Most development stakeholders agree on the need to foster more open and transparent Public Private Partnerships (PPPs) to ensure that PPP projects provide quality public goods and services to citizens, and that they effectively contribute to pro-poor development outcomes.
That sounds great in theory, but in practice, it’s not that easy. PPPs involve a trove of data and documents. On top of that, the information made available publicly is generally difficult to interrogate, when it’s not completely lost in lengthy PDF files.
Let’s face it: searching for relevant PPP data and information can oftentimes feel like looking for a needle in a haystack.
The social inclusion of disadvantaged groups is necessary for reducing poverty and boosting shared prosperity, said government representatives, experts, and civil society representatives at a World Bank seminar on Friday, April 21. Persons with disabilities, Indigenous Peoples, as well as lesbian, gay, bisexual, transgender, and intersex (LGBTI) persons form a large part of the world population affected by poverty. They often face multiple discrimination and exclusion because of their overlapping identities, stressed Maitreyi Das, Social Inclusion Global Lead at the World Bank Group.
Patricia Peña, Director General for Economic Development of Global Affairs, Canada, highlighted the commitment of Canada—through its foreign assistance, diplomacy, and domestic efforts—to support policies and programs addressing economic and social inclusion of LGBTI people. Disaggregated data collection is one of the priorities for developing effective responses. Harry Patrinos, Practice Manager at the Bank’s Education Global Practice, made a cross-country assessment of poverty among Indigenous Peoples. Ulrich Zachau, the World Bank’s Country Director for Southeast Asia, discussed the Bank’s ground-breaking data generation efforts on LGBTI persons in Thailand. There is a need to find a shared way of measuring disability, said Nick Dyer, Director General of Policy and Global Programmes at the UK Department for International Development.
View tweets from the session below. Learn more about the World Bank's work on social inclusion, disability, indigenous peoples, as well as sexual orientation and gender identity (SOGI).
My previous blog post surveyed some of the recent trends in developing global measures of urbanization. In this post, I want to turn to a brief discussion for scholars and practitioners on some possible applications and areas of focus for ongoing work:
[Download draft paper "Bright Lights, Big Cities: a Review of Research and Findings on Global Urban Expansion"]
While there are a number of different maps for documenting urban expansion, each has different strengths and weaknesses in application. Coarser resolution maps such as MODIS can be used for mapping the basic contours of artificial built-up areas in regional and comparative scales. On the other hand, high-resolution maps are best suited for individual cities, as algorithms can be used to identify and classify observed colors, textures, shading, and patterns into different types of land uses. These levels of detail are difficult to use for reliable comparisons between cities as the types of building materials, structure shapes, light reflectivity, and other factors can vary widely between countries and regions.
Nonetheless, there are a number of applications for policymakers in this regard, from identifying and mapping green spaces and natural hazard risks to identifying and tracking areas of new growth, such as informal settlements. However, such approaches to land use detection require careful calibration of these automated methods, such as cross referencing with other available maps, or by “ground truthing” with a sample of street-level photos of various types of buildings and land cover as reference inputs for automation. One solution to this is the use of social media and geo-coded data to confirm and monitor changes in urban environments alongside the use of high-resolution satellite imagery.
Nighttime light maps also have gained traction as measures of urban extent and as ways to gauge changes in economic activity in large urban centers. They are probably less useful for documenting smaller settlements, which may be dimmer or have little significant variation in brightness. It is important to correct these types of maps for “overglow” measurement effects—where certain light may “bleed” or obscure the shapes and forms of very large, bright urban areas in relation to adjacent smaller and dimmer settlements (newer VIIRs maps have made some important advances in correcting this).
(land surface coverage comprised of buildings and roads) and population growth across time and space. This impacts how policymakers may understand and prioritize the challenges cities face and what investments or reforms may be needed. In a new paper, “Bright Lights, Big Cities: a Review of Research and Findings on Global Urban Expansion,” I provide a brief introduction to some of the current approaches for measuring urban expansion and review the comparative findings of some recent studies.
The UN’s World Urbanization Prospects (WUP), perhaps the most comprehensive and widely cited measure of urbanization across the world, draws from a compilation of country-level population totals based on administrative definitions. A key weakness with this set is that since each country defines “urban” differently, it is difficult to accurately compare one country’s urbanization to another, as well as to estimate the urban population of a group of countries or the world itself. Recent work has provided more sophisticated ways to measure urban growth and expansion using both satellite map data and careful application of population data.
