Contributions of Participatory Budgeting to climate change adaptation and mitigation. Current local practices around the world & lessons from the field

This report builds on the contributions from two international sessions on the contributions of participatory budgeting (PB) to climate change adaptation and mitigation. It also draws on PB initiatives in 15 participating cities and regions from different continents. Its first objective is to describe and understand what is actually happening in the field and explore the extent to which PB contributes to climate change adaptation and mitigation, how it does so, and the current challenges facing PB actors. It assesses the nature and importance of these contributions: Are they marginal or not? How many projects are implemented each year? What do they cost and where do the resources come from? It highlights the numerous innovations that actors have introduced to integrate PB into climate adaptation and mitigation efforts. It finally raises questions for future explorations and advocates for climate-related participatory budgeting, raising awareness on its huge (and as yet largely untapped) potential to help addressing the dramatic impacts that climate change has on millions of people’s lives

Going Deeper with Spectral Embeddings

To make sense of millions of raw data and represent them efficiently, practitioners rely on representation learning. Recently, deep connections have been shown between these approaches and the spectral decompositions of some underlying operators. Historically, explicit spectral embeddings were built from graphs constructed on top of the data. In contrast, we propose two new methods to build spectral embeddings: one based on functional analysis principles and kernel methods, which leads to algorithms with theoretical guarantees, and the other based on deep networks trained to optimize principled variational losses, which yield practically efficient algorithms. Furthermore, we provide a new sampling algorithm that leverages learned representations to generate new samples in a single step

The contribution of participatory budgeting to the achievement of the Sustainable Development Goals: lessons for policy in Commonwealth countries

After briefly defining participatory budgeting and reviewing its evolution worldwide and Commonwealth expansion over the last three decades, this paper explores the potential it holds for contributing to the achievement of the United Nations’ Sustainable Development Goals. Its looks especially at how participatory budgeting is contributing to the achievement of SDG 16 and provides some specific recommendations for action, based on innovative practice examples from around the world, highlighting how practice across diverse local authorities could be used to monitor target 16.7 ‘to ensure responsive, inclusive, participatory and representative decision-making at all levels.

How many samples are needed to leverage smoothness?

A core principle in statistical learning is that smoothness of target functions allows to break the curse of dimensionality. However, learning a smooth function seems to require enough samples close to one another to get meaningful estimate of high-order derivatives, which would be hard in machine learning problems where the ratio between number of data and input dimension is relatively small. By deriving new lower bounds on the generalization error, this paper formalizes such an intuition, before investigating the role of constants and transitory regimes which are usually not depicted beyond classical learning theory statements while they play a dominant role in practice.Comment: 35 pages, 13 figure

A Case of Exponential Convergence Rates for SVM

Classification is often the first problem described in introductory machine learning classes. Generalization guarantees of classification have historically been offered by Vapnik-Chervonenkis theory. Yet those guarantees are based on intractable algorithms, which has led to the theory of surrogate methods in classification. Guarantees offered by surrogate methods are based on calibration inequalities, which have been shown to be highly sub-optimal under some margin conditions, failing short to capture exponential convergence phenomena. Those "super" fast rates are becoming to be well understood for smooth surrogates, but the picture remains blurry for non-smooth losses such as the hinge loss, associated with the renowned support vector machines. In this paper, we present a simple mechanism to obtain fast convergence rates and we investigate its usage for SVM. In particular, we show that SVM can exhibit exponential convergence rates even without assuming the hard Tsybakov margin condition.Comment: 16 pages, 6 figure

Financing urban agriculture

For most small urban farmers, the lack of access to financing is a major bottleneck in their capacity to maintain and expand their activities, and more generally in the potential for scaling up affordable food production in cities. This paper reports on action research undertaken by local teams in 17 cities of different size in Latin America, Asia and Africa. In each city, the teams examined how urban farmers are financing their activities along the value chain, essentially with their own resources, what the gaps are between their needs and the existing practices of public and private institutions with regard to finance, and what mechanisms and innovations can help to close this gap. Financing is defined here as a complex, dynamic combination of resource mobilization, both monetary and non-monetary, plus savings, subsidies and credits

The impact of the residential sphere on the territorial development (In French)

The residential sphere is developing according to householders localization and revenue. The sphere division (residential, productive and public) is difficult to apply because the frontiers are blurred, but it is useful to take into account new economic evolutions.\r\nThe residential sphere share is growing quickly in the global employment in France since 1990 to the detriment of the of the productive sphere share. This movement exists also in all regions and in numerous employment areas. It is explained by internal factors (productivity, consumption structure) and external factors (international competition). This economy is more important in the South and in the West of France which are more attractive for households. \r\nThe residential sphere contributes to economic development by numerous employment creations and best ability to resist to globalisation shocks; it leads often to reduction of inequality between territories. But this contribution is limited because productivity growth, wage level and job quality are lowest than in productive sphere. Residential growth cannot be generalized and his future depends of the continuity of growth of householders mobility and public and social budgets. \r\nresidential sphere, Productive sphere; employment, territories, development