Participatory Budgeting Around the World

Jay Colburn, from the International Budget Partnership:  “Public participation in budget decision making can occur in many different forms. Participatory budgeting (PB) is an increasingly popular process in which the public is involved directly in making budgetary decisions, most often at the local level. The involvement of community members usually includes identifying and prioritizing the community’s needs and then voting on spending for specific projects.
PB was first developed in Porto Alegre, Brazil, in 1989 as an innovative reform to address the city’s severe inequality. Since then it has spread around the world. Though the specifics of how the PB process works varies depending on the context in which it is implemented, most PB processes have four basic similarities: 1) community members identify spending ideas; 2) delegates are selected to develop spending proposals based on those ideas; 3) residents vote on which proposals to fund; and 4) the government implements the chosen proposals.
During the 1990s PB spread throughout Brazil and across Latin America. Examples of participatory budgeting can now be found in every region of the world, including Central Asia, Europe, and the Middle East. As the use of PB has expanded, it has been adapted in many ways. One example is to incorporate new information and communication technologies as a way to broaden opportunities for participation (see Using Technology to Improve Transparency and Citizen Engagement in this newsletter for more on this topic.)…
There are also a number of different models of PB that have been developed, each with slightly different rules and processes. Using the different models and methods has expanded our knowledge on the potential impacts of PB. In addition to having demonstrable and measurable results on mobilizing public funds for services for the poor, participatory budgeting has also been linked to greater tax compliance, increased demands for transparency, and greater access to budget information and oversight.
However, not all instances of PB are equally successful; there are many variables to consider when weighing the impact of different cases. These can include the level and mechanisms of participation, information accessibility, knowledge of opportunities to participate, political context, and prevailing socioeconomic factors. There is a large and growing literature on the benefits and challenges of PB. The IBP Open Budgets Blog recently featured posts on participatory budgeting initiatives in Peru, Kyrgyzstan, and Kenya. While there are still many lessons to be learned about how PB can be used in different contexts, it is certainly a positive step toward increased citizen engagement in the budget process and influence over how public funds are spent.
For more information and resources on PB, visit the participatory budgeting Facebook group”

(Appropriate) Big Data for Climate Resilience?

Amy Luers at the Stanford Social Innovation Review: “The answer to whether big data can help communities build resilience to climate change is yes—there are huge opportunities, but there are also risks.


  • Feedback: Strong negative feedback is core to resilience. A simple example is our body’s response to heat stress—sweating, which is a natural feedback to cool down our body. In social systems, feedbacks are also critical for maintaining functions under stress. For example, communication by affected communities after a hurricane provides feedback for how and where organizations and individuals can provide help. While this kind of feedback used to rely completely on traditional communication channels, now crowdsourcing and data mining projects, such as Ushahidi and Twitter Earthquake detector, enable faster and more-targeted relief.
  • Diversity: Big data is enhancing diversity in a number of ways. Consider public health systems. Health officials are increasingly relying on digital detection methods, such as Google Flu Trends or Flu Near You, to augment and diversify traditional disease surveillance.
  • Self-Organization: A central characteristic of resilient communities is the ability to self-organize. This characteristic must exist within a community (see the National Research Council Resilience Report), not something you can impose on it. However, social media and related data-mining tools (InfoAmazonia, Healthmap) can enhance situational awareness and facilitate collective action by helping people identify others with common interests, communicate with them, and coordinate efforts.


  • Eroding trust: Trust is well established as a core feature of community resilience. Yet the NSA PRISM escapade made it clear that big data projects are raising privacy concerns and possibly eroding trust. And it is not just an issue in government. For example, Target analyzes shopping patterns and can fairly accurately guess if someone in your family is pregnant (which is awkward if they know your daughter is pregnant before you do). When our trust in government, business, and communities weakens, it can decrease a society’s resilience to climate stress.
  • Mistaking correlation for causation: Data mining seeks meaning in patterns that are completely independent of theory (suggesting to some that theory is dead). This approach can lead to erroneous conclusions when correlation is mistakenly taken for causation. For example, one study demonstrated that data mining techniques could show a strong (however spurious) correlation between the changes in the S&P 500 stock index and butter production in Bangladesh. While interesting, a decision support system based on this correlation would likely prove misleading.
  • Failing to see the big picture: One of the biggest challenges with big data mining for building climate resilience is its overemphasis on the hyper-local and hyper-now. While this hyper-local, hyper-now information may be critical for business decisions, without a broader understanding of the longer-term and more-systemic dynamism of social and biophysical systems, big data provides no ability to understand future trends or anticipate vulnerabilities. We must not let our obsession with the here and now divert us from slower-changing variables such as declining groundwater, loss of biodiversity, and melting ice caps—all of which may silently define our future. A related challenge is the fact that big data mining tends to overlook the most vulnerable populations. We must not let the lure of the big data microscope on the “well-to-do” populations of the world make us blind to the less well of populations within cities and communities that have more limited access to smart phones and the Internet.”

