Project acronym ALLEGRO
Project unrAvelLing sLow modE travelinG and tRaffic: with innOvative data to a new transportation and traffic theory for pedestrians and bicycles
Researcher (PI) Serge Hoogendoorn
Host Institution (HI) TECHNISCHE UNIVERSITEIT DELFT
Call Details Advanced Grant (AdG), SH3, ERC-2014-ADG
Summary A major challenge in contemporary traffic and transportation theory is having a comprehensive understanding of pedestrians and cyclists behaviour. This is notoriously hard to observe, since sensors providing abundant and detailed information about key variables characterising this behaviour have not been available until very recently. The behaviour is also far more complex than that of the much better understood fast mode. This is due to the many degrees of freedom in decision-making, the interactions among slow traffic participants that are more involved and far less guided by traffic rules and regulations than those between car-drivers, and the many fascinating but complex phenomena in slow traffic flows (self-organised patterns, turbulence, spontaneous phase transitions, herding, etc.) that are very hard to predict accurately.
With slow traffic modes gaining ground in terms of mode share in many cities, lack of empirical insights, behavioural theories, predictively valid analytical and simulation models, and tools to support planning, design, management and control is posing a major societal problem as well: examples of major accidents due to bad planning, organisation and management of events are manifold, as are locations where safety of slow modes is a serious issue due to interactions with fast modes.
This programme is geared towards establishing a comprehensive theory of slow mode traffic behaviour, considering the different behavioural levels relevant for understanding, reproducing and predicting slow mode traffic flows in cities. The levels deal with walking and cycling operations, activity scheduling and travel behaviour, and knowledge representation and learning. Major scientific breakthroughs are expected at each of these levels, in terms of theory and modelling, by using innovative (big) data collection and experimentation, analysis and fusion techniques, including social media data analytics, using augmented reality, and remote and crowd sensing.
Summary
A major challenge in contemporary traffic and transportation theory is having a comprehensive understanding of pedestrians and cyclists behaviour. This is notoriously hard to observe, since sensors providing abundant and detailed information about key variables characterising this behaviour have not been available until very recently. The behaviour is also far more complex than that of the much better understood fast mode. This is due to the many degrees of freedom in decision-making, the interactions among slow traffic participants that are more involved and far less guided by traffic rules and regulations than those between car-drivers, and the many fascinating but complex phenomena in slow traffic flows (self-organised patterns, turbulence, spontaneous phase transitions, herding, etc.) that are very hard to predict accurately.
With slow traffic modes gaining ground in terms of mode share in many cities, lack of empirical insights, behavioural theories, predictively valid analytical and simulation models, and tools to support planning, design, management and control is posing a major societal problem as well: examples of major accidents due to bad planning, organisation and management of events are manifold, as are locations where safety of slow modes is a serious issue due to interactions with fast modes.
This programme is geared towards establishing a comprehensive theory of slow mode traffic behaviour, considering the different behavioural levels relevant for understanding, reproducing and predicting slow mode traffic flows in cities. The levels deal with walking and cycling operations, activity scheduling and travel behaviour, and knowledge representation and learning. Major scientific breakthroughs are expected at each of these levels, in terms of theory and modelling, by using innovative (big) data collection and experimentation, analysis and fusion techniques, including social media data analytics, using augmented reality, and remote and crowd sensing.
Max ERC Funding
2 458 700 €
Duration
Start date: 2015-11-01, End date: 2020-10-31
Project acronym CAPTURE
Project CApturing Paradata for documenTing data creation and Use for the REsearch of the future
Researcher (PI) Isto HUVILA
Host Institution (HI) UPPSALA UNIVERSITET
Call Details Consolidator Grant (CoG), SH3, ERC-2018-COG
Summary "Considerable investments have been made in Europe and worldwide in research data infrastructures. Instead of a general lack of data about data, it has become apparent that the pivotal factor that drastically constrains the use of data is the absence of contextual knowledge about how data was created and how it has been used. This applies especially to many branches of SSH research where data is highly heterogeneous, both by its kind (e.g. being qualitative, quantitative, naturalistic, purposefully created) and origins (e.g. being historical/contemporary, from different contexts and geographical places). The problem is that there may be enough metadata (data about data) but there is too little paradata (data on the processes of its creation and use).