We may not know exactly what the world will look like in two decades, but we know this: it is going to be a world of cities.
Each year, urban areas are growing by an average of more than 75 million people – more than the population of the world’s 85 smallest countries combined.
For the world’s economy, this is great news, since cities produce 80 percent of global GDP, despite currently being home to only 55 percent of the population. But it is a problem for urban infrastructure, which can’t keep up with such fast-paced growth. As a result, – from flooding and landslides that can decimate informal housing settlements, to earthquakes that can devastate power grids and water systems.
These risks could be disastrous for the urban poor, 881 million of whom currently live in slums (up 28 percent since 2000). And climate change – which is increasing the intensity and frequency of natural disasters – will only exacerbate the problem. For this reason, multilateral and government institutions now see resilience and climate adaptation as integral pillars of development.
The Swiss State Secretariat for Economic Affairs (SECO), for example, considers low-emission and climate-resilient economies to be key to global competitiveness. A recent report by the World Bank and the Global Facility for Disaster Reduction and Recovery (GFDRR) found that climate change may force up to 77 million urban residents into poverty by 2030 – unless we take action to improve the resilience of cities around the world.
The adverse impacts on the health and economic wellbeing of LGBTI groups—as well as on economies and societies at large—tell us one thing: exclusion and
We’ve already taken the first steps to address this issue, such as quantifying the loss in productivity, but there is still a long way to go. Robust, quantitative data on differential development experiences and outcomes of LGBTI people is crucial, but remains scarce especially in developing countries. Such a research and data gap poses a major constraint in designing and implementing more inclusive programs and policies.
The World Bank’s SOGI Task Force—consisting of representatives from various global practices and country offices, the Gender Cross-cutting Solution Area, as well as the GLOBE staff resource group—has identified the need for quantitative data on LGBTI as a priority.
On Zero Discrimination Day, the World Bank’s Senior Director Ede Ijjasz-Vasquez and SOGI Advisor Clifton Cortez explain the urgent need to fill the LGBTI data gap. They’ve also discussed , as well as what can be done to end poverty and inequality for LGBTI and other excluded groups.
State capacity is clearly fundamental to development, and the motivation and productivity of the personnel working in the state is clearly fundamental to state capacity.
, and 50 to 60 percent of formal sector or salaried workers in developing countries. This fact alone warrants a detailed understanding of the functioning of public sector labor markets and their influence on the broader labor market, particularly as the characteristics of public sector workers—their gender, age, and skills profiles, for instance—can be quite different from their private sector counterparts.
But more importantly, the motivation of government workers and thereby the productivity of government bureaucracies impacts almost everything else in an economy, from business regulations, to infrastructure provision, to the delivery of services.
How can governments ensure that they get their money’s worth when they embrace open government reforms?
Ongoing research suggests that open government reforms—those that promote transparency, participation, and accountability—may lead to better development outcomes if properly implemented by governments. However, governments must navigate the myriad of initiative options as they strive to improve citizens’ quality of life and achieve the ambitious Sustainable Development Goals (SDGs). Without a rough idea of the potential costs and benefits different reforms might offer, how can governments allocate their resources efficiently?
Multiple stakeholders are collaborating to answer this question. The Research Consortium on the Impact of Open Government commissioned a study to determine the financial costs associated with particular open government initiatives.
Nowadays, we don’t think twice before ordering an Uber or using Open 311 to report an issue to our municipality. In the developing world, the impact has been even greater. For example, in Latin America and the Caribbean, cellphone coverage increased from about 12 subscriptions per 100 people in 2000 to over 114 in 2014, and
The city of La Paz in Bolivia is piloting a new tool called Barrio Digital—or Digital Neighborhood—to communicate more effectively and efficiently with citizens living in areas that fall within Barrios de Verdad, or PBCV, an urban upgrading program that provides better services and living conditions to people in poor neighborhoods.
The goals of Barrio Digital are to:
- Increase citizen participation for evidence-based decision-making,
- Reduce the cost of submitting a claim and shorten the amount of time it takes for the municipality to respond, and
- Strengthen the technical skills and capacity within the municipality to use ICT tools for citizen engagement.
For all of the recent explosion in data related to learning -- as a result of standardized tests, etc. -- remarkably little is known at scale about what exactly happens in classrooms around the world, and outside of them, when it comes to learning, and what the impact of this has.
