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From Local to Global Dilemmas in Social Networks

From Local to Global Dilemmas in Social Networks | Papers | Scoop.it

Social networks affect in such a fundamental way the dynamics of the population they support that the global, population-wide behavior that one observes often bears no relation to the individual processes it stems from. Up to now, linking the global networked dynamics to such individual mechanisms has remained elusive.

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How Evolution Learns to Generalise: Principles of under-fitting, over-fitting and induction in the evolution of developmental organisation

One of the most intriguing questions in evolution is how organisms exhibit suitable phenotypic variation to rapidly adapt in novel selective environments which is crucial for evolvability. Recent work showed that when selective environments vary in a systematic manner, it is possible that development can constrain the phenotypic space in regions that are evolutionarily more advantageous. Yet, the underlying mechanism that enables the spontaneous emergence of such adaptive developmental constraints is poorly understood. How can natural selection, given its myopic and conservative nature, favour developmental organisations that facilitate adaptive evolution in future previously unseen environments? Such capacity suggests a form of \textit{foresight} facilitated by the ability of evolution to accumulate and exploit information not only about the particular phenotypes selected in the past, but regularities in the environment that are also relevant to future environments. Here we argue that the ability of evolution to discover such regularities is analogous to the ability of learning systems to generalise from past experience. Conversely, the canalisation of evolved developmental processes to past selective environments and failure of natural selection to enhance evolvability in future selective environments is directly analogous to the problem of over-fitting and failure to generalise in machine learning. We show that this analogy arises from an underlying mechanistic equivalence by showing that conditions corresponding to those that alleviate over-fitting in machine learning enhance the evolution of generalised developmental organisations under natural selection. This equivalence provides access to a well-developed theoretical framework that enables us to characterise the conditions where natural selection will find general rather than particular solutions to environmental conditions.


How Evolution Learns to Generalise: Principles of under-fitting, over-fitting and induction in the evolution of developmental organisation
Kostas Kouvaris, Jeff Clune, Louis Kounios, Markus Brede, Richard A. Watson

http://arxiv.org/abs/1508.06854

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Impact of mobility structure on the optimization of small-world networks of mobile agents

In ad hoc wireless networking, units are connected to each other rather than to a central, fixed, infrastructure. Constructing and maintaining such networks create several trade-off problems between robustness, communication speed, power consumption, etc., that bridges engineering, computer science and the physics of complex systems. In this work, we address the role of mobility patterns of the agents on the optimal tuning of a small-world type network construction method. By this method, the network is updated periodically and held static between the updates. We investigate the optimal updating times for different scenarios of the movement of agents (modeling, for example, the fat-tailed trip distances, and periodicities, of human travel). We find that these mobility patterns affect the power consumption in non-trivial ways and discuss how these effects can best be handled.


Impact of mobility structure on the optimization of small-world networks of mobile agents
Eun Lee, Petter Holme

http://arxiv.org/abs/1509.00224

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Nonlocal effects and counter measures in cascading failures

We study the propagation of cascading failures in complex supply networks with a focus on nonlocal effects occurring far away from the initial failure. It is shown that a high clustering and a small average path length of a network generally suppress nonlocal overloads. These properties are typical for many real-world networks, often called small-world networks, such that cascades propagate mostly locally in these networks. Furthermore, we analyze the spatial aspects of countermeasures based on the intentional removal of additional edges. Nonlocal actions are generally required in networks which have a low redundancy and are thus especially vulnerable to cascades.