In contrast to the rather straightforward problem of describing the data, the high-risk/high-gain problem no-one has managed to solve, is the lack of comprehensive understanding of what information about the creation and use of research data is needed and how to capture enough of that information to make the data reusable and to avoid the risk that currently collected vast amounts of research data become useless in the future. The wickedness of the problem lies in the practical impossibility to document and keep everything and the difficulty to determine optimal procedures for capturing just enough.
With an empirical focus on archaeological and cultural heritage data, which stands out by its extreme heterogeneity and rapid accumulation due to the scale of ongoing development-led archaeological fieldwork, CAPTURE develops an in-depth understanding of how paradata is #1 created and #2 used at the moment, #3 elicits methods for capturing paradata on the basis of the findings of #1-2, #4 tests the new methods in field trials, and #5 synthesises the findings in a reference model to inform the capturing of paradata and enabling data-intensive research using heterogeneous research data stemming from diverse origins.
"
Summary
"Considerable investments have been made in Europe and worldwide in research data infrastructures. Instead of a general lack of data about data, it has become apparent that the pivotal factor that drastically constrains the use of data is the absence of contextual knowledge about how data was created and how it has been used. This applies especially to many branches of SSH research where data is highly heterogeneous, both by its kind (e.g. being qualitative, quantitative, naturalistic, purposefully created) and origins (e.g. being historical/contemporary, from different contexts and geographical places). The problem is that there may be enough metadata (data about data) but there is too little paradata (data on the processes of its creation and use).
In contrast to the rather straightforward problem of describing the data, the high-risk/high-gain problem no-one has managed to solve, is the lack of comprehensive understanding of what information about the creation and use of research data is needed and how to capture enough of that information to make the data reusable and to avoid the risk that currently collected vast amounts of research data become useless in the future. The wickedness of the problem lies in the practical impossibility to document and keep everything and the difficulty to determine optimal procedures for capturing just enough.
With an empirical focus on archaeological and cultural heritage data, which stands out by its extreme heterogeneity and rapid accumulation due to the scale of ongoing development-led archaeological fieldwork, CAPTURE develops an in-depth understanding of how paradata is #1 created and #2 used at the moment, #3 elicits methods for capturing paradata on the basis of the findings of #1-2, #4 tests the new methods in field trials, and #5 synthesises the findings in a reference model to inform the capturing of paradata and enabling data-intensive research using heterogeneous research data stemming from diverse origins.
"
Max ERC Funding
1 944 162 €
Duration
Start date: 2019-05-01, End date: 2024-04-30
Project acronym CEAD
Project Contextualizing Evidence for Action on Diabetes in low-resource Settings: A mixed-methods case study in Quito and Esmeraldas, Ecuador.
Researcher (PI) Lucy Anne Parker
Host Institution (HI) UNIVERSIDAD MIGUEL HERNANDEZ DE ELCHE
Call Details Starting Grant (StG), SH3, ERC-2018-STG
Summary The relentless rise in diabetes is one of the greatest global health emergencies of the 21st century. The increase is most pronounced in low and middle income countries where today three quarters of people with diabetes live and over 80% of the deaths attributed to non-communicable diseases occur. In light of the wealth of knowledge already available about how to tackle the problem, most major international organizations call for the adoption healthy public policies and initiatives to strengthening health systems. However, implementation of recommended action remains limited in many settings. Most evidence comes from high-income settings and may generate recommendations that cannot be successfully implemented in other settings without careful consideration and contextualization. I propose here that this “know-do” gap can be reduced by revealing the barriers to implementing evidence-based recommendations, engaging local stakeholders in developing context-led innovations and developing a tool-kit for contextualizing and implementing diabetes recommendations in low-resource settings. I plan the research in two carefully selected settings in Ecuador, with mixed-methods combining quantitative epidemiological research and qualitative methodology to generate the rich and varied knowledge that is required to trigger policy action and/or changes in care models. Furthermore, I will engage patients, community members, health workers and decision makers in the process of knowledge generation, interpretation and use. The overarching objective is hence, to explore the process by which global recommendations can be translated into context-specific, evidence-informed action for diabetes prevention in low-resource settings. The findings will support the global endeavour to bridge the global “know-do” gap, one of the most important public health challenges this century and a great opportunity for strengthening health systems and achieving health equity.
