52 datasets found
  1. b

    Permanent special school exclusion rate (% pupils) - WMCA

    • cityobservatory.birmingham.gov.uk
    csv, excel, geojson +1
    Updated Jul 3, 2025
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    (2025). Permanent special school exclusion rate (% pupils) - WMCA [Dataset]. https://cityobservatory.birmingham.gov.uk/explore/dataset/permanent-special-school-exclusion-rate-percentage-pupils-wmca/
    Explore at:
    geojson, json, csv, excelAvailable download formats
    Dataset updated
    Jul 3, 2025
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Description

    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.

    Data is Powered by LG Inform Plus and automatically checked for new data on the 3rd of each month.

  2. Suspensions and permanent exclusions in England: 2022 to 2023

    • gov.uk
    Updated Jul 18, 2024
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    Department for Education (2024). Suspensions and permanent exclusions in England: 2022 to 2023 [Dataset]. https://www.gov.uk/government/statistics/suspensions-and-permanent-exclusions-in-england-2022-to-2023
    Explore at:
    Dataset updated
    Jul 18, 2024
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Department for Education
    Area covered
    England
    Description

    This publication presents statistics on suspensions and permanent exclusions within the academic year 2022 to 2023, across state-funded schools.

    The publication includes data on:

    • the reasons schools report for suspending and permanently excluding pupils
    • suspensions and permanent exclusions by pupil characteristics

    The data has been collected in the school census. Data for earlier years is also included.

  3. Data from: The Political Economies of School Exclusion and Their...

    • beta.ukdataservice.ac.uk
    Updated 2025
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    Ian Thompson (2025). The Political Economies of School Exclusion and Their Consequences: Qualitative Data, 2021-2023 [Dataset]. http://doi.org/10.5255/ukda-sn-857678
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    Dataset updated
    2025
    Dataset provided by
    UK Data Servicehttps://ukdataservice.ac.uk/
    datacite
    Authors
    Ian Thompson
    Description

    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.

  4. Suspension rates by school board

    • ouvert.canada.ca
    • data.ontario.ca
    • +1more
    html, xlsx
    Updated Jun 25, 2025
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    Government of Ontario (2025). Suspension rates by school board [Dataset]. https://ouvert.canada.ca/data/dataset/1f711bda-8953-46df-a09f-a66035a01717
    Explore at:
    xlsx, htmlAvailable download formats
    Dataset updated
    Jun 25, 2025
    Dataset provided by
    Government of Ontariohttps://www.ontario.ca/
    License

    Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
    License information was derived automatically

    Time period covered
    Sep 1, 2007 - Jun 30, 2022
    Description

    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).

  5. W

    NI 114 - Rate of permanent exclusions from school

    • cloud.csiss.gmu.edu
    • data.europa.eu
    • +1more
    xls
    Updated Dec 23, 2019
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    United Kingdom (2019). NI 114 - Rate of permanent exclusions from school [Dataset]. https://cloud.csiss.gmu.edu/uddi/dataset/ni-114-rate-of-permanent-exclusions-from-school
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    xlsAvailable download formats
    Dataset updated
    Dec 23, 2019
    Dataset provided by
    United Kingdom
    License

    http://reference.data.gov.uk/id/open-government-licencehttp://reference.data.gov.uk/id/open-government-licence

    Description

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

  6. c

    National Data on Rates of School Exclusion, Socio-Economic and Educational...

    • datacatalogue.cessda.eu
    Updated Nov 28, 2024
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    Hayden, C., University of Portsmouth (2024). National Data on Rates of School Exclusion, Socio-Economic and Educational Circumstances of Some Local Education Authorities, 1992-1993 [Dataset]. http://doi.org/10.5255/UKDA-SN-3488-1
    Explore at:
    Dataset updated
    Nov 28, 2024
    Dataset provided by
    Social Services Research and Information Unit
    Authors
    Hayden, C., University of Portsmouth
    Area covered
    England and Wales
    Variables measured
    Institutions/organisations, National, Local education authorities
    Measurement technique
    Postal survey, Transcription of existing materials
    Description

    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.

