Context

Movehub city ranking as published on http://www.movehub.com/city-rankings

Content

movehubqualityoflife.csv

Cities ranked by
Movehub Rating: A combination of all scores for an overall rating for a city or country.
Purchase Power: This compares the average cost of living with the average local wage.
Health Care: Compiled from how citizens feel about their access to healthcare, and its quality.
Pollution: Low is good. A score of how polluted people find a city, includes air, water and noise pollution.
Quality of Life: A balance of healthcare, pollution, purchase power, crime rate to give an overall quality of life score.
Crime Rating: Low is good. The lower the score the safer people feel in this city.

movehubcostofliving.csv

Unit: GBP
City
Cappuccino
Cinema
Wine
Gasoline
Avg Rent
Avg Disposable Income

cities.csv

Cities to countries as parsed from Wikipedia https://en.wikipedia.org/wiki/List_of_towns_and_cities_with_100,000_or_more_inhabitants/cityname:_A (A-Z)

Acknowledgements

Movehub

http://www.movehub.com/city-rankings

Wikipedia

https://en.wikipedia.org/wiki/List_of_towns_and_cities_with_100,000_or_more_inhabitants/cityname:_A

In practice, heads of state and government are investigated and prosecuted while in office if evidence suggests they committed a crime. A 100 score is earned where all the following conditions are met: 1) criminal allegations against heads of state and government are investigated while they are in office, 2) heads of state and government are prosecuted when investigations find evidence of possible wrongdoing, and 3) legal punishment is imposed if/when they are found guilty. A 50 score is earned where any of the following conditions apply: 1) not all allegations are investigated while they are in office, 2) not all investigations that find evidence of criminal activity result in prosecution, or 3) not all guilty verdicts result in legal punishment. A 0 score is earned where at least one of the following conditions apply: 1) allegations against heads of state and government are rarely investigated while they are in office, 2) criminal evidence rarely results in prosecution, or 3) guilty verdicts rarely result in legal punishment. A 0 also applies if the heads of state and government have immunity, therefore making it impossible in practice to investigate, prosecute or punish them. For variable descriptions, please refer to: https://www.africaintegrityindicators.org/data. For the methodology, please refer to: https://static1.squarespace.com/static/5e971d408be44753edfb976c/t/60a55f343d36117866628867/1621450563745/AII10+-+Methodology.docx+%281%29.pdf.

Ranking of LSOAs according to their score in the Crime domain.

In law, the head of state and government can be investigated and prosecuted while in office if evidence suggests they committed a crime. A YES score is earned where the law doesn't protect the heads of state and government from being investigated and prosecuted while in office if evidence suggests they committed a crime. A NO score is earned where a law protects/gives immunity to the heads of state and government from being investigated and prosecuted while in office if evidence suggests they committed a crime. For variable descriptions, please refer to: https://www.africaintegrityindicators.org/data. For the methodology, please refer to: https://static1.squarespace.com/static/5e971d408be44753edfb976c/t/60a55f343d36117866628867/1621450563745/AII10+-+Methodology.docx+%281%29.pdf.