Summary
The relentless rise in diabetes is one of the greatest global health emergencies of the 21st century. The increase is most pronounced in low and middle income countries where today three quarters of people with diabetes live and over 80% of the deaths attributed to non-communicable diseases occur. In light of the wealth of knowledge already available about how to tackle the problem, most major international organizations call for the adoption healthy public policies and initiatives to strengthening health systems. However, implementation of recommended action remains limited in many settings. Most evidence comes from high-income settings and may generate recommendations that cannot be successfully implemented in other settings without careful consideration and contextualization. I propose here that this “know-do” gap can be reduced by revealing the barriers to implementing evidence-based recommendations, engaging local stakeholders in developing context-led innovations and developing a tool-kit for contextualizing and implementing diabetes recommendations in low-resource settings. I plan the research in two carefully selected settings in Ecuador, with mixed-methods combining quantitative epidemiological research and qualitative methodology to generate the rich and varied knowledge that is required to trigger policy action and/or changes in care models. Furthermore, I will engage patients, community members, health workers and decision makers in the process of knowledge generation, interpretation and use. The overarching objective is hence, to explore the process by which global recommendations can be translated into context-specific, evidence-informed action for diabetes prevention in low-resource settings. The findings will support the global endeavour to bridge the global “know-do” gap, one of the most important public health challenges this century and a great opportunity for strengthening health systems and achieving health equity.
Max ERC Funding
1 475 334 €
Duration
Start date: 2019-01-01, End date: 2023-12-31
Project acronym CHINAWHITE
Project The Reconfiguration of Whiteness in China: Privileges, Precariousness, and Racialized Performances
Researcher (PI) Shanshan LAN
Host Institution (HI) UNIVERSITEIT VAN AMSTERDAM
Call Details Consolidator Grant (CoG), SH3, ERC-2018-COG
Summary This research examines the multiple and contradictory constructions of whiteness in China as a result of the rapid diversification of white migrants in the country and the shifting power balances between China and the West. Existing literature on white westerners in Asia mainly focuses on transnational elites. The rising number of middle- and lower-stratum of white migrants in China deserves special attention due to substantial tensions and discrepancies in their experiences of racial privilege, economic insecurity, and legal vulnerability. Multi-sited and multi-scalar ethnographic research will be conducted on daily life encounters between various groups of white migrants and Chinese in five domains: (1) state policy regarding international migrants in China; (2) the ESL industry (teaching English as a second language); (3) the media, fashion, and entertainment industries; (4) transnational business and entrepreneurship; and (5) interracial romance. Three major research questions frame this project. 1. What are the symbolic and material advantages and disadvantages of being white in China’s thriving market economy and consumer culture? 2. How is whiteness racialized in relation to blackness and other immigrant minority identities in multiple social domains and at different geographical scales? 3. How are multiple versions of whiteness produced, interpreted, negotiated, and performed through daily life interactions between white migrants and Chinese in various social and personal settings? This project contributes to a new line of research on white racial formation in East Asia by creatively integrating theories in whiteness studies and migration studies. It also expands the geographical scope of research on white expatriates from global cities in coastal areas to second-tier cities in inland China.
Summary
This research examines the multiple and contradictory constructions of whiteness in China as a result of the rapid diversification of white migrants in the country and the shifting power balances between China and the West. Existing literature on white westerners in Asia mainly focuses on transnational elites. The rising number of middle- and lower-stratum of white migrants in China deserves special attention due to substantial tensions and discrepancies in their experiences of racial privilege, economic insecurity, and legal vulnerability. Multi-sited and multi-scalar ethnographic research will be conducted on daily life encounters between various groups of white migrants and Chinese in five domains: (1) state policy regarding international migrants in China; (2) the ESL industry (teaching English as a second language); (3) the media, fashion, and entertainment industries; (4) transnational business and entrepreneurship; and (5) interracial romance. Three major research questions frame this project. 1. What are the symbolic and material advantages and disadvantages of being white in China’s thriving market economy and consumer culture? 2. How is whiteness racialized in relation to blackness and other immigrant minority identities in multiple social domains and at different geographical scales? 3. How are multiple versions of whiteness produced, interpreted, negotiated, and performed through daily life interactions between white migrants and Chinese in various social and personal settings? This project contributes to a new line of research on white racial formation in East Asia by creatively integrating theories in whiteness studies and migration studies. It also expands the geographical scope of research on white expatriates from global cities in coastal areas to second-tier cities in inland China.