Nonlocal effects and counter measures in cascading failures
Dirk Witthaut, Marc Timme

http://arxiv.org/abs/1509.00570

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Life’s a Gas: A Thermodynamic Theory of Biological Evolution

This paper outlines a thermodynamic theory of biological evolution. Beginning with a brief summary of the parallel histories of the modern evolutionary synthesis and thermodynamics, we use four physical laws and processes (the first and second laws of thermodynamics, diffusion and the maximum entropy production principle) to frame the theory. Given that open systems such as ecosystems will move towards maximizing dispersal of energy, we expect biological diversity to increase towards a level, Dmax, representing maximum entropic production (Smax). Based on this theory, we develop a mathematical model to predict diversity over the last 500 million years. This model combines diversification, post-extinction recovery and likelihood of discovery of the fossil record. We compare the output of this model with that of the observed fossil record. The model predicts that life diffuses into available energetic space (ecospace) towards a dynamic equilibrium, driven by increasing entropy within the genetic material. This dynamic equilibrium is punctured by extinction events, which are followed by restoration of Dmax through diffusion into available ecospace. Finally we compare and contrast our thermodynamic theory with the MES in relation to a number of important characteristics of evolution (progress, evolutionary tempo, form versus function, biosphere architecture, competition and fitness).


Life’s a Gas: A Thermodynamic Theory of Biological Evolution
Keith R. Skene

Entropy 2015, 17(8), 5522-5548; http://dx.doi.org/10.3390/e17085522 ;

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Gary Bamford's curator insight, September 1, 3:04 AM

Bit of a slog but worth it - the Brownian motion of life!

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Forest health in a changing world

Recognizing the signs of ill forest health and teasing apart the causes are important both for sustaining the services that humans rely on and for the effective conservation of forest biomes. Understanding how we influence forest health and function is a key challenge for the future, as we increasingly realize the importance of forests to the maintenance of a healthy planet.


Forest health in a changing world
Andrew Sugden, Julia Fahrenkamp-Uppenbrink, David Malakoff, Sacha Vignieri

Science 21 August 2015:
Vol. 349 no. 6250 pp. 800-801
http://dx.doi.org/10.1126/science.349.6250.800 ;

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Plant microbiome blueprints

Just as the number of petals in a flower or the number of limbs on an animal follow predictable rules, host-associated microbial communities (“microbiomes”) have predictable compositions. At the level of bacterial phylum, the structure of the host-associated microbiome is conserved across individuals of a species (1, 2). The consistency and predictability of host-associated microbiomes—like many of the phenotypes of a particular multicellular organism—suggest that they too may, in part, be under the regulation of a genetic blueprint. Indeed, evidence in animals shows that through production of broad-spectrum antimicrobials, the innate immune system shapes the composition of the gut microbiome (3, 4). On page 860 of this issue, Lebeis et al. (5) reveal a critical role of the plant hormone salicylic acid in determining the higher-order organization of the root-associated microbiome of the reference plant Arabidopsis thaliana.


Plant microbiome blueprints
Cara H. Haney, Frederick M. Ausubel

Science 21 August 2015:
Vol. 349 no. 6250 pp. 788-789
http://dx.doi.org/10.1126/science.aad0092 

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Hierarchical mutual information for the comparison of hierarchical community structures in complex networks

The quest for a quantitative characterization of community and modular structure of complex networks produced a variety of methods and algorithms to classify different networks. However, it is not clear if such methods provide consistent, robust and meaningful results when considering hierarchies as a whole. Part of the problem is the lack of a similarity measure for the comparison of hierarchical community structures. In this work we give a contribution by introducing the {\it hierarchical mutual information}, which is a generalization of the traditional mutual information, and allows to compare hierarchical partitions and hierarchical community structures. The {\it normalized} version of the hierarchical mutual information should behave analogously to the traditional normalized mutual information. Here, the correct behavior of the hierarchical mutual information is corroborated on an extensive battery of numerical experiments. The experiments are performed on artificial hierarchies, and on the hierarchical community structure of artificial and empirical networks. Furthermore, the experiments illustrate some of the practical applications of the hierarchical mutual information. Namely, the comparison of different community detection methods, and the study of the the consistency, robustness and temporal evolution of the hierarchical modular structure of networks.


