The UK Statistics Agency’s Inclusive Data Taskforce this week published their report Leaving no one behind – How can we be more inclusive in our data?
There’s a lot of good in the report and the eight detailed recommendations presented, providing high-level guidance and direction to those engaged in strategic decisions about data in the UK.
However – in terms of specific recommendations about gender, sex and sexuality data – the Taskforce’s focus on ‘inclusivity’ scratches at the surface of the problem and fails to meaningfully address challenges produced by power imbalances and data injustice.
For example, Recommendation 3.4 notes:
Sex, age and ethnic group should be routinely collected and reported in all administrative data and in-service process data, including statistics collected within health and care settings and by police, courts and prisons.
The thrust of the recommendation is fine, though how ‘sex’ and ‘ethnic group’ are conceptualised and counted will likely differ across data collection exercises.
These differences aren’t a problem, per se, as it’s important that data collectors ask questions that return data they require to answer their research questions. However, a failure to acknowledge the contextual and nuanced approaches of data collectors might wrongly suggest there is only one way to collect data about sex, for example.
As the Office for National Statistics have demonstrated in their research into the design of the sex question for the 2021 census in England and Wales, there exists at least five ways to collect data about sex in a national census.
Recommendation 3.4 therefore left me wondering if this actually illuminates our understanding of gender, sex and sexuality data or wrongly suggests an easy answer that does not currently exist?
Furthermore, Recommendation 5.4 notes:
Data producers and analysts should ensure that the language used in the collection and reporting of all characteristics is clear. For example, clearly distinguishing between concepts such as sex, gender and gender identity; or ethnic identity and ethnic background. This would help to avoid ambiguity and confusion among respondents and data users, which can undermine data and analytical quality, as well as belief in the validity and reliability of data.
Again, the Taskforce expect too much from data producers, analysts and those sharing their data. The concepts ‘sex’, ‘gender’ and ‘gender identity’ are ambigous and confusing among respondents and data users, there is no quick fix here.
It is particularly frustrating to see the Taskforce refer to data about the protected characteristic of gender reassignment as data about ‘gender identity’.
The choice of language is most likely intended to model the wording adopted for the question used to count trans and cis populations in England and Wale’s 2021 census, which describes itself as a ‘gender identity’ question but only collects data about the gender of people whose gender differs from their sex registered at birth.
The majority of respondents likely use the terms ‘sex’ and ‘gender’ interchangeably in everyday life and will not register any difference between the concepts when disclosing information about themselves. However, use of the tautological phrase ‘gender identity’ – in place of a term such as ‘trans status/history’ (as used in Scotland’s 2022 census) – is a slippage that only adds to this confusion. We don’t collect data about someone’s ‘religious identity’ or ‘racial identity’ or ‘sex identity’ – why ‘gender identity’? The ‘identity’ suffix is intended to differentiate the concept from ‘gender’ but as the Taskforce understand ‘gender identity’ to relate to the protected characteristic of ‘gender reassignment’ (and not ‘gender’, per se) this makes the recommended approach extremely hard to follow.
This slippage of language also aids the efforts of trans-exclusionary campaign groups to drive a wedge between concepts of sex and gender in data collection activities. Groups opposed to the counting of trans people believe that data collection agencies should capture sex data (as something only biological) and gender data (as something only social), overlooking the overlap and interconnectedness of the two concepts. This approach is not reflective of the social world nor how individuals share information about themselves in data collection exercises.
Although promising much, the Inclusive Data Taskforce fail to go far enough. Future work by the UK Statistics Agency needs to move beyond ‘being inclusive’ as an aspiration and ensure their outputs decrease rather than increase confusion about gender, sex and sexuality data.
Kevin Guyan 