Max ERC Funding
2 000 000 €
Duration
Start date: 2019-06-01, End date: 2024-05-31
Project acronym CHRONO
Project Chronotype, health and family: The role of biology, socio- and natural environment and their interaction
Researcher (PI) Melinda MILLS
Host Institution (HI) THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD
Call Details Advanced Grant (AdG), SH3, ERC-2018-ADG
Summary The widespread use of electronic devices, artificial light and rise of the 24-hour economy means that more individuals experience disruption of their chronotype, which is the natural circadian rhythm that regulates sleep and activity levels. The natural and medical sciences focus on the natural environment (e.g., light exposure), genetics, biology and health consequences, whereas the social sciences have largely explored the socio-environment (e.g., working regulations) and psychological and familial consequences of nonstandard work schedules. For the first time CHRONO bridges these disparate disciplines to ask: What is the role of biology, the natural and socio-environment and their interaction on predicting and understanding resilience to chronotype disruption and how does this in turn impact an individual’s health (sleep, cancer, obesity, digestive problems) and family (partnership, children) outcomes? I propose to: (1) develop a multifactor interdisciplinary theoretical model; (2) disrupt data collection by crowdsourcing a sociogenomic dataset with novel measures; (3) discover and validate with informed machine learning innovative measures of chronotype (molecular genetic, accelerometer, microbiome, patient-record, self-reported) and the natural and socio-environment; (4) ask fundamentally new substantive questions to determine how chronotype disruption influences health and family outcomes and, via Biology x Environment interaction (BxE), whether this is moderated by the natural or socio-environment; and, (5) develop new statistical models and methods to cope with contentious issues, answer longitudinal questions and engage in novel quasi-experiments (e.g., policy and life course changes) to transcend description to identify endogenous factors and causal mechanisms. Interdisciplinary in the truest sense, CHRONO will overturn long-held substantive findings of the causes and consequences of chronotype disruption.
Summary
The widespread use of electronic devices, artificial light and rise of the 24-hour economy means that more individuals experience disruption of their chronotype, which is the natural circadian rhythm that regulates sleep and activity levels. The natural and medical sciences focus on the natural environment (e.g., light exposure), genetics, biology and health consequences, whereas the social sciences have largely explored the socio-environment (e.g., working regulations) and psychological and familial consequences of nonstandard work schedules. For the first time CHRONO bridges these disparate disciplines to ask: What is the role of biology, the natural and socio-environment and their interaction on predicting and understanding resilience to chronotype disruption and how does this in turn impact an individual’s health (sleep, cancer, obesity, digestive problems) and family (partnership, children) outcomes? I propose to: (1) develop a multifactor interdisciplinary theoretical model; (2) disrupt data collection by crowdsourcing a sociogenomic dataset with novel measures; (3) discover and validate with informed machine learning innovative measures of chronotype (molecular genetic, accelerometer, microbiome, patient-record, self-reported) and the natural and socio-environment; (4) ask fundamentally new substantive questions to determine how chronotype disruption influences health and family outcomes and, via Biology x Environment interaction (BxE), whether this is moderated by the natural or socio-environment; and, (5) develop new statistical models and methods to cope with contentious issues, answer longitudinal questions and engage in novel quasi-experiments (e.g., policy and life course changes) to transcend description to identify endogenous factors and causal mechanisms. Interdisciplinary in the truest sense, CHRONO will overturn long-held substantive findings of the causes and consequences of chronotype disruption.
