This blog post is part of a series investigating different demographics and uses of mySociety services. You can read more about this series here.
A key question when looking at the role of the internet in civic life is whether it changes the demographics of who participates; or whether it simply changes the methods by which already engaged citizens participate. The two sides in this argument can be described as mobilisation and reinforcement.
The mobilisation argument says that the internet reduces the cost of communication and action, which means that more people can be involved and access becomes more broad.
The reinforcement argument says that the reduced costs of connectivity will mostly reinforce existing participation divides, making it cheaper for people already engaged to participate, but not necessarily reaching disengaged people.
This is a fundamental question for civic tech: how are these online tools used? Are they mobilising everyone or just providing more efficient processes for people who are already engaged?
This is explored in mySociety’s 2015 report Who benefits from Civic Technology?, and is a recurring question in much of our research since, such as our work on FixMyStreet, and digital technologies in sub-Saharan Africa.
Two themes we are currently investigating in this area are proxies and bundles.
Proxies are where services are used by intermediaries, on behalf of — and bringing benefits to — others: for instance, where charities engage in more effective lobbying as a result of free access to TheyWorkForYou, or where case workers find it easier to identify and write to a client’s local councillor using WriteToThem.
Bundles are about exploring how different groups of users use a service in different ways, to such an extent that one service can in fact be understood as a bundle of services serving different kinds of users.
This is the first in a series of blog posts investigating bundles.
A common finding across mySociety services is that most people only use “transactional” services (like WhatDoTheyKnow, FixMyStreet or WriteToThem) once, to do one thing. Repeat users make up a minority of users (even if they account for the majority of actual usage).
From a technology point of view or an organisational point of view, it makes sense to understand that there is a website called FixMyStreet.com run by mySociety. But from the point of view of the majority of users, it makes sense to think of a website like FixMyStreet as dozens of different services, most of which they will never use. For one user, FixMyStreet is a tool for reporting potholes, for another it is for reporting littering. Similarly, WriteToThem is most often used as a tool to write to MPs — but the profile of people who use it to write to their local councillors is very different.
Some services in a bundle are used by a different demographic to other uses of the same website. Understanding how to encourage FixMyStreet use in underrepresented groups requires an understanding of how there are already differences in usage across all the “services” in the FixMyStreet bundle.
To get more information about these different uses of a website, we’ve built a mini-site that helps to explore basic demographic information about each use type. Starting with FixMyStreet, personal information (names) have been anonymised and converted to gender (approximately), while coordinates are grouped into Lower Super Output Areas (LSOA) — geographic areas commonly used for statistical purposes. This means that we can look at a general, anonymised set of data representing people making FixMyStreet reports, and match this grouped data against various measures of deprivation.
Understanding more about these different patterns of users suggests possible ways a service can be used and helps sharpen new research questions.
When examining uses of one element of a bundle, the key question is whether the pattern observed reflects just the individual, or the overall pattern of the bundle. To answer this, a chi-square test is used to tell if the distribution of a sub-use of the site is different to a statistically significant extent to all other uses of the site (this method was inspired by an analysis of gender of reporters in Reka Solymosi, Kate Bowers and Taku Fujiyama’s 2018 paper on FixMyStreet). The groupings of categories in FixMyStreet use Elvis Nyanzu’s meta categories. The mini-site highlights in red and green areas where a distribution differs from how patterns on the site as a whole respond.
We’ll be writing a number of blog posts over the next few months covering things we’ve learned from the mini-site. The first two are already up (and linked below):
This page will be updated as new blog posts are released.
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