This presentation was given as a webinar in collaboration with All things Urban (https://www.allthingsurban.net/) and IE University. It is entitled Urban Inequalities: How can cities include people?
I provide a brief problem definition of urban inequalities as a complex urban problem that extends far beyond wealth and income inequalities. I show different perspectives and ways we may look at this complex problem. I then propose that urban inequalities emerge through the interactions between critical infrastructure and society over time, with key insights.
I conclude by providing examples of socially inclusive design projects and initiatives at different urban scales with actionable insights that practitioners and students in the built environment may use to create more socially inclusive environments.
Urban Inequalities_ How can cities include people_.pdf
1. Ruth Nelson
TU Delft PhD Researcher and spatial data scientist
Urban Inequalities:
How can cities include people?
January 2023.
Ruth Nelson
TU Delft PhD Researcher and spatial data scientist
2. Ruth Nelson
TU Delft PhD Researcher and spatial data scientist
Contents
Background
1
2
3
4
5
Perspectives
Examples: socially inclusive design
Action steps: towards socially inclusive design!
Insights
Fig: Unequal Scenes
Ref: unequalscenes.com
3. Ruth Nelson
TU Delft PhD Researcher and spatial data scientist
01. Background
Why is reducing urban inequalities
important and what are urban
inequalities?
Ruth Nelson
TU Delft PhD Researcher and spatial data scientist
4. Ruth Nelson
TU Delft PhD Researcher and spatial data scientist
01.1
Urban inequalities have grown within almost every
single country in the world over the last 30 years
(World Inequality Report, 2022).
Reducing urban inequalities is widely acknowledged
as imperative by organisations such as the United
Nations for creating and working towards
Sustainable Development.
Ref: https://ourworldindata.org/grapher/energy-consumption-by-source-and-region?country=~FRA
Sustainable Development
Fig: United Nations Sustainable Development Goals
Ref: https://international-partnerships.ec.europa.eu
5. Ruth Nelson
TU Delft PhD Researcher and spatial data scientist
01.2
Fig: Global Gini Index
Ref: data.worldbank.org.
Inequality
● Primarily been defined as an
economic issue - relating to the
distribution of income and wealth
● Metrics developed such as the Gini
Index, Atkinson Index to measure
income inequality.
6. Ruth Nelson
TU Delft PhD Researcher and spatial data scientist
Urban inequalities
are about much
more than just
income and wealth…
7. Ruth Nelson
TU Delft PhD Researcher and spatial data scientist
01.3
Housing
inequalities
● Access to shelter
● Access to housing in centrally
located areas
● Home ownership
Fig: Protests
Ref: https://www.ft.com/content/eab48cd2-06a2-11e8-9650-9c0ad2d7c5b5
8. Ruth Nelson
TU Delft PhD Researcher and spatial data scientist
01.4
Energy
inequalities
● Access to electricity
● Soaring gas prices in Europe
Fig: Energy inequalities
Ref: https://www.globaltimes.cn/page/202210/1277499.shtml
9. Ruth Nelson
TU Delft PhD Researcher and spatial data scientist
01.5
Transportation
inequalities
● Can you walk, cycle safely in
your city?
● Do you have access to efficient
and safe public transport?
● Can you afford public transport?
Fig: Cycling
Ref Upsplash:
10. Ruth Nelson
TU Delft PhD Researcher and spatial data scientist
01.6
Digital
inequalities
● Internet access
● Cost
Fig: Wifi
Ref:Upsplash
11. Ruth Nelson
TU Delft PhD Researcher and spatial data scientist
02. Perspectives
How can we engage with and measure
urban inequalities beyond economic
metrics?