Max ERC Funding
2 499 811 €
Duration
Start date: 2019-11-01, End date: 2024-10-31
Project acronym CRISP
Project Cognitive Aging: From Educational Opportunities to Individual Risk Profiles
Researcher (PI) Anja LEIST
Host Institution (HI) UNIVERSITE DU LUXEMBOURG
Call Details Starting Grant (StG), SH3, ERC-2018-STG
Summary Cognitive impairment and dementia have dramatic individual and social consequences, and create high economic costs for societies. In order to delay cognitive aging of future generations as long as possible, we need evidence about which contextual factors are most supportive for individuals to reach highest cognitive levels relative to their potential. At the same time, for current older generations, we need scalable methods to exactly identify individuals at risk of cognitive impairment. The project intends to apply recent methodological and statistical advancements to reach two objectives. Firstly, contextual influences on cognitive aging will be comparatively assessed, with a focus on inequalities related to educational opportunities and gender inequalities. This will be done using longitudinal, population-representative, harmonized cross-national aging surveys, merged with contextual information. Secondly, the project will quantify the ability of singular and clustered individual characteristics, such as indicators of cognitive reserve and behaviour change, to predict cognitive aging and diagnosis of dementia. Project methodology will rely partly on parametric ‘traditional’ multilevel- or fixed-effects modelling, partly on non-parametric statistical learning approaches, to address objectives both hypothesis- and data-driven. Applying statistical learning techniques in the field of cognitive reserve will open new research avenues for efficient handling of large amounts of data, among which most prominently the accurate prediction of health and disease outcomes. Quantifying the role of contextual inequalities related to education and gender will guide policymaking in and beyond the project. Assessing risk profiles of individuals in relation to cognitive aging will support efficient and scalable risk screening of individuals. Identifying the value of behaviour change to delay cognitive impairment will guide treatment plans for individuals affected by dementia.
Summary
Cognitive impairment and dementia have dramatic individual and social consequences, and create high economic costs for societies. In order to delay cognitive aging of future generations as long as possible, we need evidence about which contextual factors are most supportive for individuals to reach highest cognitive levels relative to their potential. At the same time, for current older generations, we need scalable methods to exactly identify individuals at risk of cognitive impairment. The project intends to apply recent methodological and statistical advancements to reach two objectives. Firstly, contextual influences on cognitive aging will be comparatively assessed, with a focus on inequalities related to educational opportunities and gender inequalities. This will be done using longitudinal, population-representative, harmonized cross-national aging surveys, merged with contextual information. Secondly, the project will quantify the ability of singular and clustered individual characteristics, such as indicators of cognitive reserve and behaviour change, to predict cognitive aging and diagnosis of dementia. Project methodology will rely partly on parametric ‘traditional’ multilevel- or fixed-effects modelling, partly on non-parametric statistical learning approaches, to address objectives both hypothesis- and data-driven. Applying statistical learning techniques in the field of cognitive reserve will open new research avenues for efficient handling of large amounts of data, among which most prominently the accurate prediction of health and disease outcomes. Quantifying the role of contextual inequalities related to education and gender will guide policymaking in and beyond the project. Assessing risk profiles of individuals in relation to cognitive aging will support efficient and scalable risk screening of individuals. Identifying the value of behaviour change to delay cognitive impairment will guide treatment plans for individuals affected by dementia.
Max ERC Funding
1 148 290 €
Duration
Start date: 2019-01-01, End date: 2023-12-31
Project acronym CWASI
Project Coping with water scarcity in a globalized world
Researcher (PI) Francesco Laio
Host Institution (HI) POLITECNICO DI TORINO
Call Details Consolidator Grant (CoG), SH3, ERC-2014-CoG
Summary We intend to set up a new globalized perspective to tackle water and food security in the 21st century. This issue is intrinsically global as the international trade of massive amounts of food makes societies less reliant on locally available water, and entails large-scale transfers of virtual water (defined as the water needed to produce a given amount of a food commodity). The network of virtual water trade connects a large portion of the global population, with 2800 km3 of virtual water moved around the globe in a year. We provide here definitive indications on the effects of the globalization of (virtual) water on the vulnerability to a water crisis of the global water system. More specifically, we formulate the following research hypotheses:
1) The globalization of (virtual) water resources is a short-term solution to malnourishment, famine, and conflicts, but it also has relevant negative implications for human societies.
