The Alchemist Butterfly
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The Alchemist Butterfly
Ideas about effortless change
Curated by Lucho Osorio
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M4P and UHC: How M4P in Health Supports Development
Policy Objectives and Universal Health Coverage

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The jobs and poverty paradox | DFID bloggers

The jobs and poverty paradox | DFID bloggers | The Alchemist Butterfly | Scoop.it
Staff blogs from the UK Department for International Development. Get real-life perspectives from those on the ground to fight poverty and join in the debate.
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#wageworkmatters

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Exploring complex networks : Article : Nature

Exploring complex networks : Article : Nature | The Alchemist Butterfly | Scoop.it
Nature is the international weekly journal of science: a magazine style journal that publishes full-length research papers in all disciplines of science, as well as News and Views, reviews, news, features, commentaries, web focuses and more,...
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#modelthinkingcourse

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The Impact of Labor Market Regulation on Employment in Low; Income Countries: A Meta Analysis

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Lucho Osorio's insight:

#wageworkmatters

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What to do with 'big data' when we don't yet have a theory of complex systems

What to do with 'big data' when we don't yet have a theory of complex systems | The Alchemist Butterfly | Scoop.it
As the world becomes increasingly complex and interconnected, some of our biggest challenges have begun to seem intractable. What should we do about uncertainty in the financial markets? How can we predict energy supply and demand? How will climate change play out? How do we cope with rapid urbanization? Our traditional approaches to these problems are often qualitative and disjointed and lead to unintended consequences. To bring scientific rigor to the challenges of our time, we need to develop a deeper understanding of complexity itself.

Via Ashish Umre
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NetLogo User Community Models: Dissemination of Culture

NetLogo User Community Models: Dissemination of Culture | The Alchemist Butterfly | Scoop.it
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#modelthinkingcourse

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Tipping points paper

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This paper formally defines tipping points as a discontinuity between current and future states of a system and introduces candidate measures of when a system tips based on changes in the probability distribution over future states. 


We make two categorical distinctions between types of tips relevant in social contexts: The first differentiates between direct tips and contextual tips. A direct tip occurs when a gradual change in the value of a variable leads to a large, i.e. discontinuous, jump in that same variable in the future. 


A contextual tip occurs when a gradual change in the value of one variable leads to a discontinuous jump in some other variable of interest. 


We argue that while scholars and writers often focus on direct tips, contextual tips often make direct tips possible, such as when human rights conditions in a state deteriorate creating the potential for an uprising. 


The second differentiates tips between outcomes that belong to the same class – such as tips from one equilibrium to another – from tips that result in a change in the outcome class, such as tips that occur when an equilibrium system becomes chaotic or complex.

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