Ruth Nelson
TU Delft PhD Researcher and spatial data scientist
12. Ruth Nelson
TU Delft PhD Researcher and spatial data scientist
● Amenities
● Grocery stores
● Employment opportunities
● Transit
02.1
Access
● Transportation
Research
● Economics
● Network science
Inequalities through an
accessibility lens
Access to: Methods/metrics
13. Ruth Nelson
TU Delft PhD Researcher and spatial data scientist
02.1
Access
Barriers Disadvantages Processes
14. Ruth Nelson
TU Delft PhD Researcher and spatial data scientist
● Market distributions
● Infrastructure
● Income
● Housing
02.2
Distribution
● GIS
● Statistics
● Dimension
reducing
techniques
Geographies of distribution Kinds of distributions Methods/metrics
15. Ruth Nelson
TU Delft PhD Researcher and spatial data scientist
02.2
Distribution Scale
Country
City Neighbourhoods
● Welfare Systems
● Housing policies
● National development frameworks
● Rural to urban migration
● Housing prices
● Infrastructure
● Transport
● Zoning
● Crime
● Educational Facilities
● Local services
● Local environmental factors
16. Ruth Nelson
TU Delft PhD Researcher and spatial data scientist
● Women
● Socio-economically
disadvantaged
Policy and Stakeholders
● Participatory
methods
● Computational: ie
ABM
Policy and stakeholder lens Stakeholders Methods/metrics
02.3
17. Ruth Nelson
TU Delft PhD Researcher and spatial data scientist
02.3
Policy and Stakeholders
Effects of past policy Effects of current policy Future policy effects
18. Ruth Nelson
TU Delft PhD Researcher and spatial data scientist
03. Insights
What insights have we drawn from
examining inequalities from these
perspectives?
Ruth Nelson
TU Delft PhD Researcher and spatial data scientist
19. Ruth Nelson
TU Delft PhD Researcher and spatial data scientist
Urban inequalities
are complex
problems
20. Ruth Nelson
TU Delft PhD Researcher and spatial data scientist
Inequalities and complexity theory
● Exist in relational systems
that are composed of
interacting components
● These components do not
interact in a way that is
linear in cause and effect
● The interactions can
lead to new
emergent patterns
of self organisation
03.1
● There will always be
trade-offs in
developing solutions
21. Ruth Nelson
TU Delft PhD Researcher and spatial data scientist
What is the system
that urban
inequalities emerge in
composed of?
22. Ruth Nelson
TU Delft PhD Researcher and spatial data scientist
03.2
Framework
Urban inequality emerges through the
interaction between social and
critical infrastructure systems over
space and time.
Ecological
Material & Energy
Transport , Buildings,
Housing, etc.
Water, Waste,
Electricity etc.
Green areas, Trees,
Water, Terrain etc.
Digital
ICT, Internet, Cloud,
Markets, Data etc.
Social
Components
Critical
Infrastructure
Components
Urban Inequalities emerge
through the interaction
between Social and Critical
Infrastructure components
over space and time.
Space and Time
Governance
Individual
State Actors,
Municipal, etc.
Capital, Race, Gender,
Education etc.
Community
organisations etc.
Private
Companies, Business,
NGOs etc.
Community
Top down
Bottom Up
Physical
Ephemeral
Social Components shape
Infrastructure through policy,
private investment and
community action.
Over time, Infrastructure
Components reflect on the
structure of the Social through
access + distribution
Urban Infrastructure
23. Ruth Nelson
TU Delft PhD Researcher and spatial data scientist
How do the social and
critical infrastructure
components in the
city interact?
24. Ruth Nelson
TU Delft PhD Researcher and spatial data scientist
03.3
Spatial Segregation and
inequality
Extreme spatial segregation and
inequalities can form a vicious cycle.
Extreme
segregation
Social
Exclusion
Unemployment
Poverty
25. Ruth Nelson
TU Delft PhD Researcher and spatial data scientist
03.4
Individual and
Neighbourhood
The socio-spatial composition of
neighbourhoods matter: it influences
the type of school an individual
attends, community support,
employment opportunities, transport
they have access to…
26. Ruth Nelson
TU Delft PhD Researcher and spatial data scientist
03.5
The role of the State
in perpetuating
inequalities.
Governance structures and regulation
(or lack thereof) influence the way
critical infrastructure is
distributed across space and
therefore ultimately who has access to
it.
Fig: Abandoned Infonavit Homes in Mexico
Ref:https://www.mexicanist.com/l/there-are-more-than-4-million-abandoned-houses-in-mexico/
27. Ruth Nelson
TU Delft PhD Researcher and spatial data scientist
03.6
Identity and
inequalities
Identity can be thought of as the
qualities, beliefs, personality traits,
appearance or expressions that
characterise a specific group, which
may be rooted in their gender, religion,
race, nationality, or age.