  7. Permanent exclusions and suspensions in England: 2021 to 2022

    • gov.uk
    Updated Jul 20, 2023
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    Department for Education (2023). Permanent exclusions and suspensions in England: 2021 to 2022 [Dataset]. https://www.gov.uk/government/statistics/permanent-exclusions-and-suspensions-in-england-2021-to-2022
    Explore at:
    Dataset updated
    Jul 20, 2023
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Department for Education
    Area covered
    England
    Description

    This publication presents statistics on permanent exclusions and suspensions within the 2021 to 2022 academic year across state-funded schools.

    The publication includes data on:

    • reasons schools report for excluding and suspending pupils
    • exclusions and suspensions by pupil characteristics
    • independent exclusion review panels

    The data has been collected in the school census. Data for earlier years is also included.

  8. w

    Permanent Exclusions from School, Borough

    • data.wu.ac.at
    • data.europa.eu
    xls
    Updated Sep 26, 2015
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    London Datastore Archive (2015). Permanent Exclusions from School, Borough [Dataset]. https://data.wu.ac.at/schema/datahub_io/MWUyNDAzN2EtZDE3NC00OWUwLWIxMDctZDQwOWE2MTQ1NzA5
    Explore at:
    xls(142848.0)Available download formats
    Dataset updated
    Sep 26, 2015
    Dataset provided by
    London Datastore Archive
    License

    http://reference.data.gov.uk/id/open-government-licencehttp://reference.data.gov.uk/id/open-government-licence

    Description

    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.

  9. o

    Expulsion rates by school board

    • data.ontario.ca
    • ouvert.canada.ca
    • +1more
    xlsx
    Updated Jan 12, 2024
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    Education (2024). Expulsion rates by school board [Dataset]. https://data.ontario.ca/dataset/expulsion-rates-by-school-board
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    xlsx(54702), xlsx(25081)Available download formats
    Dataset updated
    Jan 12, 2024
    Dataset authored and provided by
    Education
    License

    https://www.ontario.ca/page/open-government-licence-ontariohttps://www.ontario.ca/page/open-government-licence-ontario

    Time period covered
    Oct 20, 2023
    Area covered
    Ontario
    Description

    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).

  10. g

    NI 114 - Rate of permanent exclusions from school | gimi9.com

    • gimi9.com
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    NI 114 - Rate of permanent exclusions from school | gimi9.com [Dataset]. https://gimi9.com/dataset/uk_ni-114-rate-of-permanent-exclusions-from-school/
    Explore at:
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Description

    🇬🇧 영국

  11. d

    The Impact of Exclusion in School: A Comprehensive Study in New York City,...

    • catalog.data.gov
    • icpsr.umich.edu
    Updated Mar 12, 2025
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    National Institute of Justice (2025). The Impact of Exclusion in School: A Comprehensive Study in New York City, 2010-2015 [Dataset]. https://catalog.data.gov/dataset/the-impact-of-exclusion-in-school-a-comprehensive-study-in-new-york-city-2010-2015-2b5c3
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    Dataset updated
    Mar 12, 2025
    Dataset provided by
    National Institute of Justice
    Area covered
    New York
    Description

    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.

  12. e

    Data from: Children with Special Educational Needs: an analysis

    • data.europa.eu
    • data.wu.ac.at
    html, unknown
    Updated Oct 11, 2021
    + more versions
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    Department for Education (2021). Children with Special Educational Needs: an analysis [Dataset]. https://data.europa.eu/data/datasets/children_with_special_educational_needs-an_analysis?locale=en
    Explore at:
    html, unknownAvailable download formats
    Dataset updated
    Oct 11, 2021
    Dataset authored and provided by
    Department for Education
    License

    http://reference.data.gov.uk/id/open-government-licencehttp://reference.data.gov.uk/id/open-government-licence

    Description

    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

  13. o

    High School Exclusionary Discipline Data in Pennsylvania (SY 2016/2017)

    • openicpsr.org
    spss
    Updated Dec 30, 2023
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    Jacob-Paul Taylor; Malgorzata Zuber; David Shoup (2023). High School Exclusionary Discipline Data in Pennsylvania (SY 2016/2017) [Dataset]. http://doi.org/10.3886/E196441V1
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    spssAvailable download formats
    Dataset updated
    Dec 30, 2023
    Dataset provided by
    Alvernia University
    Authors
    Jacob-Paul Taylor; Malgorzata Zuber; David Shoup
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Pennsylvania
    Description

    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.

