What’s ethnicity got to do with it?
Aotearoa’s growing ethnic diversity and the implications for policy
EeMun Chen / 22 April 2020
Evaluation and research specialist EeMun Chen looks at what happens when people of multiple ethnicities meet up with the Census and other official statistics in Aotearoa.
The 2018 Census of Population and Dwellings has taken a bit of a hammering as a result of having the lowest response rates for the past five surveys, as well as for the new ‘digital first’ model used to collect the data. Māori have been particularly vocal about this, and the independent review into Census 2018 stated that only 68% of Māori responded to the Census.
That response rate is very concerning, as it means the Census has most likely not captured those communities and demographics for which we desperately need good, robust data, including youth, rural, low socio-economic means, weak social connections and networks, and high mobility and/or homeless.
However, a voice that hasn’t been heard in the conversation on the 2018 Census so far is from New Zealand’s culturally and linguistically diverse communities. It’s an important perspective, particularly as our official statisticians grapple to understand and reflect a New Zealand that is becoming more and more ethnically diverse.
I have lingering doubts about whether we, as filler-outers of the Census and other forms, collectively know what ‘ethnicity’ is. What’s more, will ethnicity even continue to matter as diversity increases? Will all this data on ethnicity be used appropriately for designing government policy and service delivery?
What is ethnicity?
Ethnicity has been measured in some way or other through the New Zealand Census since the middle of the 19th century, but the way in which it’s been defined and measured has changed.
Until the 1986 Census, the ethnicity question was based around racial ancestry, with people of mixed race being asked to report their ‘proportions of blood’. By the 1970s there was increasing opposition to that race-based approach, both from the public and from the users of statistics. New Zealand demographics were changing and becoming increasingly complex, through ethnic intermarriage. People were also finding it harder to calculate their percentages of ancestry, and were increasingly self-identifying.
So in the 1986 ‘ethnic origin’ question there was a shift to asking people to ‘tick the box or boxes which apply to you’. The question didn’t specify whether respondents should base this on ancestry or self-identified cultural affiliation, but the form of the question clearly allowed for people to self-identify if they chose. Censuses since then have continued this approach.
The importance of self-identified cultural affiliation was confirmed by a 2009 study for Stats NZ, which found that people viewed ethnicity as both subjective and self-identified, and objective and based on race and ancestry. It appears that us Census respondents flip between self-identification and a more objective notion of race or ancestry.
‘I’m a New Zealander’
The importance of self-identification has been reflected in another dynamic in the development of the New Zealand Census.
My husband usually writes ‘New Zealander’ on the Census form, as he doesn’t identify as ‘New Zealand European’. ‘What do I have to do with Europe?!’, he says, ‘I’m from Christchurch — I’m a New Zealander.’ He’s even been known to write ‘Southern Man’ on the occasional form.
The ‘New Zealand European’ category was introduced in the 1991 Census to appease people who have European ancestry but also strong attachments to New Zealand built up over a number of generations. The continuing development of national identity later saw a large increase in ‘New Zealander’ responses in the 2006 Census, given in the ‘Other’ option. After a public media campaign encouraging people to give that response, just under 430,000 people identified as a ‘New Zealander’ on their form that year.
A 2009 review considered whether there should be some additional question about nationality, distinct from the ethnicity question. In the event, no nationality-related question was added and the ‘New Zealander’ response to the ethnicity question would continue to be added to the ‘Other ethnicity’ category.
In recent Censuses, people identifying as ‘New Zealander’ made up the vast majority of the ‘Other ethnicity’ category. In 2013, there were 65,973 ‘New Zealanders’ out of the 67,752 categorised as ‘Other ethnicity’ — or 97%. Recently released statistics from the 2018 Census show that 58,053 people were classified as ‘Other ethnicity’, a decline from 2013.
Where are you from really?
The Census and countless other forms now ask: ‘Which ethnic group do you belong to? Select all that apply to you.’ For many people, this is a harmless question and an easy one-second tick.
