These maps show how hard it is to measure inequality in English council areas

Maps! Maps! Maps! Image: author provided.

As heads of state, billionaires and other influencers pondered the issue of inequality at the World Economic Forum in Davos, an unlikely hero emerged in the form of Dutch historian Rutger Bregman. His memorable take down of the super wealthy on tax avoidance clearly resonated, at a time when the deep social divisions associated with inequality are manifesting themselves forcefully across the world: from the gilet jaunes protests in France, to the ongoing fallout from Brexit.

In the UK, people often think about inequality in geographical terms: for example, places such as Kensington in London are considered “rich”, while Blackpool in Lancashire is considered “poor”. In reality there are rich and poor areas almost everywhere, but they are not distributed evenly across England.

Inner urban neighbourhoods are often associated with deprivation, as are the so-called “left-behind” towns so often associated with Brexit, but quite often rural poverty is overlooked. When we began investigating inequality in England, as part of a new project funded by the Nuffield Foundation, we quickly found that the truth is far more complex.

Kensington constituency. Image: Alasdair Rae and Elvis Nyanzu, University of Sheffield.

Take Kensington, for example: when we mapped out data from government statistics on deprivation, we found that it’s actually a very unequal area.

We want to cut through old stereotypes and divisions, by presenting data in a new way, which sheds light on the longstanding inequalities within and between places – no matter how big or small, or urban or rural they are.

By the time we complete our project in 2020, we hope to produce an atlas of inequality, which illustrates the scale and severity of inequality across England, right down to a local level – since that’s where its impacts are felt most keenly.

Divided cities?

Looking at the data for English cities, the problems with mapping inequality become clearer. The maps below show eight major English cities, plus Greater London. Areas shown in red are among the 10 per cent most deprived in the whole of England, whereas the blue areas are among the 10 per cent least deprived. The ratio of red to blue areas is shown in the bar along the bottom of each city map.

Divided cities? Areas among the 10 per cent most and least deprived in England. Image: Alasdair Rae and Elvis Nyanzu, University of Sheffield.

Some cities look very deprived, others are quite mixed. In Sheffield in particular you could almost draw a straight line between the red and blue areas. Where boundaries are drawn matters a lot. Take Manchester, for example: its official boundary doesn’t include places which are functionally part of the city, such as Salford, where a lot of people work.

The City of Manchester (black outline) and surrounding areas. Image: Alasdair Rae, University of Sheffield.

Looking at the map of Manchester above, you might think it’s quite deprived, but you only have to look beyond the boundaries, in the map to the left, to see things in a different light. By contrast, Leeds has a wide boundary which extends far beyond the core of the city, and takes in wealthier places like Wetherby.

The blue areas all sit outside the functional core of the city, yet from an administrative point of view, they’re still part of Leeds. So although you might assume that Manchester is considerably more deprived than Leeds, the reality is more complex.

Is inequality inevitable?

Our initial findings have raised some critical issues, which prompted us to think more deeply about what level of inequality might ultimately be considered “acceptable” in the first place – and especially, whether areas with greater levels of inequality have worse outcomes.

This might seem like a strange thing to consider, but it’s important because it speaks to the issue of what kind of society we want to live in – and, as a result, what policies can be put in place to bring that about.

What would an ‘acceptable’ deprivation profile look like? Image: author provided.

The graph above looks at a very simple measure of inequality across three of England’s 149 official labour market areas (also known as “travel to work areas” or TTWAs). It shows what proportion of neighbourhoods are within each deprivation decile (i.e. poorest 10 per cent, 20 per cent and so on) for Lincoln, Liskeard and Liverpool. For example, you can see that a large proportion of Liverpool’s neighbourhoods are within the 10 per cent most deprived areas across England (the tallest bar on the Liverpool chart), yet this is not the case in Lincoln or Liskeard.

Lincoln has a more balanced profile, and Liskeard has far more areas in the middle. The key question here is how these variations in local inequalities impact both the life chances of individuals and overall levels of economic vitality.


At a time when society is defined more by its cleavages than its cohesiveness, it’s more important than ever to have a clear-eyed understanding of where inequality exists, and what impact it has on local people.

Of course, data and maps aren’t the only way of gaining insights into inequality – nor are they always as compelling as other media, like striking photographs, or people’s personal stories. Our approach is only one way of understanding the world. But it can help to inform leaders in local and national governments about inequality, and, we hope, lead to action which makes life better for people living in relative poverty.

The Conversation

Alasdair Rae, Professor in Urban Studies and Planning, University of Sheffield and Elvis Nyanzu, PhD Candidate in Urban Studies and Planning, University of Sheffield.

This article is republished from The Conversation under a Creative Commons license. Read the original article.

 
 
 
 

What Citymapper’s business plan tells us about the future of Smart Cities

Some buses. Image: David Howard/Wikimedia Commons.