Open data for accountable governance: Is data literacy the key to citizen engagement?

at UNDP’s Voices of Eurasia blog: “How can technology connect citizens with governments, and how can we foster, harness, and sustain the citizen engagement that is so essential to anti-corruption efforts?
UNDP has worked on a number of projects that use technology to make it easier for citizens to report corruption to authorities:

These projects are showing some promising results, and provide insights into how a more participatory, interactive government could develop.
At the heart of the projects is the ability to use citizen generated data to identify and report problems for governments to address….

Wanted: Citizen experts

As Kenneth Cukier, The Economist’s Data Editor, has discussed, data literacy will become the new computer literacy. Big data is still nascent and it is impossible to predict exactly how it will affect society as a whole. What we do know is that it is here to stay and data literacy will be integral to our lives.
It is essential that we understand how to interact with big data and the possibilities it holds.
Data literacy needs to be integrated into the education system. Educating non-experts to analyze data is critical to enabling broad participation in this new data age.
As technology advances, key government functions become automated, and government data sharing increases, newer ways for citizens to engage will multiply.
Technology changes rapidly, but the human mind and societal habits cannot. After years of closed government and bureaucratic inefficiency, adaptation of a new approach to governance will take time and education.
We need to bring up a generation that sees being involved in government decisions as normal, and that views participatory government as a right, not an ‘innovative’ service extended by governments.

What now?

In the meantime, while data literacy lies in the hands of a few, we must continue to connect those who have the technological skills with citizen experts seeking to change their communities for the better – as has been done in many a Social Innovation Camps recently (in Montenegro, Ukraine and Armenia at Mardamej and Mardamej Relaoded and across the region at Hurilab).
The social innovation camp and hackathon models are an increasingly debated topic (covered by Susannah Vila, David Eaves, Alex Howard and Clay Johnson).
On the whole, evaluations are leading to newer models that focus on greater integration of mentorship to increase sustainability – which I readily support. However, I do have one comment:
Social innovation camps are often criticized for a lack of sustainability – a claim based on the limited number of apps that go beyond the prototype phase. I find a certain sense of irony in this, for isn’t this what innovation is about: Opening oneself up to the risk of failure in the hope of striking something great?
In the words of Vinod Khosla:

“No failure means no risk, which means nothing new.”

As more data is released, the opportunity for new apps and new ways for citizen interaction will multiply and, who knows, someone might come along and transform government just as TripAdvisor transformed the travel industry.”

Citizen science versus NIMBY?

Ethan Zuckerman’s latest blog: “Safecast is a remarkable project born out of a desire to understand the health and safety implications of the release of radiation from the Fukushima Daiichi nuclear power plant in the wake of the March 11, 2011 earthquake and tsunami. Unsatisfied with limited and questionable information about radiation released by the Japanese government, Joi Ito, Peter, Sean and others worked to design, build and deploy GPS-enabled geiger counters which could be used by concerned citizens throughout Japan to monitor alpha, beta and gamma radiation and understand what parts of Japan have been most effected by the Fukushima disaster.

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The Safecast project has produced an elegant map that shows how complicated the Fukushima disaster will be for the Japanese government to recover from. While there are predictably elevated levels of radiation immediately around the Fukushima plant and in the 18 mile exclusion zones, there is a “plume” of increased radiation south and west of the reactors. The map is produced from millions of radiation readings collected by volunteers, who generally take readings while driving – Safecast’s bGeigie meter automatically takes readings every few seconds and stores them along with associated GPS coordinates for later upload to the server.
This long and thoughtful blog post about the progress of government decontamination efforts, the cost-benefit of those efforts, and the government’s transparency or opacity around cleanup gives a sense for what Safecast is trying to do: provide ways for citizens to check and verify government efforts and understand the complexity of decisions about radiation exposure. This is especially important in Japan, as there’s been widespread frustration over the failures of TEPCO to make progress on cleaning up the reactor site, leading to anger and suspicion about the larger cleanup process.
For me, Safecast raises two interesting questions:
– If you’re not getting trustworthy or sufficient information from your government, can you use crowdsourcing, citizen science or other techniques to generate that data?
– How does collecting data relate to civic engagement? Is it a path towards increased participation as an engaged and effective citizen?
To have some time to reflect on these questions, I decided I wanted to try some of my own radiation monitoring. I borrowed Joi Ito’s bGeigie and set off for my local Spent Nuclear Fuel and Greater-Than-Class C Low Level Radioactive Waste dry cask storage facility…