Me, I’m part of a visible minority — Chinese — that gets aggregated into the group ‘Asian’. Asian is an ultra-diverse group encompassing Korean, Chinese, Indian, Pakistani, Japanese and so on. China itself has 55 ethnic minority groups, in addition to the Han majority.
My parents are Chinese. They came from Malaysia in the 1960s — Dad from East and Mum from West Malaysia — to live in Christchurch to study. I was born in Christchurch. People like me are referred to as ‘bananas’ — yellow on the outside, white on the inside. Recent migrants from mainland China don’t think of me as ‘real Chinese’.
So how do I convey all this by ticking a box, or multiple boxes?
The answer is I don’t — I leave the form with just ‘Chinese’. And so in the Census — and the National Health Index, education databases, and countless other databases — I am absorbed under ‘Asian’, a category covering about half of humanity. This probably reflects how I’m treated by the world around me, but it doesn’t line up with how I perceive and experience my identity.
I don’t usually indicate ‘New Zealander’ and ‘Asian’ in Census or other forms, but I wonder if I should, as it provides more and better information about my identity.
How we record multiple ethnic identities
Before 2004, if you reported multiple ethnicities Stats NZ would allocate you to one ethnic category based on an arbitrary ranking of the ethnic responses. One problem with this approach was that Pacific peoples and other minority groups were increasingly undercounted, as Māori were at the top of the prioritisation schedule. The 2004 review of the measurement of ethnicity recommended discontinuing the ‘prioritisation of multiple ethnic responses to one group’. In line with the review’s recommendations, Stats NZ now uses the ‘total response’ and ‘single and combined response’ classifications instead.
‘Total response’ means that the number of people who have reported each ethnic category are recorded, no matter how many categories each person reported. Accordingly, the sum will be more than the real number of people involved, and people of multiple ethnicity are effectively hidden. In 2018, 11% of the population reported their ethnicity in more than one ethnic group. That’s almost 540,000 people — 10,000 more than the population of the entire Wellington region.
By contrast, the ‘single and combined response’ classification method assigns you to a unique ethnic category that reflects the mix of responses you provide. So if you report multiple ethnicities of, say, Eritrean and ‘New Zealander’, you would be reported under ‘African/Other Ethnicity’.
The problem with using ‘Total response’, which is pretty much what statisticians and organisations reporting ethnicity data use, is that as the number of people with mixed heritage grows, the percentages will both exaggerate European people as a proportion of New Zealand’s total population and exaggerate the rise of minority ethnicities.
In 2018, using ‘total response’, European were 70%, Māori 17%, and Asian 15% (up from 12% in 2013) of the population. By contrast, under the ‘single and combined response’ method, European-only are 60% (falling from 65% in 2013), Māori-only 8%, and Asian-only 14%.
So you can see that, in the wrong hands, poorly contextualised sets of statistics could act as a powerful tool for anti-immigration agendas.
Research from the US suggests that, in terms of ‘the contexts in which they are raised and their social identities and affiliations’, people from mixed families look more like white Europeans than they do like minorities, except for those who are partly African-American. This blurring of the relative differences from European appears to be particularly marked for people from mixed Asian-European families — they will be viewed as European, English will tend to be the language of choice at home, and their friends will tend to be European.
In New Zealand there have been some, mostly quantitative, studies of the effect of intermarriage and multiple ethnicities, and mostly focusing on Māori as one of the ethnicities. The international and New Zealand literature and data shows that making ethnic choices for children is complex, and that many children of ethnic intermarriage will choose to emphasise one ethnicity over another.
In Aotearoa there is a whole new generation of people whom governments are not geared up to understand or respond to. Nearly a quarter of people under 15 years old (23% — almost 120,000 kids) identify with more than one ethnic group. Government needs to understand how these young people, as well as adults like me with multiple cultures and diverse heritage, perceive and experience their identity, and understand how might this affect key areas such as employment, wellbeing, housing, education, and health.
Heck, governments aren’t geared up to understand and respond to minority ethnic communities full stop. The terrible events in Christchurch brought into sight just how much ethnic communities are removed from policy discussion. Government agencies were warned many times of the rise of alt-right groups and the growing discrimination against Muslim people here.
