Analysis and presentation of results
Data should be analysed and presented in a way that is most useful to users of the data, with consideration of what kind of analysis would be most likely to reveal any inequalities that require action. In Scotland, many ethnic groups are small in number which could lead to statistical unreliability when analysing data and hinder publication of figures because of the need to avoid identification of individuals.
The problem of small numbers can be overcome by combining categories under a section heading, for example combining the counts of people who responded "Arab, Scottish Arab or British Arab" and "Other, please write in (for example, SIKH, JEWISH)" category within Section F. This is not an ideal solution as it can hide inequalities that occur between each of the separate categories.
If it is necessary to combine categories B, C, D E and F, or a subset thereof, you must label the combined results as "Minority Ethnic" and provide a footnote detailing which ethnicities have been included in this grouping. For example, in an analysis providing breakdowns for "White - Scottish", "White - Other British", "White - Other" and "Minority ethnic groups" the footnote should be to the effect of:
For the purposes of the analysis presented here, 'White: Other' includes 'Irish', 'Polish', 'Gypsy/Traveller', 'Roma', 'Showman/Showwoman' and 'other white ethnic groups'. 'Minority ethnic groups' includes 'Mixed or multiple ethnic groups', 'Asian, Scottish Asian or British Asian', 'African, Scottish African or British African', 'Caribbean or Black', 'Arab, Scottish Arab or British Arab' or any other ethnic groups
Where an analysis provides breakdowns for "White – Scottish", "White – Other British" and "Minority ethnic groups" the footnote should be to the effect of:
For the purposes of the analysis presented here, 'Minority ethnic groups' includes 'Irish', 'Polish', 'Gypsy/Traveller', 'Roma', 'Showman/Showwoman', 'other white ethnic groups', 'Mixed or multiple ethnic groups', 'Asian, Scottish Asian or British Asian', 'African, Scottish African or British African', 'Caribbean or Black', 'Arab, Scottish Arab or British Arab' or any other ethnic groups
'Minority ethnic' is preferred over terms such as 'other ethnicities', 'ethnic minority' or 'BAME/BME'. This is because these terms can imply that minority ethnic individuals are a homogeneous group, or focus on the perceived 'non-whiteness' of the word 'ethnic', whereas several groups categorised as 'White' could be considered minority ethnic groups in certain contexts, including Irish, Polish and Gypsy/ Travellers.
Additionally, the term 'Black' is controversial with many stakeholders, particularly in the African community. As such care should be taken to use the full "Caribbean or Black" label, and not just "Black" or "Caribbean and Black". This is because there are some people who find the term Black offensive, and others who feel very strongly that their ethnic group is Black and take pride in that term. It is important that data are presented in a way that is respectful of both these points of view.
It is important that the results should be presented in as much detail as possible. It is better to list all of the categories and where possible the figures. If the numbers are too small to publish then suppress the figures for that category with an explanation of why this has been done, taking care to ensure that if only one figure is suppressed, that figure can then not be calculated by simple subtraction from the totals displayed. Consideration should be given to increasing sample sizes by aggregating several years of data where that can be done.
Comparing data across question versions
The categories are slightly different across different versions of the question. The previous iteration of this guidance provided methods for combining groups to compare data collected between the 2001 and 2011 census questions. This is detailed in an annex at the end of this document. Similar guidance on comparing between the current version and previous version is not yet available but may be provided in the future.
An intersectional analysis gives an insight into how a combination of socio-demographic characteristics might relate to specific forms of disadvantage. For example disadvantage for a young minority ethnic woman may be different to an older minority ethnic man.
There is an increasing awareness that taking an intersectional approach to research, policy making and operational decisions is important. This is because intersectionality can give insight into the experiences of different groups in society, and how particular characteristics can combine to impact on an individual's experiences. However, there is not always disaggregated data available to support such an approach. This is likely to mean that the information on which important decisions are made is not fully representative of the population it is intending to measure.
For example, data on demographic characteristics may be collected by a public body, but not disaggregated in an intersectional way due to issues around sample size and risk of disclosing an individual's identity. In these cases, organisations should not risk disclosing information about an individual's ethnicity.
Where sample size and quality allows, data should be disaggregated, including by sex, gender reassignment, race, religion or belief, age, disability, and sexual orientation, where combinations of these factors can result in discrimination, disadvantage and inequality. Being able to identify cases where combinations of factors are resulting in disadvantage enables policies to be developed and action taken to address these issues.
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