2) The virtual water dynamics provide the suitable framework in order to quantitatively relate water-crises occurrence to environmental and socio-economic factors.
3) The risk of catastrophic, global-scale, water crises will increase in the next decades.
To test these hypotheses, we will capitalize on the tremendous amount of information embedded in nearly 50 years of available food and virtual water trade data. We will adopt an innovative research approach based on the use of: advanced statistical tools for data verification and uncertainty modeling; methods borrowed from the complex network theory, aimed at analyzing the propagation of failures through the network; multivariate nonlinear analyses, to reproduce the dependence of virtual water on time and on external drivers; multi-state stochastic modeling, to study the effect on the global water system of random fluctuations of the external drivers; and scenario analysis, to predict the future probability of occurrence of water crises.
Summary
We intend to set up a new globalized perspective to tackle water and food security in the 21st century. This issue is intrinsically global as the international trade of massive amounts of food makes societies less reliant on locally available water, and entails large-scale transfers of virtual water (defined as the water needed to produce a given amount of a food commodity). The network of virtual water trade connects a large portion of the global population, with 2800 km3 of virtual water moved around the globe in a year. We provide here definitive indications on the effects of the globalization of (virtual) water on the vulnerability to a water crisis of the global water system. More specifically, we formulate the following research hypotheses:
1) The globalization of (virtual) water resources is a short-term solution to malnourishment, famine, and conflicts, but it also has relevant negative implications for human societies.
2) The virtual water dynamics provide the suitable framework in order to quantitatively relate water-crises occurrence to environmental and socio-economic factors.
3) The risk of catastrophic, global-scale, water crises will increase in the next decades.
To test these hypotheses, we will capitalize on the tremendous amount of information embedded in nearly 50 years of available food and virtual water trade data. We will adopt an innovative research approach based on the use of: advanced statistical tools for data verification and uncertainty modeling; methods borrowed from the complex network theory, aimed at analyzing the propagation of failures through the network; multivariate nonlinear analyses, to reproduce the dependence of virtual water on time and on external drivers; multi-state stochastic modeling, to study the effect on the global water system of random fluctuations of the external drivers; and scenario analysis, to predict the future probability of occurrence of water crises.
Max ERC Funding
1 222 500 €
Duration
Start date: 2015-07-01, End date: 2020-06-30
Project acronym DAFINET
Project Dynamic Attitude Fixing: A novel theory of opinion dynamics in social networks and its implications for computational propaganda in hybrid social networks (containing humans and bots)
Researcher (PI) Michael QUAYLE
Host Institution (HI) UNIVERSITY OF LIMERICK
Call Details Starting Grant (StG), SH3, ERC-2018-STG
Summary Understanding the coordination of attitudes in societies is vitally important for many disciplines and global social challenges. Network opinion dynamics are poorly understood, especially in hybrid networks where automated (bot) agents seek to influence economic or political processes (e.g. USA: Trump vs Clinton; UK: Brexit). A dynamic fixing theory of attitudes is proposed, premised on three features of attitudes demonstrated in ethnomethodology and social psychology; that people: 1) simultaneously hold a repertoire of multiple (sometimes ambivalent) attitudes, 2) express attitudes to enact social identity; and 3) are accountable for attitude expression in interaction. It is proposed that interactions between agents generate symbolic links between attitudes with the emergent social-symbolic structure generating perceived ingroup similarity and outgroup difference in a multilayer network. Thus attitudes can become dynamically fixed when constellations of attitudes are locked-in to identities via multilayer networks of attitude agreement and disagreement; a process intensified by conflict, threat or zero-sum partisan processes (e.g. elections/referenda). Agent-based simulations will validate the theory and explore the hypothesized channels of bot influence. Network experiments with human and hybrid networks will test theoretically derived hypotheses. Observational network studies will assess model fit using historical Twitter data. Results will provide a social-psychological-network theory for attitude dynamics and vulnerability to computational propaganda in hybrid networks.
The theory will explain:
(a) when and how consensus can propagate rapidly through networks (since identity processes fix attitudes already contained within repertoires);
(b) limits of identity-related attitude propagation (since attitudes outside of repertoires will not be easily adopted); and
(c) how attitudes can often ‘roll back’ after events (since contextual changes ‘unfix’ attitudes).