  14. b

    Fixed period exclusions - state schools (% pupils) - WMCA

    • cityobservatory.birmingham.gov.uk
    csv, excel, geojson +1
    Updated Jun 3, 2025
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    (2025). Fixed period exclusions - state schools (% pupils) - WMCA [Dataset]. https://cityobservatory.birmingham.gov.uk/explore/dataset/fixed-period-exclusions-state-schools-percentage-pupils-wmca/
    Explore at:
    excel, geojson, csv, jsonAvailable download formats
    Dataset updated
    Jun 3, 2025
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Description

    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%.

    Data is Powered by LG Inform Plus and automatically checked for new data on the 3rd of each month.

  15. Suspensions, exclusions and expulsions - Dataset - data.sa.gov.au

    • data.sa.gov.au
    + more versions
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    data.sa.gov.au, Suspensions, exclusions and expulsions - Dataset - data.sa.gov.au [Dataset]. https://data.sa.gov.au/data/dataset/suspensions-exclusions-and-expulsions
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    Dataset provided by
    Government of South Australiahttp://sa.gov.au/
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    South Australia
    Description

    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.

  16. Characteristics of children in need: 2011 to 2012

    • gov.uk
    Updated Oct 31, 2012
    + more versions
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    Department for Education (2012). Characteristics of children in need: 2011 to 2012 [Dataset]. https://www.gov.uk/government/statistics/characteristics-of-children-in-need-in-england-year-ending-march-2012
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    Dataset updated
    Oct 31, 2012
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Department for Education
    Description

    Reference Id: SFR27/2012

    Publication Type: Statistical First Release

    Publication data: Local Authority data

    Local Authority data: LA data

    Region: England

    Release Date: 31 October 2012

    Coverage status: Final

    Publication Status: Recently updated

    This publication contains final figures on the numbers of children referred to and assessed by children’s social services. It includes information on the characteristics of children in need and information on children who were the subject of a child protection plan for year ending March 2012.

    The key points from this release are:

    Children in need

    • There were 369,400 children in need at 31 March 2012, which was a rate of 325.7 per 10,000 children
    • There were a total of 739,300 episodes of need throughout the year
    • There were 395,300 episodes of need starting between the financial year 1 April 2011 and 31 March 2012, and 369,900 episodes of need that came to an end.

    Referrals and assessments

    • There were 605,100 referrals to children’s social care services in the year ending 31 March 2012.
    • There were 451,500 initial assessments completed in the year ending 31 March 2012, 349,500 (77.4%) of which were completed within 10 working days.
    • The number of initial assessments completed in the year as a percentage of all referrals in the year was 74.6%.
    • There were 220,700 core assessments completed in the year ending 31 March 2012, 166,600 (75.5%) of which were completed within 35 working days.
    • The number of children subject to a section 47 enquiry which started in the 2011-12 year was 124,600. Of these, 56,200 (45.1%) were subject to an initial stage child protection conference. 40,600 (72.3%) initial child protection conferences were held within 15 working days of the start of the section 47 enquiry.

    Children who were the subject of a child protection plan

    • At 31 March 2012, there were 42,900 children who were the subject of a child protection plan.
    • In the year ending 31 March 2012, 52,100 children became the subject of a child protection plan. Of these 7,200 (13.8%) became the subject of a plan for the second or subsequent time.
    • 51,600 child protection plans came to an end in the year. 2,900 (5.6%) of these children had been the subject of a plan for 2 years or more.

    All 28 tables from the publication are contained in the ‘Additional tables’ Excel document on this page.

    Additional analysis of children in need by characteristics available through matching to the National Pupil Database (NPD) was published on 19 March 2013.

