This is the number of permanent exclusions at special schools expressed as a percentage of the number (headcount) of pupils (including sole or dual main registrations and boarding pupils). A permanent exclusion refers to a pupil who is excluded and their name removed from the school register. Such a pupil would then be educated at another school or via some other form of provision. The head teacher of a school can exclude a pupil on disciplinary grounds only. Good discipline in schools is essential to ensure that all pupils can benefit from the opportunities provided by education. The decision to exclude a pupil must be lawful, reasonable, and fair. In addition, schools have a statutory duty not to discriminate against pupils on the basis of protected characteristics, such as disability or race. Schools and LAs must arrange alternative provision from the sixth day of the exclusion of pupils of compulsory school age. Special schools include maintained special schools, non-maintained special schools, and special academies. Pupil and exclusion numbers of 1 to 4 are suppressed to protect pupil confidentiality and numbers at national and regional levels are rounded to the nearest 10. Local authority totals across school types are also rounded to the nearest 10 to prevent disclosure of any suppressed values. Where any number is shown as 0, the original figure was also 0.

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The main objective of this research was to develop a multi-disciplinary understanding of the political economies and consequences of school exclusion across the UK through a home-international comparison.

The motivation for the study was the need to understand the great differences in the rates of permanent school exclusions and suspensions in different parts of the UK. with numbers rising rapidly in England but remaining relatively low or falling in Northern Ireland, Scotland and Wales.

The research was undertaken by the multi-disciplinary (criminology, economics, education, law, psychology, psychiatry, sociology) and multi-site (the universities of Oxford, Cardiff, Edinburgh, Queen’s Belfast, and the LSE) Excluded Lives Research Team. The research was organised into two work strands: A. Landscapes of Exclusion; and B. Experiences of Exclusion. In Strand A work packages examined: the ways in which policies and legal frameworks shape interventions designed to prevent exclusions; the financial costs associated with exclusion; and patterns and characteristics of exclusion. Strand B work packages focussed on families’, pupils’ and professionals’ experiences of the risks and consequences of exclusion.

The data were collected from representative local educational authorities (4 in England, 2 in both Scotland and Wales) and across NI. Our sampling strategy for schools used modelled data, whereby we calculated the rates of exclusions for schools after controlling for pupil characteristics to estimate whether schools had above or below expected levels of exclusion based on their pupil characteristics. For the purposes of sampling, we used the number of temporary exclusions officially recorded over a five-to-seven-year period (depending on the availability of national data in each of the UK jurisdictions). School and local authority staff were selected on the basis of their roles. This data set comprises of interviews from across the UK with Headteachers, Alternative Provision providers in England and Scotland, and national policymakers in Scotland.

Data includes: * board number * board name * number of students suspended * suspension rate This dataset displays the number of students suspended by academic year for all publicly funded school boards in Ontario. The following school types are included: * public * Catholic The following school types are excluded: * private schools * school authorities * publicly funded hospital and provincial schools * care and/or treatment, custody and correctional (CTCC) facilities * summer schools * night schools * adult continuing education day schools Dataset reporting is drawn from data submitted by schools and school boards in the Ontario School Information System (OnSIS).

Number of pupils who are permanently excluded from school in the year expressed as a percentage of the school population

Abstract copyright UK Data Service and data collection copyright owner.

The aims of the survey are:
to identify key variables associated with school exclusions;
to identify local authorities displaying a range of exclusion rates associated with key variables;
to examine in depth the policies and practices of four local education authorities and three schools displaying a range of exclusion rates in each LEA;
to explore the experience of a small number of excluded children, their parent(s)/guardian(s) and key actors in the process of exclusion;
to inform the development of alternatives to exclusions, such as counselling programmes and support structures for schools.
Main Topics:

Type of Local Education Authority; rates of exclusion; socio-economic indicators for areas; educational indicators/circumstances for areas.

Figures for maintained primary, secondary and special schools are as confirmed by Local Authorities as part of the data checking exercise.

Figures for CTCs, academies and non-maintained special schools are as reported by schools and are unconfirmed.

National totals, regional totals and totals across school types have been rounded to the nearest 10.

Includes middle schools as deemed.

The number of permanent exclusions expressed as a percentage of the number (headcount) pupils in Primary, Secondary and Special schools, excluding dually registered pupils in special schools in January 2007.

x less than 5, or a rate based on less than 5.

Figures have been rounded to the nearest 10.

See more on statistics on excluded pupils on the DfE website or read more on permanent and fixed-period exclusions on the DfE website.

Data includes:

• board number
• board name
• number of students expelled
• expulsion rate

This dataset displays the number of students expelled by academic year for all publicly funded school boards in Ontario.

The following school types are included:

• public
• Catholic

The following school types are excluded:

• private schools
• school authorities
• publicly funded hospital and provincial schools
• care and/or treatment, custody and correctional (CTCC) facilities
• summer schools
• night schools
• adult continuing education day schools

Dataset reporting is drawn from data submitted by schools and school boards in the Ontario School Information System (OnSIS).