Summary
Understanding the coordination of attitudes in societies is vitally important for many disciplines and global social challenges. Network opinion dynamics are poorly understood, especially in hybrid networks where automated (bot) agents seek to influence economic or political processes (e.g. USA: Trump vs Clinton; UK: Brexit). A dynamic fixing theory of attitudes is proposed, premised on three features of attitudes demonstrated in ethnomethodology and social psychology; that people: 1) simultaneously hold a repertoire of multiple (sometimes ambivalent) attitudes, 2) express attitudes to enact social identity; and 3) are accountable for attitude expression in interaction. It is proposed that interactions between agents generate symbolic links between attitudes with the emergent social-symbolic structure generating perceived ingroup similarity and outgroup difference in a multilayer network. Thus attitudes can become dynamically fixed when constellations of attitudes are locked-in to identities via multilayer networks of attitude agreement and disagreement; a process intensified by conflict, threat or zero-sum partisan processes (e.g. elections/referenda). Agent-based simulations will validate the theory and explore the hypothesized channels of bot influence. Network experiments with human and hybrid networks will test theoretically derived hypotheses. Observational network studies will assess model fit using historical Twitter data. Results will provide a social-psychological-network theory for attitude dynamics and vulnerability to computational propaganda in hybrid networks.
The theory will explain:
(a) when and how consensus can propagate rapidly through networks (since identity processes fix attitudes already contained within repertoires);
(b) limits of identity-related attitude propagation (since attitudes outside of repertoires will not be easily adopted); and
(c) how attitudes can often ‘roll back’ after events (since contextual changes ‘unfix’ attitudes).
Max ERC Funding
1 499 925 €
Duration
Start date: 2018-12-01, End date: 2023-11-30
Project acronym DecentLivingEnergy
Project Energy and emissions thresholds for providing decent living standards to all
Researcher (PI) Narasimha Desirazu Rao
Host Institution (HI) INTERNATIONALES INSTITUT FUER ANGEWANDTE SYSTEMANALYSE
Call Details Starting Grant (StG), SH3, ERC-2014-STG
Summary There is confusion surrounding how poverty eradication will contribute to climate change. This is due to knowledge gaps related to the material basis of poverty, and the relationship between energy and human development. Addressing this issue rigorously requires bridging gaps between global justice, economics, energy systems analysis, and industrial ecology, and applying this knowledge to projections of anthropogenic greenhouse gases. This project will develop a body of knowledge that quantifies the energy needs and related climate change impacts for providing decent living standards to all. The research will address three questions: which goods and services, and with what characteristics, constitute ‘decent living standards’? What energy resources are required to provide these goods and services in different countries, and what impact will this energy use have on climate change? How do the constituents of decent living and their energy needs evolve as countries develop? The first task will operationalize basic needs views of human development and advance their empirical validity by discerning characteristics of basic goods in household consumption patterns. The second will quantify the energy needs (and climate-related emissions) for decent living constituents and reveal their dependence on culture, climate, technology, and other contextual conditions in countries. This will be done using lifecycle analysis and input-output analysis, and mapping energy to climate change using state-of-the-art energy-economy integrated assessment modelling tools for 5 emerging economies that face the challenges of eradicating poverty and mitigating climate change. The third task will shed light on path dependencies and trends in the evolution of basic goods and their energy intensity using empirical analysis. This research will identify opportunities to shift developing societies towards low-carbon pathways, and help quantify burden-sharing arrangements for climate mitigation.
