I've charted the latest June data below:
(Right click to enlarge)
Some commentary.
1/ This disproportion accounts substantially for the high rate of Maori child poverty. While Pacific children are also disproportionately poor, they are more likely to have working parents.
2/ The Maori numbers are dropping. There are 9.5 percent fewer on Sole Parent Support now than at June 2014.
3/ But, some with children aged 14 and older are now buried away in JobSeeker statistics. I suspect these numbers will be relatively high in regions like Northland and the East Coast
4/ The falling Maori teenage birth rate may make a positive reduction in the future OR the delayed births may still appear in the benefit numbers
I have included the notes regarding ethnicity that accompany the data tables.
Ethnicity data is self-identified and multiple ethnicities may be chosen by an individual as fits their preference or self-concept. Multiple selected ethnicities are then prioritised into a hierarchy. The Māori ethnicity has the highest priority in this hierarchy, followed by Pacific peoples. NZ European has the lowest priority. This is to ensure that smaller and politically significant ethnic groups do not get overwhelmed by the larger ethnic groups. A single ethnicity is assigned to an individual based on this hierarchy. Ethnic groups do not currently align with Statistics New Zealand ethnicity groupings.
4 comments:
I looked at the data for All supporting benefits working age people.
Then did a comparison to population. ..
European 112,000 actual benefits /65 % NZ population / 40% of benefit total numbers
Maori 98,000 actual benefits / 15% NZ population / 35% of benefit total numbers
Pacific 23,000 actual benefits / 8% NZ population / 08% of benefit total numbers
All others 47,000 actual benefits / 14% of NZ population / 27 % of total numbers . Others include Asian.
Asian suppressed info / 12 % NZ population / suppressed
The figures of over 100% represent people with dual ethnic affiliation
Pacific 8% of population and 8% of welfare numbers
European 65% of population and 40% of welfare numbers
Maori 15% population 35% welfare numbers
Others 14% of population 14% of welfare numbers
The others number here includes Asian 11% population, welfare number suppressed.
Also there is an interesting figures for: unspecified.
Nothing is easily clear with welfare stats, and nothing adds up to 100%.
What interests me is , what is the Asian breakdown, but Nanny will not say.
I repeat these figures for all welfare [ not super ] and the double entry ethnicity, fudges the entire thing. Population adds up to over 100%
I can not get my spreadsheet on here, but I have it .
Using ethnicity to classify people is outdated and divisive. this is so clearly shown in the comment above. I have been saying this for years in various forums, no-one seems to get it.So if someone is 10% maori, by definition they are classed as JUST maori. I would guess if people were classified by their majority bloodline, the number given for maori in NZ would crash, as would the %. This artificial use of profiling people on race is totally inaccurate, and unhelpful in the extreme, but it perpetuates the victim narrative so certain people , mostly minority maori ehthnicity, can grab power and money for themselves, at the expense of the rest.
I'm surprised you have used the term "child poverty" Lindsay??
First anon, I noted in a recent paper the inherent difficulties of classification by ethnicity, and to an extent I agree with you. But in forming policy the focus should be on where the social problems lie and govt doesn't regard this approach as "outdated". If you don't want to talk about the ethnicity of beneficiaries then we could talk about gender, age and geographical location. But they would all correlate with ethnicity. See:
https://www.familyfirst.org.nz/wp-content/uploads/2016/05/Child-Poverty-and-Family-Structure-FULL-REPORT-1.pdf
p34
Second anon, Perhaps if you look at the same link it explains (after a fashion) why I use the term "child poverty". That is the phrase the media commonly uses to describe children living in relative low income families so I use their language to explain why the incidence has risen.
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