This piece builds on previous articles (here, here, here and here) to explain why statistics about equality need to be collected and how equality monitoring can be used by oppressed groups, their allies and trade unions, to challenge discrimination and advance equal rights.
This is not to argue that the existing Act could not be massively strengthened. In terms of disabled people employers and service providers have the massive get-out that you can only demand a ‘reasonable’ adjustment. Employers also sometimes fail to recognise that in law ‘reasonable’ should be judged by the budget of the whole organisation, not a department or small work area. Recent events have shown major flaws in terms of the protection of trans people, even though the Equality Act includes gender reassignment as a protected category. Another flaw is that the Equality Act (like the Sex Discrimination Act 1975) permits discrimination against single people; marital status is only protected in the cases of marriage and civil partnership. Further there is a danger of some campaigners thinking legal protection without self-organisation is enough. Nonetheless at the same time our opponents on the far-right are correct in understanding that this legislation is a tool for the working class and oppressed.
Data
“That’s just your opinion” or “that’s just your personal experience“ is often the response to claims of discrimination and under-representation in the absence of equality data. It can be hard for an individual to know whether they did not get a job because of their race, sex or impairment. It is even more difficult to prove it. An employer can always give some other reason for not hiring.
When patterns of hiring, promotion and dismissal are recorded over time and analysed, by race, sex and disability, it is possible to see if some groups are losing out. It’s then possible to bring a claim of unfair discrimination.
There is a world of difference between just knowing you are being discriminated against and having statistical proof which can be used to demand governments and employers take action. Documenting inequalities can be part of the work of liberation movements and has a consciousness-raising element. It makes discrimination a political issue.
Losing equality data
In the UK far-right parties such as Reform UK propose to repeal the Equality Act. They claim that government, local and national, spends too much on ‘unnecessary bureaucracy’. Among their targets for saving money by cutting ‘waste’ are areas concerned with equality. This includes collecting records of decisions on job selection, and statistics on populations, broken down by sex, race, and disability.
At present legal obligations under equality laws require the collection of this data for policy implementation and as defence against claims of discrimination. If a far-right government could repeal the Equality Act 2010, how long would equality monitoring survive?
Equality monitoring
Equality monitoring is used to measure discrimination, set equality targets and check progress. It involves collecting data disaggregated by race, sex, disability and any other characteristics which may be the basis of unfair discrimination. This can be used to measure discrimination, for instance by comparing those hired with the labour pool from which the employer recruits. It can be used to set targets for affirmative action programmes. It can then be used to measure progress in achieving equality targets.
The use of equality monitoring is basic to implementing equal opportunities in education, training and employment. Without statistical evidence it is easy to assert there is no problem of discrimination and to deny injustice.
Social values and data collection
The data that governments and other organisations collect indicates the values they hold or at least pay lip-service to. Many governments and work organisations now collect data on aspects of equality, such as the gender pay gap or class differences in health. This is partly because social movements have demanded this information and the existence of equality laws provides a major impetus to its collection. Organisations like Oxfam report global poverty, broken down by sex, highlighting poverty among women. This is a result of feminism and of having the data.
Social scientists routinely analyse data by variables such as socio-economic class, age, race, and sex. This data is vital to analysis of social inequality. Much of this work involves secondary analysis of government data.
In many areas of social policy, such as education, health, housing, planning, policing and transport, use is made of equality data to check whether all sections of the population are getting equal levels of service; whether some groups have greater or different needs than others and how to avoid unequal treatment.
Having statistics for instance about the disproportionate number of Black people tasered by the police is important for challenging police racism. Planning bus routes involves taking into account the travel patterns of different groups of the population, e.g. going to work, to college, for leisure etc.
Equality bargaining by unions
Trade unions have responsibilities under the Equality Act 2010. Many have strong equality policies and structures. Trade unions make substantial use of data about pay and employment when negotiating equal pay and equality policies with employers. Unions may negotiate on equal pay as a distinct issue and include equal pay elements in national pay bargaining.
The gender pay gap
Longitudinal pay data has allowed feminists, trade unionists and policy analysts to understand that equal pay was not achieved simply by abolishing sex-specific pay grades and making all pay grades open to all workers -a reform brought in by the Equal Pay Act 1970. Comparison of men’s and women’s average earnings, both across the economy and within industries, has allowed economists to measure the gender pay gap. This is often done by comparing men’s and women’s average hourly earnings.
Analysis shows that the gender pay gap arises from three main factors: occupational segregation by sex; women’s interrupted working lives; and direct discrimination. So, our understanding of equal pay has gone from simply removing sex-specific pay grades to looking at recruitment patterns, occupational segregation, calculation of initial starting salary, bonus payments and promotion patterns. Skills which are central to caring occupations, such as nursing or primary school teaching, where large numbers of women, and racialised people of any gender, work were generally evaluated as being worth less than ‘male’ attributes such as physical strength or leadership. All these factors contributed to the gender pay gap.
The gender pensions gap
Trade unions and pensions analysts now talk too about the gender pensions gap. Inequalities in pay in working life impact upon women’s income in retirement. The gender pensions gap also arises from time out of the labour market, for instance bringing up children; being a carer for other family members; part-time working; and lower enrolment of women in occupational pension schemes. The married women’s stamp, a reduction in insurance payments which married women were able to claim, but which was accompanied by fewer benefits and is now understood as working towards women’s disadvantage also has a pernicious legacy.
Fears and categories
Sometimes oppressed groups are resistant to equality monitoring because they fear information about them will be used to their detriment. It is vital that equality monitoring is followed by action to remove inequalities. Data from equality monitoring should be reported back to relevant groups, workers and their union representatives.
Equality monitoring categories sometimes need to change over time, as for instance has happened with race categories in the census. In terms of sex equality monitoring there is a case for the addition of a non-binary category for people who do not identify as either male or female.
For many people who use equality data as part of their work or studies, it might seem inconceivable that much of this data could disappear. In many organisations it is routine to use this data for analysis and planning. Nonetheless much of it could be lost in a ‘bonfire of the bureaucracy’ from the far-right and much of it did not exist 50 years ago, before equality laws.