Our people

Corrections is an equal opportunity employer, and we work on retaining and developing our workforce.


Māori and Pacific peoples continue to be over-represented in the Corrections system. As such, it is important for Corrections to ensure that our staff are representative of the full spectrum of the offender population.

More than 20% of staff identified as Mäori in 2015/16, and approximately 9% as Pacific Peoples. A high number of staff identify themselves as having a multi-ethnic background, and this is reflected in the high level of the ‘other’ category8.


Voluntary turnover at Corrections was just below 9% in 2015/16. This rate has remained between 9% and 10% for the past five years, so dropping below 9% is a notable change.

Turnover is not currently a cause for concern and is below average levels for the Public Sector. This low level of turnover reflects Corrections’ emphasis on valuing and developing our staff, and the sense of achievement that can come from work that keeps communities safe and working to improve the lives of New Zealanders.

Pay equality

The gender pay gap at Corrections was approximately 2% in 2015/16. This is significantly below the Public Sector average of 14%, and is consistent with Corrections’ results over the previous five years.

Driving continuous improvement: The Well Functioning Site Framework

The Well Functioning Site (WFS) framework is a strengths-based approach to completing a review of the quality of our practice and performance at each site. The aim is to support the development and strengthening of high functioning teams and sites. Strengths-based means that the evaluation looks at what is done well, and at the areas that need developing and/or improving. The framework assists senior leaders to look beneath the presenting issues to understand the drivers and barriers for quality practice. It is designed for the local sites to assist their learning and create a culture of continuous improvement.

The framework covers four domains that focus on how effective we are being for offenders, how well we are supporting staff, how we work in collaboration with the community and how we are perceived by that community. The framework has a clearly defined process and assessment criteria, and is run over one week with reports provided to the relevant site manager, Regional Commissioner and National Office senior leaders.

Five graphs, first four are bar graphs the fifth is a line graph. First graph, titled “Staff gender proportion by age group”. Data: under 30, male 41.64%, female 58.36%. 30 to 40, male 50.08%, female 49.92%. 40 to 50, male 49.92%, female 48.90%. 50 to 60, male 59.71%, female 40.29%. Over 60, male 67.04%, female 32.96%. Not Advised, male 43.23%, female 56.77%. Total, male 53.90%, female 46.10%. End of graph. Second graph titled “Number of full time equivalent positions”. Data: 2008/09 7,185; 2009/10 7,805; 2010/11 7,369; 2011/12 7,594; 2012/13 7,676; 2013/14 7,628; 2014/15 7,674; 2015/16 7,659. End of graph. Third graph titled “Ethnicity of staff”. Data: 2010 – NZ European 55.99%, Māori 22.87%, Pacific Peoples 9.59%, Other 28.63%. 2011 – NZ European 57.44%, Māori 22.61%, Pacific Peoples 8.79%, Other 28.68%. 2012 – NZ European 57.86%, Māori 22.51%, Pacific Peoples 8.64%, Other 28.84%. 2013 – NZ European 58.23%, Māori 21.85%, Pacific Peoples 8.60%, Other 29.25%. 2014 – NZ European 54.76%, Māori 20.61%, Pacific Peoples 8.27%, Other 26.33%. 2015 – NZ European 55.69%, Māori 20.98%, Pacific Peoples 8.30%, Other 26.64%. 2016 – NZ European 55.17%, Māori 20.72%, Pacific Peoples 8.56%, Other 27.06%. End of graph. Fourth graph titled “Number of staff by age group and gender”. Data: Under 30 – Male 244, Female 342. 30 to 40 – Male 596, Female 594. 40 to 50 – Male 1002, Female 959. 50 to 60 – Male 1298, Female 876. Over 60 – Male 712, Female 350. Not Advised – Male 380, Female 499. Total – Male 4232, Female 3620. End of graph. Fifth graph titled “Percentage voluntary turnover”. Data: 2009/10 8.12%; 2010/11 9.27%; 2011/12 9.44%; 2012/13 9.28%; 2013/14 9.12%; 2014/15 9.30%; 2015/16 8.82%.

8 The percentages for each year in the graph will add up to more than 100%, because staff can identify as more than one ethnicity.

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