This isn't to say that we know nothing, of course:
The World Bank (to cite an example from within my own institution) has been using standardized classroom observation techniques to help document what is happening in many classrooms around the world (see, for example, reports based on modified Stallings Method classroom observations across Latin America which seek to identify how much time is actually spent on instruction during school hours; in many cases, the resulting data generated are rather appalling).
Common sense holds various tenets dear when it comes to education, and to learning; many educators profess to know intuitively what works, based on their individual (and hard won) experience, even in the absence of rigorously gathered, statistically significant 'hard' data; the impact of various socioeconomic factors is increasingly acknowledged (even if many policymakers remain impervious to them); and cognitive neuroscience is providing many interesting insights.
But in many important ways, education policymaking and processes of teaching and learning are constrained by the fact that we don't have sufficient, useful, actionable data about what is actually happening with learners at a large scale across an education system -- and what impact this might have. Without data, as Andreas Schleicher likes to say, you are just another person with an opinion. (Of course, with data you might be a person with an ill-considered or poorly argued opinion, but that’s another issue.)
|side observation: Echoing many teachers (but, in contrast to teaching professionals, usually with little or no formal teaching experience themselves), I find that many parents and politicians also profess to know intuitively ‘what works’ when it comes to teaching. When it comes to education, most everyone is an ‘expert’, because, well, after all, everyone was at one time a student. While not seeking to denigrate the ‘wisdom of the crowd’, or downplay the value of common sense, I do find it interesting that many leaders profess to have ready prescriptions at hand for what ‘ails education’ in ways that differ markedly from the ways in which they approach making decisions when it comes to healthcare policy, for example, or finance – even though they themselves have also been patients and make spending decisions in their daily lives.|
One of the great attractions of educational technologies for many people is their potential to help open up and peer inside this so-called black box. For example:
- When teachers talk in front of a class, there are only imperfect records of what transpired (teacher and student notes, memories of participants, what's left on the blackboard -- until that's erased). When lectures are recorded, on the other hand, there is a data trail that can be examined and potentially mined for related insights.
- When students are asked to read in their paper textbook, there is no record of whether the book was actually opened, let along whether or not to the correct page, how long a page was viewed, etc. Not so when using e-readers or reading on the web.
- Facts, figures and questions scribbled on the blackboard disappear once the class bell rings; when this information is entered into, say, Blackboard TM (or any other digital learning management system, for that matter), they can potentially live on forever.
|A few years ago I worked on a large project where a government was planning to introduce lots of new technologies into classrooms across its education system. Policymakers were not primarily seeking to do this in order to ‘transform teaching and learning’ (although of course the project was marketed this way), but rather so that they could better understand what was actually happening in classrooms. If students were scoring poorly on their national end-of-year assessments, policymakers were wondering: Is this because the quality of instruction was insufficient? Because the learning materials used were inadequate? Or might it be because the teachers never got to that part of the syllabus, and so students were being assessed on things they hadn’t been taught? If technology use was mandated, at least they might get some sense about what material was being covered in schools – and what wasn’t. Or so the thinking went ....|
Yes, such digital trails are admittedly incomplete, and can obscure as much as they illuminate, especially if the limitations of such data are poorly understood and data are investigated and analyzed incompletely, poorly, or with bias (or malicious intent). They also carry with them all sorts of very important and thorny considerations related to privacy, security, intellectual property and many other issues.
That said, used well, the addition of additional data points holds out the tantalizing promise of potentially new and/or deeper insights than has been currently possible within 'analogue' classrooms.
But there is another 'black box of education' worth considering.
In many countries, there have been serious and expansive efforts underway to compel governments make available more ‘open data’ about what is happening in their societies, and to utilize more ‘open educational resources’ for learning – including in schools. Many international donor and aid agencies support related efforts in key ways. The World Bank is a big promoter of many of these so-called ‘open data’ initiatives, for example. UNESCO has long been a big proponent of ‘open education resources’ (OERs). To some degree, pretty much all international donor agencies are involved in such activities in some way.
There is no doubt that increased ‘openness’ of various sorts can help make many processes and decisions in the education sector more transparent, as well as have other benefits (by allowing the re-use and ‘re-mixing’ of OERs, teachers and students can themselves help create new teaching and learning materials; civil society groups and private firms can utilize open data to help build new products and services; etc.).
What happens when governments promote the use of open education data and open education resources but, at the same time, refuse to make openly available the algorithms (formulas) that are utilized to draw insights from, and make key decisions based on, these open data and resources?
- Are we in danger of opening up one black box, only to place another, more inscrutable back box inside of it?