Leave No One Behind in Cities: How Can Knowledge Gaps About Marginalisation Be Filled?
Street dwellers and the urban poor often don’t have access to their cities’ services. One reason behind this problem is the fact that they are not surveyed and consulted in data collection. How can this gap be filled?
In search of opportunities in the city of Dhaka, Fatima has been living on the streets for the past 10 years. As a young woman who has never attended school, she is unable to read or write. During the day she roams the streets scavenging for food and searching for a job, before finding a place to sleep when night falls. Fatima is just one of the many faces of homelessness, not only in Dhaka but in cities like Rio de Janeiro, Johannesburg, Lagos, and Buenos Aires where the challenges of rapid urbanisation are countless.
According to the United Nations, one in four urban residents live in slum-like conditions. In 2018, this population reached 23.5 per cent globally. Street dwellers, who are not captured within these statistics, sleep often without shelter, in railway terminals and platforms, parks, and other public places. Fatima is one of many young women living on the streets who can be seen begging, sometimes with a child on their back. The lives of street dwellers and the growth of slums reveal the disturbing side of rapid urbanisation, and the extreme poverty that is symptomatic of the growing inequality in and between nations.
Street Dwellers: Lack of Data Leads to Poor Urban Governance
To understand the complexity of urban poverty, we need disaggregated data on the diversity of urban experiences. In most countries, street dwellers like Fatima are almost invisible in national statistics, as national surveys based on household data exclude individuals living on the streets. Such data gaps have contributed to poor urban governance, depriving street dwellers and those living in slum-like conditions of access to healthcare, education and shelter, and therefore the right to a dignified life. Fiscal expenditure, local budgets and urban aid is often inappropriately targeted, while street dwellers and the urban poor are primary victims of government austerity measures.
The SDG agenda includes a commitment to ‘leave no one behind’. SDG 11, which calls for inclusive, safe, resilient and sustainable cities, is particularly important for ensuring the urban poor are not left behind. Yet marginalised groups remain largely overlooked in data used to monitor the SDGs. The reliance of national statistical agencies on aggregated data masks large disparities and fails to adequately capture the experiences of marginalised groups. The timing of census data, which is generally conducted at decade-long intervals, further prevents proactive policy interventions.
The Leave No One Behind Partnership
Without effective engagement of street dwellers and marginalised groups in public policy discourse, their voices will go unheard and their problems unresolved. To realise the promise of ‘Leave No One Behind’ (LNOB), national and local governments must look beyond national averages and take special measures to harness inclusive data on the most marginalised.
In 2017, twelve large international civil society organisations, national NGOs and community groups formed the Leave No One Behind Partnership for inclusive data generation. The coalition works to identify those most at risk of being left behind in SDG implementation and seeks to address their needs.1
Five national coalitions in Bangladesh, India, Kenya, Nepal and Vietnam collaborated to identify marginalised groups, analyse drivers of exclusion, and develop specific policy recommendations. Using official SDG indicators to inform their work, they also developed unique indicators to capture drivers of exclusion that are not adequately reflected in national monitoring. So far, over 2,000 representatives of marginalised groups have been engaged in data collection and trained in a wide array of monitoring tools and approaches, including household surveys, focus groups and key informant interviews.
Inclusive Data Collection is Imperative for Addressing the Needs of the Marginalised
In Bangladesh, the coalition undertook a qualitative study on access to universal health care among street dwellers using SDG target 3.8 on quality essential health care services2. The study identified that even if facilities exist and there is free healthcare provision, street dwellers face other barriers when they want to access the services. Poor communication about health care provision and the difficulties in reaching certain groups lead to a general lack of information on the existence and availability of the free services to which they are entitled.
Financial hardship, long hospital queues, the absence of identity cards, and geographical distance from health care facilities are additional reasons street dwellers remain excluded from access to basic health services. Women and girls on the streets face additional gendered struggles due to the lack of appropriate child birth and maternal health facilities.
The partnership’s use of inclusive methods has engaged community members in data collection and amplified their voices in local and national advocacy work. Each coalition presented their findings in dissemination workshops with local and national government authorities. In Kenya, the coalition worked with the platform ‘SDG Kenya’ to influence changes in the language and data collection tools of the national census towards a more inclusive approach. In India, the use of citizen-generated data has allowed community members to better understand the national SDG context, monitor progress and hold local decision makers accountable. This demonstrates how civic education builds the skills and awareness for marginalised groups to demand their representation and fundamental rights.
The Road Ahead: Inclusive Data Partnerships to Improve SDG Implementation
Whilst the LNOB partnership is still in its early stages with plans to upscale, success in SDG implementation depends upon inclusive and collaborative methods of data collection of this kind. National and local authorities, especially statistical agencies, must acknowledge and take serious account of this alternative data to better inform public policy and development planning. The Voluntary National Review (VNR) process should insist on the inclusion of data on marginalised groups, while national coordinating agencies must ensure that plans for SDG implementation and review have a specific focus on those left behind.
For the SDGs to be truly transformational, we must hold decision makers accountable on their promise to ‘leave no one behind.’ Close attention must be paid to the stories of marginalised people and their communities. Using data, we must work together to identify and expose exclusion, and demand that all forms of discrimination and injustice are fully addressed.