In 2015, the UN adopted a new set of Sustainable Development Goals (SDGs) to eradicate poverty, establish socioeconomic inclusion and protect the environment. Critical voices such as the International Council for Science (ICSU), however, have expressed concerns about the potential incompatibility of the SDGs, specifically the incompatibility of socio-economic development and environmental sustainability. In this paper, we test, quantify and model the alleged inconsistency of SDGs. Our analyses show which SDGs are consistent and which are conflicting. We measure the extent of inconsistency and conclude that the SDG agenda will fail as a whole if we continue with business as usual. We further explore the nature of the inconsistencies using dynamical systems models, which reveal that the focus on economic growth and consumption as a means for development underlies the inconsistency. Our models also show that there are factors which can contribute to development (health programmes, government investment) on the one hand and ecological sustainability (renewable energy) on the other, without triggering the conflict between incompatible SDGs. ARTICLE HISTORY

Data arising from social systems is often highly complex, involving non-linear relationships between the macro-level variables that characterize these systems. We present a method for analyzing this type of longitudinal or panel data using differential equations. We identify the best non-linear functions that capture interactions between variables, employing Bayes factor to decide how many interaction terms should be included in the model. This method punishes overly complicated models and identifies models with the most explanatory power. We illustrate our approach on the classic example of relating democracy and economic growth, identifying non-linear relationships between these two variables. We show how multiple variables and variable lags can be accounted for and provide a toolbox in R to implement our approach.

Over the past decades many countries have experienced rapid changes in their economies, their democratic institutions and the values of their citizens. Comprehensive data measuring these changes across very different countries has recently become openly available. Between country similarities suggest common underlying dynamics in how countries develop in terms of economy, democracy and cultural values. We apply a novel Bayesian dynamical systems approach to identify the model which best captures the complex, mainly non-linear dynamics that underlie these changes. We show that the level of Human Development Index (HDI) in a country drives first democracy and then higher emancipation of citizens. This change occurs once the countries pass a certain threshold in HDI. The data also suggests that there is a limit to the growth of wealth, set by higher emancipation. Having reached a high level of democracy and emancipation, societies tend towards equilibrium that does not support further economic growth. Our findings give strong empirical evidence against a popular political science theory, known as the Human Development Sequence. Contrary to this theory, we find that implementation of human-rights and democratisation precede increases in emancipative values.

Gait and movement asymmetries are important variables for assessing locomotor mechanics in humans and other animals and as a predictor of risk of injury and success of clinical interventions. The four indices used most often to assess symmetry are not well designed for different variable types and perform poorly when presented with cases of high asymmetry or when variables are of low magnitude and are easily influenced by small variation in the signal. The purpose of the present study was to test the performance of these indices on previously unpublished data on ACL-R patients and to propose a new index to resolve some of these limitations. The performance of four currently used indices and a new index-the Normalized Symmetry Index (NSI), which is scaled to the range of variables being tested across multiple trials-were compared using force and angular data on participants who had undergone anterior cruciate ligament reconstruction and healthy controls. The NSI performed well compared to all other indices with all variables and had the additional benefit of returning values that range from 0% (full symmetry) to ±100% (full asymmetry). Therefore, the NSI can serve as a universal index for assessing asymmetry in humans, nonhuman animal models, and in a clinical context for assessing risk for injury and clinical outcomes.

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