Hierarchical mutual information for the comparison of hierarchical community structures in complex networks
Juan Ignacio Perotti, Claudio Juan Tessone, Guido Caldarelli

http://arxiv.org/abs/1508.04388

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Artificial Life Art, Creativity, and Techno-hybridization (editor's introduction)

Artists and engineers have devised lifelike technology for millennia. Their ingenious devices have often prompted inquiry into our preferences, prejudices, and beliefs about living systems, especially regarding their origins, status, constitution, and behavior. A recurring fabrication technique is shared across artificial life art, science, and engineering. This involves aggregating representations or re-creations of familiar biological parts—techno-hybridization—but the motives of practitioners may differ markedly. This article, and the special issue it introduces, explores how ground familiar to contemporary artificial life science and engineering has been assessed and interpreted in parallel by (a) artists and (b) theorists studying creativity explicitly. This activity offers thoughtful, alternative perspectives on artificial life science and engineering, highlighting and sometimes undermining the fields' underlying assumptions, or exposing avenues that are yet to be explored outside of art. Additionally, art has the potential to engage the general public, supporting and exploring the findings of scientific research and engineering. This adds considerably to the maturity of a culture tackling the issues the discipline of artificial life raises.


Artificial Life Art, Creativity, and Techno-hybridization (editor's introduction)
Alan Dorin

Artificial Life

Summer 2015, Vol. 21, No. 3, Pages 261-270
http://dx.doi.org/10.1162/ARTL_e_00166 ;

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Creativity and ALife

Three forms of creativity are exemplified in biology and studied in ALife. Combinational creativity exists as the first step in genetic algorithms. Exploratory creativity is seen in models using cellular automata or evolutionary programs. Transformational creativity can result from evolutionary programming. Even radically novel forms can do so, given input from outside the program itself. Transformational creativity appears also in reaction-diffusion models of morphogenesis. That there are limits to biological creativity is suggested by ALife work bearing on instances of biological impossibility.


Creativity and ALife
Margaret A. Boden

Artificial Life

Summer 2015, Vol. 21, No. 3, Pages 354-365
http://dx.doi.org/10.1162/ARTL_a_00176 

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Engineering an Anthropocene Citizenship Framework

This article presents an Anthropocene citizen-cantered framework by incorporating the neuroscience of sustainability related stressors, the biology of collaboration in multi-agent ecosystems such as urban systems, and by emphasising on the importance of harnessing the collective intelligence of the crowd in addressing wicked challenges of sustainable development. The Anthropocene citizenship framework aims to transcend the cognitive model of global citizenship and sustainability to a dynamic, resilient and thriving mental model of collective cooperation.


Engineering an Anthropocene Citizenship Framework
Shima Beigi

http://arxiv.org/abs/1508.03525 

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The joy of transient chaos

The joy of transient chaos | Papers | Scoop.it

We intend to show that transient chaos is a very appealing, but still not widely appreciated, subfield of nonlinear dynamics. Besides flashing its basic properties and giving a brief overview of the many applications, a few recent transient-chaos-related subjects are introduced in some detail. These include the dynamics of decision making, dispersion, and sedimentation of volcanic ash, doubly transient chaos of undriven autonomous mechanical systems, and a dynamical systems approach to energy absorption or explosion.

 

The joy of transient chaos   

Tamás Tél

Chaos 25, 097619 (2015)

http://dx.doi.org/10.1063/1.4917287 

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Graphene kirigami

The ratio of in-plane stiffness to out-of-plane bending stiffness of graphene is shown to be similar to that of a piece of paper, which allows ideas from kirigami (a variation of origami that allows cutting) to be applied to micrometre-scale graphene sheets to build mechanically stretchable yet robust electrodes, springs and hinges.


