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Using Census and deprivation data for iwi planning and evidence

Start with the kaupapa, not the deficit​

Census and deprivation data can help iwi and Māori organisations understand population patterns, access to services, housing pressures, exposure to hazards and structural inequities. They can also support funding applications and advocacy.

But these datasets should not become the definition of a whānau, hapū, iwi or place.

A Māori-centred analysis starts with the aspirations, responsibilities and questions of the people doing the mahi. Crown and research datasets can then add evidence to that kaupapa. The order matters. If the first question is only how deprived are our people?, the analysis has already accepted a deficit frame supplied by someone else.

Useful starting questions include:

  • What are whānau, hapū or iwi trying to strengthen or change?
  • What strengths, networks and resources already exist?
  • What barriers or structural conditions are getting in the way?
  • What decisions about services, investment, whenua or resilience need evidence?
  • What do local knowledge and lived experience tell us that national datasets cannot?
  • What evidence will be useful when dealing with funders, councils or Crown agencies?

What these measures can and cannot say​

NZDep and IMD describe characteristics of areas. They do not measure the worth, capability or wellbeing of the people who live there.

High deprivation scores can be evidence of unequal access to income, housing, employment, transport, health care or other resources. They should not be written as if deprivation is an attribute inherent in Māori communities.

Keep these distinctions clear:

  • area-based measures describe places and populations statistically, not individuals
  • administrative categories are designed for particular statistical purposes
  • Census and deprivation data capture only what their variables and methods measure
  • small-area maps can stigmatise places if labels and interpretation are careless
  • a statistical absence does not mean a local strength, relationship or problem does not exist
  • local kōrero and mātauranga are not qualitative extras added after the official numbers

Use the right geography​

Most social and health indicators are mapped using Stats NZ geographies such as SA1 and SA2. Those geographies are useful statistical containers. They are not Māori rohe and should not be presented as if they are.

Where the kaupapa is iwi or hapū based, a practical approach may be to:

  1. analyse data in the geography in which it is safely available
  2. aggregate or relate results to a rohe or service area where methodologically sound
  3. explain the limitations of that relationship
  4. avoid implying that a statistical boundary defines the people or place

For very small populations, aggregate data enough to protect privacy and avoid unstable rates.

Where to get the data​

Stats NZ Census and Māori outputs​

Use Stats NZ definitions when reporting Stats NZ measures, but do not let a statistical definition become the only way an iwi understands itself.

NZDep​

NZDep is a widely used area-based measure built from Census variables.

IMD​

The Index of Multiple Deprivation uses several indicator domains including employment, income, crime, housing, health, education and access.

Choosing NZDep or IMD​

Use the measure that fits the question rather than selecting whichever produces the strongest-looking map.

NZDep is useful when a recognised summary measure of area-level socioeconomic deprivation is needed. IMD can be useful when the individual domains, such as access or housing, help explain the pattern more clearly.

In either case:

  • state which version and year you used
  • explain the geography
  • do not compare deciles from different measures as if they mean the same thing
  • avoid language that turns a high-deprivation place into a problem community

Put Māori priorities around the analysis​

Rather than creating a Māori-focused framing after the statistical analysis, decide the Māori framing first.

Depending on the kaupapa, that may include:

  • housing security, warmth and ability to remain connected to whenua
  • access to hauora services, transport and pharmacies
  • access to education, training and digital connectivity
  • employment and income security
  • whānau and marae networks that provide support
  • access to whenua, wai and places important to identity and wellbeing
  • exposure to hazards and ability to recover
  • opportunities to strengthen local services and Māori capability

Useful Māori-focused sources include Te Pā Harakeke: Māori housing and wellbeing and HUD's Exploring Māori housing data sources.

Method 1: Build a rohe social profile​

A social profile can bring several evidence sources together without pretending the statistical geography is the rohe itself.

