Department of Justice and the Probation Service: Probation Service

Department of Justice and the Probation Service: Probation Service Pay Gap Data

Company Website Industry: Public Administration and Defence, Compulsory Social Security Return

Below is all of the gender pay gap data gathered for Department of Justice and the Probation Service: Probation Service. The headline figures reported are generally those listed under a company's "all employees" figures. Where present, figures for part-time and temporary contract employees are displayed in the additional data blocks on this page. If you'd prefer to see that additional data in tables instead of graphs, hit the toggle on the right hand side of any panel to change the view. If you're looking for some guidance on how to interpret the data, I've written some explanations on the "Understanding the Data" page. Where you see "No Value", a company has either not reported this data, or reported it incorrectly. This may be because they have no part-time or temporary employees, or paid no bonus, for example. If you find any broken report links, please do let me know so that I can replace it where possible.

Year Mean Hourly Pay Gap Median Hourly Pay Gap Mean Bonus Gap Median Bonus Gap Full Report
2022 -1% 1% No Value No Value Report
2023 -5.2% -19.66% No Value No Value Report

2022 Additional Data

Mean Hourly Pay Gap (Part Time)9.59% Mean Hourly Pay Gap (Temp & Fixed Term Contracts)No Value
Median Hourly Pay Gap (Part Time)0% Median Hourly Pay Gap (Temp & Fixed Term Contracts)No Value

Workforce Split

Pay Quartiles

Workforce Split
%
Female 75%
Male 25%
Pay Quartiles
Quartile Female Male
Lower 70% 30%
Lower Middle 80% 20%
Upper Middle 74% 26%
Upper 74% 26%

2023 Additional Data

Mean Hourly Pay Gap (Part Time)-10.84% Mean Hourly Pay Gap (Temp & Fixed Term Contracts)No Value
Median Hourly Pay Gap (Part Time)-40.27% Median Hourly Pay Gap (Temp & Fixed Term Contracts)No Value

Workforce Split

Pay Quartiles

Workforce Split
%
Female 67%
Male 33%
Pay Quartiles
Quartile Female Male
Lower 56% 44%
Lower Middle 63% 37%
Upper Middle 76% 24%
Upper 72% 28%
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