Graphene kirigami
• Melina K. Blees, Arthur W. Barnard, Peter A. Rose, Samantha P. Roberts, Kathryn L. McGill, Pinshane Y. Huang, Alexander R. Ruyack, Joshua W. Kevek, Bryce Kobrin, David A. Muller & Paul L. McEuen

Nature 524, 204–207 (13 August 2015) http://dx.doi.org/10.1038/nature14588 ;

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Non-parametric estimation of Fisher information from real data

The Fisher Information matrix is a widely used measure for applications ranging from statistical inference, information geometry, experiment design, to the study of criticality in biological systems. Yet there is no commonly accepted non-parametric algorithm to estimate it from real data. In this rapid communication we show how to accurately estimate the Fisher information in a nonparametric way. We also develop a numerical procedure to minimize the errors by choosing the interval of the finite difference scheme necessary to compute the derivatives in the definition of the Fisher information. Our method uses the recently published "Density Estimation using Field Theory" algorithm to compute the probability density functions for continuous densities. We use the Fisher information of the normal distribution to validate our method and as an example we compute the temperature component of the Fisher Information Matrix in the two dimensional Ising model and show that it obeys the expected relation to the heat capacity and therefore peaks at the phase transition at the correct critical temperature.

 

"Non-parametric estimation of Fisher information from real data"
Omri Har Shemesh, Rick Quax, Borja Miñano, Alfons G. Hoekstra, Peter M. A. Sloot
arXiv:1507.00964 [stat.CO], 2014
http://arxiv.org/abs/1507.00964

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Multiplex networks in metropolitan areas: generic features and local effects

Most large cities are spanned by more than one transportation system. These different modes of transport have usually been studied separately: it is however important to understand the impact on urban systems of the coupling between them and we report in this paper an empirical analysis of the coupling between the street network and the subway for the two large metropolitan areas of London and New York. We observe a similar behaviour for network quantities related to quickest paths suggesting the existence of generic mechanisms operating beyond the local peculiarities of the specific cities studied. An analysis of the betweenness centrality distribution shows that the introduction of underground networks operate as a decentralising force creating congestions in places located at the end of underground lines. Also, we find that increasing the speed of subways is not always beneficial and may lead to unwanted uneven spatial distributions of accessibility. In fact, for London -- but not for New York -- there is an optimal subway speed in terms of global congestion. These results show that it is crucial to consider the full, multimodal, multi-layer network aspects of transportation systems in order to understand the behaviour of cities and to avoid possible negative side-effects of urban planning decisions.


Multiplex networks in metropolitan areas: generic features and local effects
Emanuele Strano, Saray Shai, Simon Dobson, Marc Barthelemy

http://arxiv.org/abs/1508.07265

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Sex differences in social focus across the lifecycle in humans

Age and gender are two important factors that play crucial roles in the way organisms allocate their social effort. In this study, we analyse a large mobile phone dataset to explore the way lifehistory influences human sociality and the way social networks are structured. Our results indicate that these aspects of human behaviour are strongly related to the age and gender such that younger individuals have more contacts and, among them, males more than females. However, the rate of decrease in the number of contacts with age differs between males and females, such that there is a reversal in the number of contacts around the late 30s. We suggest that this pattern can be attributed to the difference in reproductive investments that are made by the two sexes. We analyse the inequality in social investment patterns and suggest that the age and gender-related differences that we find reflect the constraints imposed by reproduction in a context where time (a form of social capital) is limited.


Sex differences in social focus across the lifecycle in humans
Kunal Bhattacharya, Asim Ghosh, Daniel Monsivais, Robin I. M. Dunbar, Kimmo Kaski

http://arxiv.org/abs/1508.06878

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The multi-layer network nature of systemic risk and its implications for the costs of financial crises

•We present a multi-layer network approach to quantify systemic-risk.
•Systemic-risk is drastically underestimated when computed on single layers only, as is current practice.
•We introduce a nation-wide systemic-risk index that reflects the public costs for crises.
•The index unveils drastically higher risk than estimated by current risk indicators.
•We demonstrate the validity of the method on a complete dataset of the Mexican financial system.