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This study uses quantitative and qualitative research to fill a gap in the scholarly literature on "what works" in school discipline, climate, and safety and has important implications for educators and justice policymakers nationwide. The quantitative analysis utilized data from 2010-2015 of middle and high school students (N=87,471 students nested within 804 schools and 74 neighborhoods) in New York City. Researchers applied hierarchical modeling methods to analyze effects of neighborhood, school, and student characteristics on: 1) future school disciplinary outcomes; 2) future arrest; and 3) grade advancement. Demographic variables for individual participants include race, gender, and if they are an English language learner. Demographic variables for neighborhoods include race, median income, crime rates, and education levels.

Characteristics and attainment data on pupils with special educational needs (SEN) as well as school absence and exclusion rates for this group of children. Published in response to the SEN Information Act (2008).

Source agency: Education

Designation: Official Statistics not designated as National Statistics

Language: English

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.

This is the number of fixed period suspensions at state-funded primary, state-funded secondary, and special schools expressed as a percentage of the number (headcount) of pupils (including sole or dual main registrations and boarding pupils). A fixed period exclusion refers to a pupil who is excluded from a school but remains on the register of that school because they are expected to return when the exclusion period is completed. The head teacher of a school can exclude a pupil on disciplinary grounds only. Good discipline in schools is essential to ensure that all pupils can benefit from the opportunities provided by education. The decision to exclude a pupil must be lawful, reasonable, and fair. In addition, schools have a statutory duty not to discriminate against pupils on the basis of protected characteristics, such as disability or race. Schools and LAs must arrange alternative provision from the sixth day of the exclusion of pupils of compulsory school age. Fixed period exclusion refers to a pupil who is excluded from a school for a set period of time. A fixed period exclusion can involve a part of the school day and it does not have to be for a continuous period. A pupil may be excluded for one or more fixed periods up to a maximum of 45 school days in a single academic year. This total includes exclusions from previous schools covered by the exclusion legislation. Schools include state-funded schools including schools maintained by the local authority (primary, middle, and secondary), maintained special schools, non-maintained special schools, academies, and special academies. Pupil and exclusion numbers of 1 to 4 or percentages based on these are suppressed to protect pupil confidentiality and numbers at national and regional levels are rounded to the nearest 10. Local authority totals across school types are also rounded to the nearest 10 to prevent disclosure of any suppressed values. Where any number is shown as 0, the original figure was also 0. As pupils can receive more than one fixed period exclusion, in some cases the rate of exclusion may be above 100%.

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Count of students being suspended, excluded or expelled and number of incidents in each category during Term 2 of each year from 2012. Suspension from school means that the student does not attend school for a period of time ranging from one to five school days.

Data includes: * board number * board name * number of students suspended * suspension rate This dataset displays the number of students suspended by academic year for all publicly funded school boards in Ontario. The following school types are included: * public * Catholic The following school types are excluded: * private schools * school authorities * publicly funded hospital and provincial schools * care and/or treatment, custody and correctional (CTCC) facilities * summer schools * night schools * adult continuing education day schools Dataset reporting is drawn from data submitted by schools and school boards in the Ontario School Information System (OnSIS).

Researchers from the University of Colorado Boulder's Center for the Study and Prevention of Violence (CSPV) partnered with educators in 46 middle schools to implement Safe Communities Safe Schools (SCSS). SCSS seeks to prevent and reduce behavioral incidents, address mental and behavioral health concerns, and increase prosocial behavior in the school setting through three core program components: developing a functioning multidisciplinary school team, building capacity around data use, and selecting and implementing evidence-based programs. The study explored research questions in three areas: readiness (whether schools met baseline criteria and experienced changes in readiness over time), implementation (whether the SCSS model was implemented as intended; whether it is feasible, acceptable, and effective when implemented schoolwide), and associated outcomes (effects on school climate, safety, related behavioral and mental health indicators, and academic outcomes). To explore questions in these three areas, CSPV and external evaluators from American Institutes for Research conducted a mixed-methods randomized control trial with a staggered implementation design using qualitative data (open-ended questions on implementation surveys, focus groups) and quantitative data (staff and student school climate data, attendance/truancy rates, and suspension rates, and academic achievement data). This collection is organized into 12 parts and includes administrative school record data, student and staff climate surveys, and fidelity data. School record data from years 1 and 2 of the study include school-level attendance, truancy, and suspension rates, as well as student-level assessment data. Qualitative focus group data is not currently included in the collection.

Minority students are suspended at a disproportionately higher rate compared to others. To reduce racial suspension gaps, four California school districts banned schools from suspending students for willful defiance, a category consisting of relatively minor disruptive offenses. I evaluate the impact of these policies on high school student discipline outcomes using a difference-in-differences strategy that exploits the temporal variation in the enactment of these policies across school districts. The results suggest that while these policies decreased willful defiance out-of-school suspension rates by around 69%, they did not reduce overall out-of-school suspension rates. In fact, the policies significantly increased out-of-school suspension rates among Black students, particularly in schools with a small share of Black teachers. Taken together, the results suggest that the willful defiance suspension bans failed to address implicit and explicit biases in California schools.

Data includes: * board number * board name * number of students expelled * expulsion rate This dataset displays the number of students expelled by academic year for all publicly funded school boards in Ontario. The following school types are included: * public * Catholic The following school types are excluded: * private schools * school authorities * publicly funded hospital and provincial schools * care and/or treatment, custody and correctional (CTCC) facilities * summer schools * night schools * adult continuing education day schools Dataset reporting is drawn from data submitted by schools and school boards in the Ontario School Information System (OnSIS).