Projects like Safecast – and the projects I’m exploring this coming year under the heading of citizen infrastructure monitoring – have a challenge. Most participants aren’t going to uncover Ed Snowden-calibre information by driving around with a geiger counter or mapping wells in their communities. Lots of data collected is going to reveal that governments and corporations are doing their jobs, as my data suggests. It’s easy to track a path between collecting groundbreaking data and getting involved with deeper civic and political issues – will collecting data that the local nuclear plant is apparently safe get me more involved with issues of nuclear waste disposal?
It just might. One of the great potentials of citizen science and citizen infrastructure monitoring is the possibility of reducing the exotic to the routine….”

Index: The Data Universe

The Living Library Index – inspired by the Harper’s Index – provides important statistics and highlights global trends in governance innovation. This installment focuses on the data universe and was originally published in 2013.

  • How much data exists in the digital universe as of 2012: 2.7 zetabytes*
  • Increase in the quantity of Internet data from 2005 to 2012: +1,696%
  • Percent of the world’s data created in the last two years: 90
  • Number of exabytes (=1 billion gigabytes) created every day in 2012: 2.5; that number doubles every month
  • Percent of the digital universe in 2005 created by the U.S. and western Europe vs. emerging markets: 48 vs. 20
  • Percent of the digital universe in 2012 created by emerging markets: 36
  • Percent of the digital universe in 2020 predicted to be created by China alone: 21
  • How much information in the digital universe is created and consumed by consumers (video, social media, photos, etc.) in 2012: 68%
  • Percent of which enterprises have liability or responsibility for (copyright, privacy, compliance with regulations, etc.): 80
  • Amount included in the Obama Administration’s 2-12 Big Data initiative: over $200 million
  • Amount the Department of Defense is investing annually on Big Data projects as of 2012: over $250 million
  • Data created per day in 2012: 2.5 quintillion bytes
  • How many terabytes* of data collected by the U.S. Library of Congress as of April 2011: 235
  • How many terabytes of data collected by Walmart per hour as of 2012: 2,560, or 2.5 petabytes*
  • Projected growth in global data generated per year, as of 2011: 40%
  • Number of IT jobs created globally by 2015 to support big data: 4.4 million (1.9 million in the U.S.)
  • Potential shortage of data scientists in the U.S. alone predicted for 2018: 140,000-190,000, in addition to 1.5 million managers and analysts with the know-how to use the analysis of big data to make effective decisions
  • Time needed to sequence the complete human genome (analyzing 3 billion base pairs) in 2003: ten years
  • Time needed in 2013: one week
  • The world’s annual effective capacity to exchange information through telecommunication networks in 1986, 2007, and (predicted) 2013: 281 petabytes, 65 exabytes, 667 exabytes
  • Projected amount of digital information created annually that will either live in or pass through the cloud: 1/3
  • Increase in data collection volume year-over-year in 2012: 400%
  • Increase in number of individual data collectors from 2011 to 2012: nearly double (over 300 data collection parties in 2012)

*1 zetabyte = 1 billion terabytes | 1 petabyte = 1,000 terabytes | 1 terabyte = 1,000 gigabytes | 1 gigabyte = 1 billion bytes


Internet Governance is Our Shared Responsibility

New paper by Vint Cerf, Patrick Ryan and Max Senges Senges: “This essay looks at the the different roles that multistakeholder institutions play in the Internet governance ecosystem. We propose a model for thinking of Internet governance within the context of the Internet’s layered model. We use the example of the negotiations in Dubai in 2102 at the World Conference on International Telecommunications as an illustration for why it is important for different institutions within the governance system to focus on their respective areas of expertise (e.g., the ITU, ICANN, and IGF). Several areas of conflict (a “tussle”) are reviewed, such as the desire to promote more broadband infrastructure, a topic that is in the remit of the International Telecommunications Union, but also the recurring desire of countries like Russia and China to use the ITU to regulate content and restrict free expression on the Internet through onerous cybersecurity and spam provisions. We conclude that it is folly to try and regulate all these areas through an international treaty, and encourage further development of mechanisms for global debate like the Internet Governance Forum (IGF).”

China Law Translate (CLT), a collaborative translation project.