The multi-layer network nature of systemic risk and its implications for the costs of financial crises
Sebastian Poledna, José Luis Molina-Borboa, Serafín Martínez-Jaramillo, , Marco van der Leij, Stefan Thurner

http://dx.doi.org/10.1016/j.jfs.2015.08.001 

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The unique ecology of human predators

Paradigms of sustainable exploitation focus on population dynamics of prey and yields to humanity but ignore the behavior of humans as predators. We compared patterns of predation by contemporary hunters and fishers with those of other predators that compete over shared prey (terrestrial mammals and marine fishes). Our global survey (2125 estimates of annual finite exploitation rate) revealed that humans kill adult prey, the reproductive capital of populations, at much higher median rates than other predators (up to 14 times higher), with particularly intense exploitation of terrestrial carnivores and fishes. Given this competitive dominance, impacts on predators, and other unique predatory behavior, we suggest that humans function as an unsustainable “super predator,” which—unless additionally constrained by managers—will continue to alter ecological and evolutionary processes globally.


The unique ecology of human predators
Chris T. Darimont, Caroline H. Fox, Heather M. Bryan, Thomas E. Reimchen

Science 21 August 2015:
Vol. 349 no. 6250 pp. 858-860
http://dx.doi.org/10.1126/science.aac4249 

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Colloidal matter: Packing, geometry, and entropy

Colloidal particles, which consist of clusters of hundreds or thousands of atoms, can still resemble atomic systems. In particular, colloids have been used to study the packing of spheres and the influence of short-range interactions on crystallization and melting. Manoharan reviews these similarities, as well as the cases in which colloidal particles show behavior not seen in atomic systems. For example, the packing of nonspherical objects, where geometry or topology may matter, can give insights into the role of entropy in packing.


Colloidal matter: Packing, geometry, and entropy
Vinothan N. Manoharan

Science 28 August 2015:
Vol. 349 no. 6251
http://dx.doi.org/10.1126/science.1253751

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SMART DATA: Running the Internet of Things as a Citizen Web

Moore's law, describing the exponential explosion of processing power and data production, is currently driving a fundamental transformation of our economy and society. While processing power doubles every 18 months, data volumes double every 12 months, which means that we literally produce as much data in one year as in the entire history of humankind (i.e. all previous years). However, this is not the end of the digital revolution. More and more "things" are now equipped with communicating sensors - fridges, coffee machines, tooth brushes, smartphones and smart devices. In ten years, this will connect 150 billion "things" with each other - and with 10 billion people. This creates the "Internet of Everything" and data volumes that double every 12 hours rather than every 12 months. How will this impact our society?


http://futurict.blogspot.ch/2015/08/smart-data-running-internet-of-things.html 

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An Entangled Model for Sustainability Indicators

An Entangled Model for Sustainability Indicators | Papers | Scoop.it

Nowadays the challenge for humanity is to find pathways towards sustainable development. Decision makers require a set of sustainability indicators to know if the sustainability strategies are following those pathways. There are more than one hundred sustainability indicators but they differ on their relative importance according to the size of the locality and change on time. The resources needed to follow these sustainability indicators are scarce and in some instances finite, especially in smaller regions. Therefore strategies to select set of these indicators are useful for decision makers responsible for monitoring sustainability. In this paper we propose a model for the identification and selection of a set of sustainability indicators that adequately represents human systems. 


Vázquez P, del Río JA, Cedano KG, Martínez M, Jensen HJ (2015) An Entangled Model for Sustainability Indicators. PLoS ONE 10(8): e0135250. http://dx.doi.org/10.1371/journal.pone.0135250

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SustainOurEarth's curator insight, August 26, 6:00 PM

add your insight ...