This dataset includes publicly available data published primarily by the Pennsylvania Department of Education and the Pennsylvania Office of Safe Schools. The dataset was created by combining several publications by the Pennsylvania Department of Education, including the 2017 School Fast Fact database, 2016-2017 Academic Performance database, and the 2017 Keystone Score database. The dataset includes institutional (school-wide) variables for every public high school in Pennslyvania (n = 407 ). The data includes information surrounding each institution's socio-economic status, racial composition, academic performance, and type of and total use of exclusionary discipline (in-school suspension, out-of-school suspension, and expulsion) for the school year 2016-2017. The dataset also includes neighborhood information for each school location. This data was collected from AreaVibes, a website known for its ability to guide individuals in their search for ideal residential areas in the United States and Canada. AreaVibes deploys a unique algorithm that evaluates multiple different data points for each location, including amenities, cost of living, crime rates, employment, housing, schools, and user ratings. This dataset deployed AreaVibes to input the physical addresses of each high school in order to retrieve the livability score for the surrounding neighborhoods of these educational institutions. Furthermore, the website was instrumental in collecting neighborhood crime scores, offering valuable insights into the levels of criminal activity within specific geographic zones. The crime score takes into account both violent crime and property crime. However, higher weights are given to violent crimes (65%) than property crime (35%) as they are more severe. Data for calculation by Areavibes is derived from FBI Uniform Crime Report.School discipline is crucial for ensuring safety, well-being, and academic success. However, the continued use of exclusionary discipline practices, such as suspension and expulsion, has raised concerns due to their ineffectiveness and harmful effects on students. Despite compelling evidence against these practices, many educational institutions persist in relying on them. This persistence has led to a troubling reality—a racial and socioeconomic discipline gap in schools. This data is used to explore the evident racial and socioeconomic disparities within high school discipline frameworks, shedding light on the complex web of factors that contribute to these disparities and exploring potential solutions. Drawing from social disorganization theory, the data explores the interplay between neighborhood and school characteristics, emphasizing the importance of considering the social context of schools.

TIAS 17-920.4 cover memo. Visit https://dataone.org/datasets/sha256%3A0fd5f6c7017fed3fe2c912b96119a49a2b83e61f530ab67c948bc1a1e1c62380 for complete metadata about this dataset.

The Pittsburgh Youth Study (PYS) is part of the larger "Program of Research on the Causes and Correlates of Delinquency" initiated by the Office of Juvenile Justice and Delinquency Prevention in 1986. PYS aims to document the development of antisocial and delinquent behavior from childhood to early adulthood, the risk factors that impinge on that development, and help seeking and service provision of boys' behavior problems. The study also focuses on boys' development of alcohol and drug use, and internalizing problems.

PYS consists of three samples of boys who were in the first, fourth, and seventh grades in Pittsburgh, Pennsylvania public schools during the 1987-1988 academic year (called the youngest, middle, and oldest sample, respectively). Using a screening risk score that measured each boy's antisocial behavior, boys identified at the top 30 percent within each grade sample on the screening risk measure (n=~250), as well as an equal number of boys randomly selected from the remainder (n=~250), were selected for follow-up. Consequently, the final sample for the study consisted of 1,517 total students selected for follow-up. 506 of these students were in the oldest sample, 508 were in the middle sample, and 503 were in the youngest sample.

Assessments were conducted semiannually and then annually using multiple informants (i.e., boys, parents, teachers) between 1987 and 2010. The youngest sample was assessed from ages 6-19 and again at ages 25 and 28. The middle sample was assessed from ages 9-13 and again at age 23. The oldest sample was assessed from ages 13-25, with an additional assessment at age 35. Information has been collected on a broad range of risk and protective factors across multiple domains (e.g., individual, family, peer, school, neighborhood). Measures of conduct problems, substance use/abuse, criminal behavior, mental health problems have been collected.

This collection contains data and syntax files for delinquency constructs. The datasets include constructs on the frequency and level of criminal and delinquent activities, including theft, violence, weapons used, delinquency, drug-selling, white collar crime, as well as police contacts and past incarceration. Additionally, the collection includes data on delinquency risk (high vs. low) and the associated weight.

The delinquency constructs were created by using the PYS raw data. The raw data are available at ICPSR in the following studies: Pittsburgh Youth Study Youngest Sample (1987 - 2001) [Pittsburgh, Pennsylvania], Pittsburgh Youth Study Middle Sample (1987 - 1991) [Pittsburgh, Pennsylvania] , and Pittsburgh Youth Study Oldest Sample (1987 - 2000) [Pittsburgh, Pennsylvania].

TIAS 09-417 cover memo. Visit https://dataone.org/datasets/sha256%3Ab6203929f09f37a80602a37013cee699fdc27d3c3bd2ac713f3851897ffd5c70 for complete metadata about this dataset.