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Police Perceptions of Maori - Rethinking Crime and Punishment

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A clinical survey which does not allow for grey areas.<br />

Some suggested that the research may have harmful consequences:<br />

I find this research insulting, a waste <strong>of</strong> money <strong>and</strong> time. Of all the years I<br />

have worked in the police, you will always get some people who are racist etc<br />

but this is right across the community both work wise <strong>and</strong> private life. I was<br />

brought up with ‘there is good <strong>and</strong> bad in every race’ <strong>and</strong> that can be applied<br />

to jobs etc as well. When you put out papers such as this one you people<br />

create <strong>and</strong> encourage problems.<br />

These issues <strong>of</strong> possible research bias <strong>and</strong> potential harm from the findings are<br />

important concerns to raise <strong>and</strong> they are considered in the final section which discusses<br />

the interpretation <strong>of</strong> the results <strong>of</strong> the research.<br />

Data presentation <strong>and</strong> analysis<br />

The data are presented as percentages <strong>of</strong> the total who replied to each question.<br />

Unless otherwise stated, they add to a 100 in each column in each table. When more<br />

than 10 people did not respond or have answered ‘don’t know’ to a particular question<br />

the percentage is given in the text, the relevant table or in a footnote. Percentages<br />

have been rounded to the nearest whole number so that sometimes they may add to 99<br />

or 101.<br />

Statistical tests have been used at a number <strong>of</strong> points. Those readers without a<br />

technical background may find these difficult to follow. For this reason, the technical<br />

detail has been largely kept to footnotes <strong>and</strong> to one section <strong>of</strong> the text which those<br />

without a technical background can skip over.<br />

Tests <strong>of</strong> statistical significance <strong>of</strong> differences have been used for comparing the<br />

responses <strong>of</strong> different groups. For readers with statistical knowledge, Chi-squared has<br />

been used for data divided into categories <strong>and</strong> t-tests have been used to compare the<br />

significance <strong>of</strong> differences between means. The important point for the reader without<br />

technical knowledge is that these tests make it possible to determine whether the<br />

differences between groups are likely to be due to chance or whether they are likely to<br />

be real. The key feature to look for is the probability or p value. If p

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