-curricular activities offered through my school, such as, school clubs or organizations, musical groups, sports teams, student council, or any other extra-curricular activities.
• ENGPAR4: My teachers use my ideas to help my classmates learn.
• ENGPAR5: I have a choice in how I show my learning (e.g., write a paper, prepare a presentation, make a video).
• ENGPAR6: My teachers will explain things in different ways until I understand.
• ENGPAR7: When I need help, my teachers use my interests to help me learn.
• ENGPAR8: My teachers ask me to share what I have learned in a lesson.
• ENGPAR9: When I am stuck, my teachers want me to try again before they help me.
• ENGPAR10: In my classes, my teachers use students' interests to plan class activities.
• ENGPAR11: In at least two of my academic classes, I can work on assignments that interest me personally.
• ENGPAR12: If I finish my work early, I have a opportunity to do more challenging work.
• ENGPAR13: My classmates behave the way my teachers want them to.
• ENGPAR14: In at least two of my academic classes, students are asked to teach a lesson or part of a lesson.
• ENGPAR15: In my classes, students teach each other how they solved a problem.
• ENGPAR16: Students plan and work on group projects that solve real-world (everyday) problems.
• ENGPAR17: In at least two of my academic classes, students plan and work on projects that solve real-world problems.
• ENGPAR18: In my academic classes, students review each other's work and provided advice on how to improve it.
• ENGPAR19: In my classes, teachers use open-ended questions that make students think of many possible answers.
• ENGPAR20: I can connect what I learn in on class to what I learn in other classes.
• ENGPAR21: In my academic classes, students wrestle with problems that don't have an obvious answer.
• ENGPAR22: In my academic classes, I am asked to apply what I know to new types of complex tasks or problems.
• ENGPAR24: In my academic classes, students work on long-term group projects (more than one month in length) that they independently carry out.
• ENGPAR25: Students plan and work on group projects that solve real problems.

Engagement - Relationships

• ENGREL1: Students respect one another.
• ENGREL2: Students respect each other in my school.
• ENGREL3: My teachers care about me as a person.
• ENGREL4: Students at my school get along well with each other.
• ENGREL6: Teachers are available when I need to talk with them.
• ENGREL13: Adults at our school are respectful of student ideas even if the ideas expressed are different from their own.
• ENGREL14: My teachers promote respect among students.
• ENGREL15: In my classes, students work well together in groups.

Environment - Discipline Environment

• ENVDIS1: Students have a voice in deciding school rules.
• ENVDIS2: School rules are fair for all students.
• ENVDIS3: Students help decide school rules.
• ENVDIS4: School staff are consistent when enforcing rules in school.
• ENVDIS5: Teachers give students a chance to explain when they do something wrong.
• ENVDIS6: The consequences for the same inappropriate behavior (e.g., disrupting the class) are the same, no matter who the student is.
• ENVDIS7: Teachers give students a chance to explain their behavior when they do something wrong.
• ENVDIS8: My teachers will first try to help (guide) students who break class rules, instead of punishing them.
• ENVDIS9: My teachers will first try to help students who break class rules, instead of punishing them.

Environment - Instructional Environment

• ENVINS1: Students help each other learn without having to be asked by the teacher.
• ENVINS2: My teachers are proud of me when I work hard in school.
• ENVINS3: My teachers help me succeed with my schoolwork when I need help.
• ENVINS4: In class, students help each other learn.
• ENVINS5: My teachers set high expectations for my work.
• ENVINS8: My teachers believe that all students can do well in their learning.
• ENVINS9: My school work is challenging (hard) but not too difficult.
• ENVINS10: My classwork is hard but not too hard.
• ENVINS11: My teachers support me even when my work is not my best.
• ENVINS12: The things I am learning in school are relevant (important) to me.
• ENVINS13: Teachers ask students for feedback on their classroom instruction.
• ENVINS14: When I am home, I like to learn more about the things we are learning in school.
• ENVINS15: My teachers inspire confidence in my ability to be ready for college or career.
• ENVINS16: In this class, other students take the time to listen to my ideas.
• ENVINS17: In my classes, it is OK for me to suggest other ways to do my work.
• ENVINS18: Teachers go over my work with me so I can improve it before it is graded.
• ENVINS19: In my school, teachers focus on my understanding of the material and not on my grades.
• ENVINS20: In my academic classes, there is a good balance between students having to master subject content and being able to explore topics that interest them.
• ENVINS21: In my classes, mistakes or even failure on an assignment are viewed as an important part of our learning.
• ENVINS22: Students are given multiple opportunities to show that they have mastered their classwork.
• ENVINS23: Teachers go over my work with me so I can improve it.