In late September, transport planning app Citymapper announced that it had accumulated £22m in losses, nearly doubling its total loss since the start of 2019. 

Like Uber and Lyft, Citymapper survives on investment funding rounds, hoping to stay around long enough to secure a monopoly. Since the start of 2019, the firm’s main tool for establishing that monopoly has been the “Citymapper Pass”, an attempt to undercut Transport for London’s Oyster Card. 

The Pass was teased early in the year and then rolled out in the spring, promising unlimited travel in zones 1-2 for £31 a week – cheaper than the TfL rate of £35.10. In effect, that means Citymapper itself is paying the difference for users to ride in zones 1-2. The firm is basically subsidising its customers’ travel on TfL in the hopes of getting people hooked on its app. 

So what's the company’s gameplan? After a painful, two-year long attempt at a joint minibus and taxi service – known variously as Smartbus, SmartRide, and Ride – Citymapper killed off its plans at a bus fleet in July. Instead of brick and mortar, it’s taken a gamble on their mobile mapping service with Pass. It operates as a subscription-based prepaid mobile wallet, which is used in the app (or as a contactless card) and operates as a financial service through MasterCard. Crucially, the service offers fully integrated, unlimited travel, which gives the company vital information about how people are actually moving and travelling in the city.

“What Citymapper is doing is offering a door-to-door view of commuter journeys,” says King’s College London lecturer Jonathan Reades, who researches smart cities and the Oyster card. 

TfL can only glean so much data from your taps in and out, a fact which has been frustrating for smart city researchers studying transit data, as well as companies trying to make use of that data. “Neither Uber nor TfL know what you do once you leave their system. But Citymapper does, because it’s not tied to any one system and – because of geolocation and your search – it knows your real origin and destination.” 

In other words, linking ticketing directly with a mapping service means the company can get data not only about where riders hop on and off the tube, but also how they're planning their route, whether they follow that plan, and what their final destination is. The app is paying to discount users’ fares in order to gain more data.

Door-to-door destinations gives a lot more detailed information about a rider’s profile as well: “Citymapper can see that you’re also looking at high-profile restaurant as destinations, live in an address on a swanky street in Hammersmith, and regularly travel to the City.” Citymapper can gain insights into what kind of people are travelling, where they hang out, and how they cluster in transit systems. 

And on top of finding out data about how users move in a city, Citymapper is also gaining financial data about users through ticketing, which reflects a wider trend of tech companies entering into the financial services market – like Apple’s recent foray into the credit card business with Apple Card. Citymapper is willing to take a massive hit because the data related to how people actually travel, and how they spend their money, can do a lot more for them than help the company run a minibus service: by financialising its mapping service, it’s getting actual ticketing data that Google Maps doesn’t have, while simultaneously helping to build a routing platform that users never really have to leave


The integrated transit app, complete with ticket data, lets Citymapper get a sense of flows and transit corridors. As the Guardian points out, this gives Citymapper a lot of leverage to negotiate with smaller transit providers – scooter services, for example – who want to partner with it down the line. 

“You can start to look at ‘up-sell’ and ‘cross-sell’ opportunities,” explain Reades. “If they see that a particular journey or modal mix is attractive then they are in a position to act on that with their various mobility offerings or to sell that knowledge to others. 

“They might sell locational insights to retailers or network operators,” he goes on. “If you put a scooter bay here then we think that will be well-used since our data indicates X; or if you put a store here then you’ll be capturing more of that desirable scooter demographic.” With the rise of electric rideables, Citymapper can position itself as a platform operator that holds the key to user data – acting a lot like TfL, but for startup scooter companies and car-sharing companies.

The app’s origins tell us a lot about the direction of its monetisation strategy. Originally conceived as “Busmapper”, the app used publicly available transit data as the base for its own datasets, privileging transit data over Google Maps’ focus on walking and driving.  From there it was able to hone in on user data and extract that information to build a more efficient picture of the transit system. By collecting more data, it has better grounds for selling that for urban planning purposes, whether to government or elsewhere.

This kind of data-centred planning is what makes smart cities possible. It’s only become appealing to civic governments, Reades explains, since civic government has become more constrained by funding. “The reason its gaining traction with policy-makers is because the constraints of austerity mean that they’re trying to do more with less. They use data to measure more efficient services.”  

The question now is whether Citymapper’s plan to lure riders away from the Oyster card will be successful in the long term. Consolidated routing and ticketing data is likely only the first step. It may be too early to tell how it will affect public agencies like TfL – but right now Citymapper is establishing itself as a ticketing service - gaining valuable urban data, financialising its app, and running up those losses in the process.

When approached for comment, Citymapper claimed that Pass is not losing money but that it is a “growth startup which is developing its revenue streams”. The company stated that they have never sold data, but “regularly engage with transport authorities around the world to help improve open data and their systems”

Josh Gabert-Doyon tweets as @JoshGD.