Possible inputs:

  • SA1 or SA2 Census information
  • age and population structure
  • housing and household indicators
  • NZDep or IMD
  • service locations such as marae, hauora providers, kura and community hubs
  • local information the iwi is authorised to use

Useful outputs can include:

  • maps showing patterns in access or structural disadvantage
  • tables comparing areas with regional and national figures
  • maps of existing services and strengths as well as gaps
  • a short interpretation connecting the statistics to the kaupapa

Show counts and rates where useful. Explain any mismatch between statistical geographies and the area the iwi is planning for.

Method 2: Map access, not only deprivation​

A decile alone does not explain why people face barriers.

Combine population and deprivation information with questions such as:

  • travel time to hauora services
  • access to schools, training and pharmacies
  • public transport and road access
  • digital connectivity
  • proximity to marae and Māori services

This can shift the question from where are deprived people? to where are systems failing to provide reasonable access?

IMD's access domain can support this kind of analysis. Local travel-time analysis may add more useful detail.

Method 3: Connect health evidence carefully​

Health statistics can support iwi planning and advocacy, but avoid treating ethnicity and deprivation as explanations in themselves.

Where a health outcome differs, look for the structural and service conditions that may contribute, and use Māori health research and local knowledge to interpret the pattern.

Do not turn a correlation on a map into a causal claim.

Method 4: Hazards, resilience and recovery​

Combining social indicators with flood, coastal, landslide or other hazards can help identify where resources may be needed before and after an event.

The map should also recognise capability:

  • marae and local response hubs
  • whānau networks
  • local knowledge of access and safe places
  • existing community and iwi services
  • transport, communications and supply capacity

A vulnerability map that shows only what a place lacks can give a distorted picture of how people actually respond.

Useful supporting material includes EHINZ social vulnerability work and hazard datasets from councils and national providers.

Funding applications are one use, not the purpose of the data​

Funders often ask for evidence of need. You can meet that requirement without allowing the funding template to define the kaupapa.

A strong evidence pack can show:

  • the outcome iwi or whānau are seeking
  • what local experience and Māori-led evidence show
  • relevant population and area statistics
  • structural barriers and service gaps
  • existing strengths and capability
  • where resources could make a practical difference
  • how success will be understood and measured

Maps should support that story, not reduce it to a red high deprivation surface.

Language matters​

Prefer language that describes conditions and systems rather than labelling people.

For example:

  • areas experiencing high socioeconomic deprivation rather than deprived communities
  • limited access to primary care rather than high-need people when access is the issue
  • housing pressure or the specific indicator rather than a vague deficit label

Use the wording that the evidence actually supports.

GIS workflow​

In QGIS or ArcGIS Pro:

  1. obtain the correct geographic boundaries for the data release
  2. join NZDep, IMD or Census tables using the correct geographic code
  3. verify the join with record counts and known places
  4. keep years and geographies explicit
  5. calculate rates only with suitable denominators
  6. aggregate where privacy or statistical stability requires it
  7. add local or Māori-held information only where there is authority and an appropriate purpose
  8. record the source, method and limitations with the output

For public web maps, publish aggregated information where small numbers could identify people or stigmatise a small place.

Before publishing​

Ask:

  • Does the map serve an iwi or whānau question, or mainly reproduce the data provider's categories?
  • Does it show strengths and capability where they matter to the kaupapa?
  • Could the symbology or wording stigmatise a place?
  • Are statistical areas being mistaken for Māori rohe?
  • Are small populations protected?
  • Have limitations and structural context been stated?
  • Would the people represented recognise the story the map tells?

The purpose is not to make uncomfortable evidence disappear. It is to make sure the evidence is used without turning Māori people and places into a collection of deficits.

Check the source before mapping the pattern​

Use the 2018 Census iwi-data case when working with iwi population series, GIS data for Aotearoa for current public sources, and Te Whata and other Māori GIS projects for iwi-oriented data products.

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