Environment - Mental Environment

• ENVMEN1: In school, I learn how to manage (control) my feelings when I am angry or upset.
• ENVMEN2: In school, I learn how to manage (control) my feelings when I am upset.
• ENVMEN3: Our school offers guidance to students on how to mediate (settle) conflicts (e.g., arguments, fights) by themselves.
• ENVMEN4: If I need help with my emotions (feelings), effective help is available at my school.
• ENVMEN6: I have access to effective help at school if I am struggling emotionally or mentally.
• ENVMEN7: At our school, students learn to care about other students' feelings.
• ENVMEN9: The level of pressure I feel at school to perform well is unhealthy.

Safety - Bullying/Cyber-bullying

• SAFBUL1: If I tell a teacher or other adult that someone is being bullied, the teacher/adult will do something to help.
• SAFBUL2: I have been punched or shoved by other students more than once in the school or on the

NATSEM child social exclusion index (2006) by SLA boundaries in Australia. Brisbane SLAs have been aggregated up to Local Council Electoral Wards and ACT SLAs have been aggregated up to Statistical Sub-Divisions. The index is calculated based on data from the ABS Census of Population and Housing 2006. In the data, the lowest CSE quintile represents the highest risk of child social exclusion. The Child Social Exclusion Index estimates social exclusion risk at a small area level for children aged 0 - 4 , 5 - 15 and 0 - 15 years. The index is based on characteristics of children's parents, families and households, and includes data about parental partnership status, employment and volunteerism, family educational attainment and occupation, household income, housing, transport and internet connection. The index depends on the variables chosen to represent social exclusion and the methodology used to summarise these data. Prior to the indexation, NATSEM remove any SLAs that had low cell counts or had a very high non-response rate in the census. Low cell counts mean that even a very small change in the data can mean a large percentage change (so one extra child at risk of social exclusion may represent a 33 per cent increase if there are only 3 children in the SLA). To deal with the issue of low cell counts, NATSEM excluded from the analysis SLAs with fewer than 30 children in either the 0-4 or 5-15 age groups. These SLAs are noted with an asterisk (*).

This table is part of a series of tables that present a portrait of Canada based on the various census topics. The tables range in complexity and levels of geography. Content varies from a simple overview of the country to complex cross-tabulations; the tables may also cover several censuses.

The 1991 Census Basic Community profiles present 57 tables containing summary characteristics of persons and/or dwellings for Local Government Areas (LGA) in Australia. This table contains data relating to annual parental income. Counts are of Families with offspring, based on place of enumeration on census night which; includes overseas visitors; excludes Australians overseas; and excludes adjustment for under-enumeration. The data is by LGA 1991 boundaries. Periodicity: 5-Yearly. This data is ABS data (cat. no. 2101.0 & original geographic boundary cat. no. 1261.0.30.001) used with permission from the Australian Bureau of Statistics. The tabular data was processed and supplied to AURIN by the Australian Data Archives. The cleaned, high resolution 1991 geographic boundaries are available from data.gov.au. For more information please refer to the 1991 Census Dictionary. Please note: (a) Comprises two parent families where a parent present did not state their income or a parent was temporarily absent. (b) Comprises cases where in a two parent family, both parents did not state their income or in a one parent family, theparent did not state his/her income.