Summary
There is confusion surrounding how poverty eradication will contribute to climate change. This is due to knowledge gaps related to the material basis of poverty, and the relationship between energy and human development. Addressing this issue rigorously requires bridging gaps between global justice, economics, energy systems analysis, and industrial ecology, and applying this knowledge to projections of anthropogenic greenhouse gases. This project will develop a body of knowledge that quantifies the energy needs and related climate change impacts for providing decent living standards to all. The research will address three questions: which goods and services, and with what characteristics, constitute ‘decent living standards’? What energy resources are required to provide these goods and services in different countries, and what impact will this energy use have on climate change? How do the constituents of decent living and their energy needs evolve as countries develop? The first task will operationalize basic needs views of human development and advance their empirical validity by discerning characteristics of basic goods in household consumption patterns. The second will quantify the energy needs (and climate-related emissions) for decent living constituents and reveal their dependence on culture, climate, technology, and other contextual conditions in countries. This will be done using lifecycle analysis and input-output analysis, and mapping energy to climate change using state-of-the-art energy-economy integrated assessment modelling tools for 5 emerging economies that face the challenges of eradicating poverty and mitigating climate change. The third task will shed light on path dependencies and trends in the evolution of basic goods and their energy intensity using empirical analysis. This research will identify opportunities to shift developing societies towards low-carbon pathways, and help quantify burden-sharing arrangements for climate mitigation.
Max ERC Funding
869 722 €
Duration
Start date: 2015-06-01, End date: 2019-05-31
Project acronym Digital Good
Project The Digital Disruption of Health Research and the Common Good. An Empirical-Philosophical Study
Researcher (PI) Tamar Sharon
Host Institution (HI) STICHTING KATHOLIEKE UNIVERSITEIT
Call Details Starting Grant (StG), SH3, ERC-2018-STG
Summary In the last three years, every major consumer technology company has moved into the health research domain. We are witnessing a digital disruption of health research, or a “Googlization of health research” (GHR). This project will be the first wide-ranging, interdisciplinary study of GHR. Its aim is to develop a normative framework for personal health data governance in this setting, where digital health and digital capitalism, and codes of research ethics and the lawlessness of the Internet economy, intersect.
I contend that the most pressing challenge at stake in this new model of research is less the question of individual privacy than the question of collective and societal welfare, and that existing governance frameworks that seek to increase individual control over data are ill-suited to address this. Commons- and solidarity-based approaches, which seek to enhance collective agency and control, are thus promising alternatives. However, these approaches allow for only one conception of the common good, while a plurality of competing conceptions are at work in GHR, including “increased efficiency”, “greater inclusivity”, and “economic growth”. This plurality must be taken seriously to avoid theory-practice discrepancies and to develop viable governance solutions.
The project will develop a normative framework that can both foreground collective benefit all the while accounting for this ethical plurality. To do this, my team will first map the different conceptions of the common good – or “moral repertoires” – that motivate actors in several GHR-type collaborations. Using an empirical-philosophical methodology, we will critically evaluate these repertoires and the value trade-offs they involve in practice. Next, we will explore the viability of commons- and solidarity-based approaches in light of this. Finally, these results will be integrated into a novel, empirically-robust normative framework that can offer guidance to research ethicists and policy makers.
Summary
In the last three years, every major consumer technology company has moved into the health research domain. We are witnessing a digital disruption of health research, or a “Googlization of health research” (GHR). This project will be the first wide-ranging, interdisciplinary study of GHR. Its aim is to develop a normative framework for personal health data governance in this setting, where digital health and digital capitalism, and codes of research ethics and the lawlessness of the Internet economy, intersect.
I contend that the most pressing challenge at stake in this new model of research is less the question of individual privacy than the question of collective and societal welfare, and that existing governance frameworks that seek to increase individual control over data are ill-suited to address this. Commons- and solidarity-based approaches, which seek to enhance collective agency and control, are thus promising alternatives. However, these approaches allow for only one conception of the common good, while a plurality of competing conceptions are at work in GHR, including “increased efficiency”, “greater inclusivity”, and “economic growth”. This plurality must be taken seriously to avoid theory-practice discrepancies and to develop viable governance solutions.
The project will develop a normative framework that can both foreground collective benefit all the while accounting for this ethical plurality. To do this, my team will first map the different conceptions of the common good – or “moral repertoires” – that motivate actors in several GHR-type collaborations. Using an empirical-philosophical methodology, we will critically evaluate these repertoires and the value trade-offs they involve in practice. Next, we will explore the viability of commons- and solidarity-based approaches in light of this. Finally, these results will be integrated into a novel, empirically-robust normative framework that can offer guidance to research ethicists and policy makers.
Max ERC Funding
1 323 473 €
Duration
Start date: 2019-01-01, End date: 2023-12-31