“CLT allows many users to translate small pieces of legal texts between Chinese and English, to promote mutual understanding and provide a resource to legal professionals around the world. The sum of these small pieces, contributed in any order or no order at all, gradually creates a completed translation. You can translate as little or as much as you like, or leave comments to discuss the work of others or suggest better translations.
Quick Start: 1. open a post 2. Select Language you want to translate INTO 3. Open Tranlator Mode. 4. Translate…
We aim to create complete translations of important Chinese laws and articles, but some of the articles you view may still be incomplete or translated less than fluently. Bear with us, we are a new resource and getting there slowly. If you are able,, help us improve the translations you see!”

The Impact and Effectiveness of Transparency and Accountability Initiatives: Freedom of Information

New paper in Development Policy Review: “Analysis of the impact and effectiveness of Freedom of Information (FOI) legislation has been hampered by lack of systematic evidence and conceptual confusion about what kind of right it represents. This article discusses some of the main conceptual parameters of FOI theory, before reviewing the available evidence from a range of studies. It presents case studies of civil-society activism on FOI in India and South Africa to illustrate the extent to which access to information is having an impact, in particular on socio-economic conditions. After reviewing the range of approaches used, it concludes that the academic community and the FOI community of practice need to come together to devise robust and rigorous methodologies.”

Facebook Is Being Redefined by Its Developing World Users

Tom Simonite in MIT Technology Review: “…as Facebook’s user base continues to expand, a growing proportion of its users think of it quite differently, as a luxury brand, badge of status, and or even a place to make a little extra money. That’s due to the rapid growth in the number of Facebook users signing on from developing countries, a trend underscored by news from the company today that more than 100 million people use a mobile app the company makes for feature phones
Little research has been done on Facebook’s growth in developing countries (and a lot would be needed to capture even some of the diversity included under the blanket term “developing world”). Two small, recent studies of Kenyan Facebook users in poor areas by Susan Wyche of Michigan State University are among the first to be published, and they provide some interesting insights.
One of Wyche’s ethnographic studies took place in rural Internet cafes, where the researchers were told that “Facebook is a luxury,” only to be indulged if someone had money to spare (here’s a PDF of Wyche’s paper). When study participants thought about social networking, the challenges of low bandwidth and sometimes unreliable electricity supplies were foremost in their minds.
The barriers of cost and infrastructure associated with Facebook led people in another community Wyche and colleagues visited, a slum of Nairobi, to see the service as for more than just socializing. They used it—with mixed success—as a way to make a little money, look for jobs, market themselves, and seek remittances from friends and family overseas. (This reminded me of a recent report on people in Kuwait using Instagram to sell things and run retail businesses.)…
Should it want to, Facebook could even become a powerful tool for efforts to improve the lives of people in poor areas, where the site is gaining traction. The company has already dabbled with using social engineering to boost organ donations in the U.S. (see “Thank God for Facebook: When Platforms Proselytize”). There’s no shortage of similar experiments that could be run in places with more fundamental health problems, where Facebook’s status as a luxury could make it very influential.”

The Science of Familiar Strangers: Society’s Hidden Social Network

The Physics arXiv Blog “We’ve all experienced the sense of being familiar with somebody without knowing their name or even having spoken to them. These so-called “familiar strangers” are the people we see every day on the bus on the way to work, in the sandwich shop at lunchtime, or in the local restaurant or supermarket in the evening.
These people are the bedrock of society and a rich source of social potential as neighbours, friends, or even lovers.
But while many researchers have studied the network of intentional links between individuals—using mobile-phone records, for example—little work has been on these unintentional links, which form a kind of hidden social network.
Today, that changes thanks to the work of Lijun Sun at the Future Cities Laboratory in Singapore and a few pals who have analysed the passive interactions between 3 million residents on Singapore’s bus network (about 55 per cent of the city’s population).  ”This is the first time that such a large network of encounters has been identied and analyzed,” they say.
The results are a fascinating insight into this hidden network of familiar strangers and the effects it has on people….
Perhaps the most interesting result involves the way this hidden network knits society together. Lijun and co say that the data hints that the connections between familiar strangers grows stronger over time. So seeing each other more often increases the chances that familiar strangers will become socially connected.
That’s a fascinating insight into the hidden social network in which we are all embedded. It’s important because it has implications for our understanding of the way things like epidemics can spread through cities.
Perhaps a more interesting is the insight it gives into how links form within communities and how these can strengthened. With the widespread adoption of smart cards on transport systems throughout the world, this kind of study can easily be repeated in many cities, which may help to tease apart some of the factors that make them so different.”
Ref: Understanding Metropolitan Patterns of Daily Encounters