Fig: Protests
Ref: https://www.britannica.com/topic/Black-Lives-Matter
28. Ruth Nelson
TU Delft PhD Researcher and spatial data scientist
04. Examples
How can we design to include people
and reduce (hopefully) inequalities?
Ruth Nelson
TU Delft PhD Researcher and spatial data scientist
29. Ruth Nelson
TU Delft PhD Researcher and spatial data scientist
04.1
Buildings:
The Student Centre,
UCL
Creating many different kinds of
spaces for all students across
faculties to meet and interact at the
University College London.
Fig 6: Different kinds of spaces, Student Centre, UCL
Ref:https://www.nicholashare.co.uk/projects/view/new-student-centre-ucl
30. Ruth Nelson
TU Delft PhD Researcher and spatial data scientist
04.2
Streets:
Paseo de la Reforma,
Mexico City
The transformation of Paseo de la
Reforma from a street dominated by
cars to cyclists-only on a Sunday in
Mexico City attracting hundreds of
families, friends and even pets.
Fig 7: Avenida Obregon on a Sunday
Ref: Author
31. Ruth Nelson
TU Delft PhD Researcher and spatial data scientist
04.3
Neighbourhoods:
Utrecht City Centre,
Netherlands
The transformation of a highway to a
pedestrian walkway and canal in
Utrecht, the Netherlands.
Fig 8: Utrecht transformation
Ref: https://www.dutchnews.nl/news/2020/09/joining-the-circle-utrecht-removes-road-to-be-ringed-by-water-once-more/
32. Ruth Nelson
TU Delft PhD Researcher and spatial data scientist
04.4
Cities:
London
New tube line connecting East and
West London, which have historically
been divided along income and class
lines.
Fig: Elizabeth Line, London
Ref: https://www.bbc.co.uk/news/uk-england-london-61095510
33. Ruth Nelson
TU Delft PhD Researcher and spatial data scientist
04.5
Country:
Housing Policy,
South Africa
Prototype with an attempt to change
policy in upgrading shacks:
Empower Shack Project Khayelitsha,
Cape Town, by Urban think tank.
Showcasing a prototype of shack
upgrading, as a means to try and
influence national policy.
Fig: Empower Shack, Cape Town
Ref:https://www.architectural-review.com/buildings/family-business-empower-shack-in-khayelitsha-near-cape-tow
n-south-africa-by-urban-think-tank-and-eth-zurich
34. Ruth Nelson
TU Delft PhD Researcher and spatial data scientist
05. Action Steps
What steps can be taken by
practitioners & students in the built
environment to reduce inequalities?
Ruth Nelson
TU Delft PhD Researcher and spatial data scientist
35. Ruth Nelson
TU Delft PhD Researcher and spatial data scientist
Incorporate metrics of
accessibility and
distribution into the
design process.
05.1
36. Ruth Nelson
TU Delft PhD Researcher and spatial data scientist
Engage with policy as
part of the design
process:
ie. land use zoning - is
it fair and just?
05.2
37. Ruth Nelson
TU Delft PhD Researcher and spatial data scientist
Design for different kinds
of transport:
Ie. Walking, bicycles, buses, trains,
trams
05.3
38. Ruth Nelson
TU Delft PhD Researcher and spatial data scientist
Design for the needs of
different kinds of people:
Women, the disabled, children, the
elderly, LGBTQ+ etc.
05.4
39. Ruth Nelson
TU Delft PhD Researcher and spatial data scientist
Addressing inequalities requires
challenging transdisciplinary and
multidisciplinary barriers.
05.5
41. Ruth Nelson
TU Delft PhD Researcher and spatial data scientist
Ruth Nelson Ruth Nelson
@ RuthJNelson
Get in touch:
42. Ruth Nelson
TU Delft PhD Researcher and spatial data scientist
Link to research
"Conceptualising urban inequalities as a complex
socio-technical phenomenon"
Nelson, Warnier and Verma (2022)
Scan me!