How we write about statistics and ethnicity
Ethnicity facts and figures brings together complex statistical data from government departments, services and other organisations.
Users range from members of the public with a personal interest, to the media, NGOs, academics, specialists and policy-makers.
The information presented on Ethnicity facts and figures aims to be trustworthy, accessible and of value to a wide variety of audiences. Written commentary and data visualisations are clear, consistent and especially careful with the language used to describe race and ethnicity.
This approach was described by the Office for Statistics Regulation as ‘a model for how all statistics should be developed’.
Clear, concise and straightforward language
Content written for Ethnicity facts and figures should be:
- user-centred (putting the needs of readers first and foremost)
- in plain English, avoiding specialist jargon whenever possible
- clear, concise and correct
- accessible to the general reader (even when explaining complex statistical ideas)
- in the appropriate tone of voice
- careful to avoid misrepresenting the data or misleading users
The guidance presented here is in line with GOV.UK requirements for any service hosted on the GOV.UK platform. It draws on evidence-based, user-tested principles for content designers across the UK government.
It is also informed by the Office of National Statistics (ONS) style guide, which states:
Plain English is clear language, with no jargon, that is understood by all readers. This isn’t “dumbing down” information, but opening up statistics and statistical commentary to everyone. Users don’t stop understanding text because it’s written clearly, but they stop understanding when it is complex.
Writing about ethnicity
In general, Ethnicity facts and figures follows the broad guidelines on ethnicity set out in the ONS style guide. This section covers the exceptions, as well as style points on a few matters not covered by the ONS style guide. All these were backed by user research for the project.
For more specific guidance, please refer to the Style guide A to Z.
BAME/BME (Black, Asian and minority ethnic/Black and minority ethnic)
Don’t use this alternative to ‘ethnic minorities’ because:
- the UK’s ethnic minorities include White ethnic minorities
- it highlights particular groups while others are omitted – for example, it includes Black and Asian people but not people of a Mixed ethnicity
Ethnicity versus race
Use the word ‘ethnicity’ on the website instead of race because:
- data collection asks respondents for their ethnicity not their race
- using consistent terminology helps users understand the content
Read Ethnicity in the UK for more on how ethnicity is described on Ethnicity facts and figures, and how ethnicity data is gathered and presented.
Major and minor ethnic groups
User testing showed this was open to misinterpretation, so use ‘broad’ and ‘specific’ ethnic groups instead.
A term defining groups in relation to the White majority was not well received in user testing. Instead of using ‘non-White’, write either:
- ‘ethnic minority groups’ when comparing with White British people
- ‘other ethnic groups’ when comparing with White people (including White ethnic minorities)
Order of ethnic categories
Generally, ONS orders categories in order of size. However, in research labs users were sometimes offended when White was placed first in commentary, charts and tables. They were also confused by the way ethnic categories found in different contexts were presented in varying orders.
Ethnic groups are therefore ordered alphabetically in charts and tables, with ‘Other’, and occasionally ‘Unknown’, as a final category.
In user testing, ‘People from a Black Caribbean background’, ‘the Black ethnic group’ and ‘Black people’ were all acceptable phrases. ‘Blacks’ was not.
Writing about statistics
Ethnicity facts and figures commentary is accessible, objective and impartial. Content has been designed not to present an explanation for the ethnic disparities the data shows, but to present that data in a way that can be understood by the widest possible audience.
Complex statistical concepts are explained as simply as possible using plain English. They are expressed consistently throughout text using ‘boilerplate’ (reusable content), which has been modified where necessary for the requirements of individual measures.
Sometimes, a two-tier explanation is needed: a high-level explanation for the general user, and more detailed and technical text for the specialist (which appears in the Methodology section).
Measure page guidance and the Style guide A to Z contain more guidance on writing about statistics.
Tone of voice
Commentary should be accurate and objective, but also approachable, helpful and human. It should avoid unnecessary formality and technical vocabulary, while remaining a professional, reliable source of information.
Users must, above all, feel confident that the information they read is trustworthy, unbiased and politically independent.
Testing showed that a neutral presentation of the facts was more credible than commentary attempting to explain them. Language that users suspect of trying to excuse or rationalise ethnic disparity risks sounding like a marketing sales pitch.
For this reason, aim for a clear, simple and impartial style. Let the facts speak for themselves and avoid value judgements.
This is neutral:
Across all ethnic groups, girls were more likely to achieve A* to C in English and Maths GCSE than boys – 67% of girls did so, compared to 59% of boys
This is judgemental:
Across all ethnic groups, girls did best at achieving A* to C in English and Maths GCSE, while boys did worst – 67% of girls did so, compared to only 59% of boys
Ethnicity facts and figures is divided into topics, sub-topics and measure pages based on consultation and engagement.
The structure of the measure page has been developed based on findings from user research. The content for each section of the measure reflects the needs (and available time) of the different audiences for that section:
- all users can rapidly read and absorb high-level findings (‘Main points’ and ‘Summaries’) and charts and tables
- all users can read important context in ‘Things you need to know’, the first accordion section of text
- users looking for detailed background information can open ‘What the data measures’ and ‘The ethnic categories used in this data’
- specialist users refer to the more technical ‘Methodology and type of data’ and ‘Data source details’, and can download the raw data for their own analysis
Measure page guidance contains a detailed guide on the way information is structured in the measure page.