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Reviewing your evidence: examples

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Example 1:

A youth project operating in a suburb of Manchester used data from the 2001 Census when estimating the percentage of people that would benefit from their project by religion and belief. The 2001 data showed that 8 per cent of their beneficiaries could be Jewish.

At the end of the first year, the project had managed to collect equality data from 70 per cent of its users, which they felt was a good achievement. Having reviewed their data, the project identified that only one per cent of their project beneficiaries were Jewish, despite their best efforts to promote the youth project through the local Synagogue.

The project felt that the difference between the estimated and actual levels was because the data source they had used for their estimates was so old. They knew that many of the younger Jewish families had moved in recent years to different neighbourhoods. The Big Lottery Fund agreed to revise the project’s estimated beneficiary levels by religion and belief.

Example 2:

A mobile library service in a rural area used the local authority’s recent community audit to work out the percentage of people who would benefit from their project, under each of the equality categories.

One year down the line, having collected equality data through a one-off customer satisfaction survey, they noticed there were large differences between their original estimates and actual beneficiary levels, across many of the equality categories. On reflection, the project realised they had only managed to collect equality data from 150 project users, despite having over 1,000 people registered for their service. This meant the volume of data wasn’t large enough and it didn’t include a wide range of users. The library service recognised to encourage a higher response rate in the future, it needed to run its survey over a longer time-frame and explain in the preamble why it was collecting this information and how it would be used.

Example 3:

A community garden used a mixture of its own research and recent data from the Office for National Statistics website to estimate who would benefit from their project (under each of the equality categories). They asked project beneficiaries to fill in an anonymous equality monitoring form when they registered and managed to collect reasonably complete information from 80 per cent of its users.

At the end of the first year, the project compared their estimates with the equality information they had collected. Knowing there was a sizeable Muslim community in the local area, the project was surprised to see that only a small percentage of beneficiaries described themselves as Muslim.

The project leader talked to one of the members who was a Muslim and found out that running the project on Tuesdays and Fridays (the Islamic holy day) was a barrier to their participation. So the community garden decided to change its days to be more inclusive.