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Brain health diplomacy aims to influence the global policy environment for brain health (i.e. dementia, depression, and other mind/brain disorders) and bridges the disciplines of global brain health, international affairs, management, law, and economics. Determinants of brain health include educational attainment, diet, access to health care, physical activity, social support, and environmental exposures, as well as chronic brain disorders and treatment. Global challenges associated with these determinants include large-scale conflicts and consequent mass migration, chemical contaminants, air quality, socioeconomic status, climate change, and global population aging. Given the rapidly advancing technological innovations impacting brain health, it is paramount to optimize the benefits and mitigate the drawbacks of such technologies.
We propose a working model of Brain health INnovation Diplomacy (BIND).
We prepared a selective review using literature searches of studies pertaining to brain health technological innovation and diplomacy.
BIND aims to improve global brain health outcomes by leveraging technological innovation, entrepreneurship, and innovation diplomacy. It acknowledges the key role that technology, entrepreneurship, and digitization play and will increasingly play in the future of brain health for individuals and societies alike. It strengthens the positive role of novel solutions, recognizes and works to manage both real and potential risks of digital platforms. It is recognition of the political, ethical, cultural, and economic influences that brain health technological innovation and entrepreneurship can have.
By creating a framework for BIND, we can use this to ensure a systematic model for the use of technology to optimize brain health.
Adverse developmental outcomes for some children following institutional care are well established. Removal from institutional care and placement into families can promote recovery. However, little is known about how positive outcomes are sustained across adolescence among children with histories of severe deprivation. The present study examined the caregiving conditions that are associated with attaining and maintaining competent functioning (i.e., outcomes within typical levels) from middle childhood to adolescence following exposure to early institutional care. The participants included children with and without a history of institutional care who had competence assessed at ages 8, 12, and 16 years across seven domains: family relationships, peer relationships, academic performance, physical health, mental health, substance use (ages 12 and 16 years only), and risk-taking behavior. The participants were grouped based on whether they were always versus not always competent and never versus ever competent at ages 8 through 16 years. Adolescents with a history of institutional care were less likely to be consistently competent than those who were family reared. Among those who were exposed to early institutional rearing, maintaining competent functioning from 8 to 16 years was associated with spending less time in institutions and receiving higher-quality caregiving early in life. Ensuring high quality early caregiving may promote competent functioning following early deprivation.
We present examples to show that people and economic activities are unevenly distributed across space. The variations in density result in strong agglomeration in some important centres. We briefly analyse urban development and illustrate ‘spikiness’ at different spatial scales (global regions, countries, provinces, and counties). We also show that the distribution across space is not random but often displays a remarkably stable and uniform pattern across time and for various levels of geographical aggregation. These observations suggest that similar spatial economic forces are relevant for explaining agglomeration and the regularities of distribution and interaction across space.
The organization of space within cities is mainly driven by spatial equilibrium forces. This chapter argues that a person who is indifferent about living in two locations within the city must derive the same net utility from these locations. This allows us to explain how rent costs decline away from the city centre as people need to be adequately compensated for higher transportation costs. We can extend the basic framework to incorporate the choice of different transport methods, changes in the slope of the rent gradient, the choice of the amount of land to use (and thus population density), building height, individual heterogeneity, the role of amenities, and observed segregation within the city.
Power laws (and the special case of Zipf’s law) allow us to characterize cities on a map with a single number, namely the slope of a rank-size curve. These rank-size curves show the rank of a city as a function of its size: the biggest city gets rank 1, the second largest city rank 2, and so on. The slope tells us whether cities are relatively similar in size (small slope) or unevenly sized (steep slope). But what explains the existence of different sized cities? This chapter introduces some urban theories that explain the existence of different sized cities; a graphical representation of the Henderson model and a graphical representation of a state-of-the-art model of differentiated cities as developed by Davis and Dingle.
A comprehensive introduction to both urban and geographical economics: the two dominant approaches used to explain the distribution of economic activity across space. This fully revised and up-to-date third edition gives a full account of the ever-expanding body of knowledge and insights on urban and geographical economics, with an increased emphasis on analytical concepts and empirical methods, reflecting developments in the literature since the last edition. The authors provide both state-of-the-art theories and empirics, introducing new data, methods and models for this edition, including a whole chapter dedicated to measurement issues and empirical methods. Written in a style that is accessible to students who are new to the field, this textbook also includes more advanced concepts that will interest experienced researchers. Unrivalled in its scope and depth, this title is perfect for readers seeking to understand the uneven spatial distribution of economic activity between and within countries.
We introduce three alternative models that extend the core model of Chapter 7. First, the intermediate goods model includes intermediate production and inter-sectoral labour mobility, instead of inter-regional labour mobility. In some cases this leads to a bell-shaped curve instead of the tomahawk diagram, implying that agglomeration gradually rises and falls as transport costs decline. Second, the generalized model incorporates both the core model and the intermediate goods model in one framework. Third, the solvable model introduces a second production factor (such as human capital) in the manufacturing sector. This model leads to explicit solutions for factor rewards. We conclude with an empirical evaluation of urban power laws and show that adding congestion to the core model allows us to better understand the influence of parameter changes on estimated power law exponents.
First, we show that simple geographic forces play a role in understanding differences in current prosperity and income. This can be partially traced back to deep roots, such as the Agricultural Revolution, which allowed for a transition from a hunter-gatherer society to a farmer society and enabled the building of institutions (this gave the Eurasian continent a head start). Second, we analyse the importance of geo-human interaction for explaining current prosperity levels. There is special attention for the role of embodied institional knowledge incorporated in international migration flows for helping us understand the ancestry-adjusted impact of bio-geographic and institutional factors (which helps explain the reversal of fortune hypothesis). Eventually, bio-geographic factors are thus important for economic development levels, either directly or indirectly through geo-human interaction.
In this chapter, we analyse the rationale of regional policies, discuss the evidence, and highlight some methodological problems. In doing so, we also take a closer look at policy consequences that follow from or can be linked to the models discussed throughout the book. In some of our thought-experiments, we take the models of the book literally and ask, what would be the lessons for policy makers? When we discuss actual cluster/regional policy thinking, but also when we discuss hypothetical policies by sticking as closely as possible to our models, there are always three main elements to take into account. First, whether it is a people- or place-based policy (or a mix of these two). Second, to go beyond the observation that a policy can change spatial economic outcomes by showing that a policy is somehow welfare improving. Third, to take into consideration the important macro/micro distinction in terms of regional policy effectiveness: a ‘good’ regional policy at the city or regional level does not necessarily imply that it is also beneficial for the economy as whole. The main message of the chapter is that regional policies should be handled with care.
Economic activity is unevenly distributed across space, or spiky. Measuring this spikiness is not trivial. A good measure is comparable across space, comparable across sectors, unbiased regarding spatial and sector classification, and should provide a measure of significance. No measure fulfils all these criteria, but some are better than others. Once spikiness is identified the next question is ‘so what?’ Does spatial agglomeration stimulate productivity? Econometric methods to deal with this question and tackle the problem of reverse causality are: difference-in-differences, natural experiments, and regression discontinuity design. These techniques are introduced in this chapter.