In New Zealand today there is increasing ethno-racial diversity and fluidity — including evidence of ethnic mobility where people’s ethnicity changes between Censuses. So how best can data collection, data interpretation and data visualisation support a ‘true’ picture of our diversity? And what might this mean for evidence-based policy?
From data to policy
Census data helps government plan services, such as which District Health Boards need more funding, where schools should be built, where roads should go, and where public transport should be maintained.
But what happens when the ‘right’ data isn’t being collected, and the data that’s collected and reported doesn’t truly reflect the people it’s supposed to be about? It means a significant risk of policy-makers and decision-makers putting funding in the wrong places or developing the wrong initiatives or programmes. This is at the heart of the conversation about Census 2018.
I believe we need to revisit several areas. First, we need to consider whether ‘ethnicity’, as self-identified cultural affiliation, is still relevant and important for data collection and for policy evidence. If we do think it’s still relevant, then we need to rethink how we understand, report and use ethnicity data.
I think ethnicity is still relevant, but we need to acknowledge that how form-fillers think of ‘ethnicity’ will vary from person to person. Indeed, scholars and policy-makers are still struggling to come to a single definition of ethnicity, and concepts of ethnicity are undergoing continuous transformation. In spite of this, it does appear to be a measure that has some predictive value and can be helpful for targeting and delivering public services.
The trick will be ensuring we don’t think of ethnicity as one-dimensional and that we make space for the increasing number of people with multiple identities.
How we report, understand and use ethnicity data
As part of a more effective approach in this area, at the very least all users of ethnicity data should consider ‘Single and combined response’ data as well as ‘Total response’.
‘Single and combined response’ data doesn’t lend itself to neat graphs of aggregate statistics, but it provides a richer and more nuanced understanding of how individuals of mixed ethnicity may encounter particular issues. Some of this analysis has been done before in New Zealand, but not as a matter of course. For example, an older paper from Tahu Kūkutai describes how individuals who identify with being a combination of Māori and non-Māori but who identify more strongly with non-Māori tended to be better off economically than all other Māori. On the flip side, those who identified more strongly as Māori had similar socio-economic and demographic attributes to those who were Māori-only.
Those results are similar in nature to the US research mentioned above. Together those studies, along with more recent research showing a high degree of mixed ethnicity among New Zealand-born Asians, challenge the popular perception of ‘Māori’ and ‘Asian’ as single, homogenous categories. They also show the danger of focusing too much, and placing too much weight, on simple and singular measures of ethnicity as a pathway into public policy interventions. This raises questions about how ethnicity is used in funding schools and District Health Boards.
Studies to date have been relatively broad-brush, Census data-driven, and exploratory. To really get at the heart of what might matter and be helpful to the increasingly large proportion of people with multiple ethnicities, we need more qualitative studies on their lived experience. For example, how do people of different ages within this population perceive their ethnicity, and to what extent do they face different levels of discrimination and racism? Answers to those questions could provide insights into, for example, unconscious bias or racism in frontline health decision-making.
At the most basic level, any research into people with multiple ethnicities provides recognition and a much-needed voice for this understudied population. And in particular, a greater focus on qualitative research will provide policy-makers with a much more accurate and nuanced understanding of the lived experiences and needs of this group, which now stands at more than half a million people.
About the author
EeMun Chen is a Senior Consultant with MartinJenkins working from the Auckland office. She is an evaluation and research professional who also provides advisory, strategic and research work in the economic development, innovation, migration, diversity and wellbeing fields. Her depth of experience across a number of areas allows her to ask the right questions and find the necessary data and information to enable her to add value and provide a robust evidence base for client projects.
EeMun joined MartinJenkins in 2011 after a 10-year career in research, evaluation and policy roles in the then-Ministry of Economic Development (MED) and the British Medical Association in the UK. She has an MSc in Industrial and Organisational Psychology and a BA in Psychology from the University of Canterbury. She is a trained facilitator in LEGO® Serious Play, a member of New Zealand’s and Australia’s professional evaluation organisations (ANZEA and AES) and a member of the Data Visualization Society.