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Welsh Government
Data Provider: Welsh Government Experimental Statistics Number of teacher sickness absences opened by month and absence type
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[Collapse]School medium type[Filtered]
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School medium type 1[Filter]
[Collapse]Sector[Filtered]
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Sector 1[Filter]
[Collapse]Tenure[Filtered]
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Tenure 1[Filter]
[Collapse]Local authorityData not available for Wrexham for 2020/21.[Filtered]
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Local authority 1[Filter]
Year[Filtered]
Measure1
[Collapse]Absence type[Filter]
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Absence type 1
[Collapse]Month[Filter]
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Month 1
[Collapse]TotalClick here to sortTotal
Click here to sortShort-termClick here to sortLong-termMore than 20 workings days lost.
[Collapse]Total37,1301,77038,900
TotalSeptember3,5052753,780
October3,3951403,535
November4,8702905,160
December2,775952,875
January3,9852354,220
February2,7701302,900
March5,2901805,470
April1,7901201,910
May2,7351402,870
June3,5101403,645
July2,510202,530
August*Numbers greater than zero but less than five.1015

Metadata

Title

Number of teacher sickness absences opened by month and absence type

Last update

July 2023 July 2023

Next update

July 2024 (provisional)

Publishing organisation

Welsh Government

Source 1

School Workforce Annual Census

Contact email

EducationWorkforceData@gov.wales

Designation

Experimental statistics

Geographical coverage

Local authorities

Languages covered

English and Welsh

Data licensing

You may use and re-use this data free of charge in any format or medium, under the terms of the Open Government License - see http://www.nationalarchives.gov.uk/doc/open-government-licence

General description

The data covers different aspects of the school workforce in Wales, using the data collected from the School Workforce Annual Census (SWAC).

Data reference periods

From 2020/21 onwards.

Rounding applied

* = numbers greater than zero but less than five. Figures have been rounded to the nearest 5.

Keywords

SWAC; Teachers; Workforce; Sickness; Absence

Statistical quality

The information collected for 2021 and 2022 has not undergone a formal final validation period. However, various stages of automated validation and sense-checking are built into the process to ensure a high quality of data to inform policy making.