    This analysis includes local authority (LA) and England information on matching rates, prevalence of special educational needs and free school meals, attainment at key stage 2, key stage 4 and progression between these key stages, as well as absence and exclusion rates all for children in need. The figures also include absence levels for children in need who were also subject to a child protection plan.

    The following key points from the analysis relate to school age (5 to16 inclusive) children in need:

    • 86.5% matched to the NPD. Matching rates varied at local authority level from 8.5% to 100%.
    • 61.0% had special educational needs and 55.6% were eligible for free school meals
    • 41.3% achieved level 4 or above at key stage 2 in both English and maths
    • 33.7% achieved 5+ A*-C grades at key stage 4
    • 10.5% of school sessions were missed due to absence
    • 0.5% had at least one permanent exclusion from school

    The tables from this additional analysis are contained in the ‘Additional tables’ Excel document on this page. Further details of the matching process and calculations included in these tables can be found in the accompanying methodology document.

    Alison Butler
    01325 735419

    Alison.Butler@education.gsi.gov.uk

  17. u

    Suspension rates by school board - Catalogue - Canadian Urban Data Catalogue...

    • beta.data.urbandatacentre.ca
    • data.urbandatacentre.ca
    Updated Sep 13, 2024
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    (2024). Suspension rates by school board - Catalogue - Canadian Urban Data Catalogue (CUDC) [Dataset]. https://beta.data.urbandatacentre.ca/dataset/gov-canada-1f711bda-8953-46df-a09f-a66035a01717
    Explore at:
    Dataset updated
    Sep 13, 2024
    Description

    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).

  18. A Roadmap to Evidence-Based School Safety: Safe Communities Safe Schools,...

    • icpsr.umich.edu
    ascii, delimited, r +3
    Updated Mar 29, 2023
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    Kingston, Beverly E.; Arredondo Mattson, Sabrina; Dymnicki, Allison; Spier, Elizabeth (2023). A Roadmap to Evidence-Based School Safety: Safe Communities Safe Schools, Colorado, 2016-2020 [Dataset]. http://doi.org/10.3886/ICPSR37913.v1
    Explore at:
    ascii, spss, delimited, sas, r, stataAvailable download formats
    Dataset updated
    Mar 29, 2023
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    Authors
    Kingston, Beverly E.; Arredondo Mattson, Sabrina; Dymnicki, Allison; Spier, Elizabeth
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/37913/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/37913/terms

    Time period covered
    2016 - 2020
    Area covered
    Colorado, United States
    Description

    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.

  19. o

    Replications files for: The Impact of Suspension Reforms on Discipline...

    • openicpsr.org
    Updated Nov 16, 2021
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    Rui Wang (2021). Replications files for: The Impact of Suspension Reforms on Discipline Outcomes: Evidence from California High Schools [Dataset]. http://doi.org/10.3886/E154821V1
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    Dataset updated
    Nov 16, 2021
    Dataset provided by
    Shanghai University of Finance and Economics
    Authors
    Rui Wang
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    California
    Description

    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.

  20. u

    Expulsion rates by school board - Catalogue - Canadian Urban Data Catalogue...

    • beta.data.urbandatacentre.ca
    • data.urbandatacentre.ca
    Updated Sep 13, 2024
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    (2024). Expulsion rates by school board - Catalogue - Canadian Urban Data Catalogue (CUDC) [Dataset]. https://beta.data.urbandatacentre.ca/dataset/gov-canada-2d2c39a7-9318-4db1-8555-a5d105e48619
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    Dataset updated
    Sep 13, 2024
    Description

    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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(2025). Permanent special school exclusion rate (% pupils) - WMCA [Dataset]. https://cityobservatory.birmingham.gov.uk/explore/dataset/permanent-special-school-exclusion-rate-percentage-pupils-wmca/

Permanent special school exclusion rate (% pupils) - WMCA

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geojson, json, csv, excelAvailable download formats
Dataset updated
Jul 3, 2025
License

Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically

Description

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.

Data is Powered by LG Inform Plus and automatically checked for new data on the 3rd of each month.

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