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Fundamental limitations of network reconstruction

Network reconstruction helps us understand, diagnose and control complex networked systems by inferring properties of their interaction matrices, which characterize how nodes in the systems directly interact with each other. Despite a decade of extensive studies, network reconstruction remains an outstanding challenge. The fundamental limitations on which properties of the interaction matrix can be inferred from accessing the dynamics of individual nodes remain unknown. Here we characterize these fundamental limitations by deriving the necessary and sufficient condition to reconstruct any property of the interaction matrix. Counterintuitively, we prove that inferring less information ---such as the sign/connectivity pattern or the degree sequence--- does not make the network reconstruction problem easier than recovering the interaction matrix itself (i.e. the traditional parameter identification problem). Our analysis also reveals that using prior information of the interaction matrix ---such as bound on the edge-weights--- is the only way to circumvent these fundamental limitations of network reconstruction. This sheds light on designing new algorithms with practical improvements over parameter identification methods.


Fundamental limitations of network reconstruction
Marco Tulio Angulo, Jaime A. Moreno, Albert-László Barabási, Yang-Yu Liu

http://arxiv.org/abs/1508.03559

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Supersampling and Network Reconstruction of Urban Mobility

Understanding human mobility is of vital importance for urban planning, epidemiology, and many other fields that draw policies from the activities of humans in space. Despite the recent availability of large-scale data sets of GPS traces or mobile phone records capturing human mobility, typically only a subsample of the population of interest is represented, giving a possibly incomplete picture of the entire system under study. Methods to reliably extract mobility information from such reduced data and to assess their sampling biases are lacking. To that end, we analyzed a data set of millions of taxi movements in New York City. We first show that, once they are appropriately transformed, mobility patterns are highly stable over long time scales. Based on this observation, we develop a supersampling methodology to reliably extrapolate mobility records from a reduced sample based on an entropy maximization procedure, and we propose a number of network-based metrics to assess the accuracy of the predicted vehicle flows. Our approach provides a well founded way to exploit temporal patterns to save effort in recording mobility data, and opens the possibility to scale up data from limited records when information on the full system is required.


Sagarra O, Szell M, Santi P, Díaz-Guilera A, Ratti C (2015) Supersampling and Network Reconstruction of Urban Mobility. PLoS ONE 10(8): e0134508. http://dx.doi.org/10.1371/journal.pone.0134508 ;

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The collaborative roots of corruption

Recent financial scandals highlight the devastating consequences of corruption. While much is known about individual immoral behavior, little is known about the collaborative roots of curruption. In a novel experimental paradigm, people could adhere to one of two competing moral norms: collaborate vs. be honest. Whereas collaborative settings may boost honesty due to increased observability, accountability, and reluctance to force others to become accomplices, we show that collaboration, particularly on equal terms, is inductive to the emergence of corruption. When partners' profits are not aligned, or when individuals complete a comparable task alone, corruption levels drop. These findings reveal a dark side of collaboration, suggesting that human cooperative tendencies, and not merely greed, take part in shaping corruption.


The collaborative roots of corruption
Ori Weisela and Shaul Shalvi

PNAS

http://dx.doi.org/10.1073/pnas.1423035112 


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The developmental dynamics of marmoset monkey vocal production

As human infants grow, their vocalizations change from cries, to babbles, to words. This pattern has been presumed to be absent from other primates. Indeed, the development of bird song is often regarded as a closer approximation of human language development. Takahashi et al., however, observed that marmoset cries and calls in the first 2 months after birth mature in much the same way as they do in humans (see the Perspective by Margoliash and Tchernichovski). Calls changed as the infants' vocal structures grew and were influenced by feedback from their parents.


The developmental dynamics of marmoset monkey vocal production
D. Y. Takahashi, A. R. Fenley, Y. Teramoto, D. Z. Narayanan, J. I. Borjon, P. Holmes, A. A. Ghazanfar

Science 14 August 2015:
Vol. 349 no. 6249 pp. 734-738
http://dx.doi.org/10.1126/science.aab1058 

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Can randomized trials eliminate global poverty?

Can randomized trials eliminate global poverty? | Papers | Scoop.it

A new generation of economists is trying to transform global development policy through the power of randomized controlled trials.


http://www.nature.com/news/can-randomized-trials-eliminate-global-poverty-1.18176 

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