When One Dimensional Models Fail: Complexifying Models of Knowledge Construction

One dimensional models of reflective practice do not incorporate spirituality and social responsibility. Theological reflection, a form of reflective practice, is contextualized by a vision of social responsibility and the use of spirituality. An alternative model of reflective practice is proposed for spirituality and socially responsive learning at work.

Social Capital and International Migration from Latin America

We combine data from the Latin American Migration Project and the Mexican Migration Project to estimate models predicting the likelihood of taking of first and later trips to the United States from five nations: Mexico, the Dominican Republic, Costa Rica, Nicaragua, and Peru. The models test specific hypotheses about the effects of social capital on international migration and how these effects vary with respect to contextual factors. Our findings confirm the ubiquity of migrant networks and the universality of social capital effects throughout Latin America. They also reveal how the sizes of these effects are not uniform across settings. Social capital operates more powerfully on first as opposed to later trips and interacts with the cost of migration. In addition, effects are somewhat different when considering individual social capital (measuring strong ties) and community social capital (measuring weak ties). On first trips, the effect of strong ties in promoting migration increases with distance whereas the effect of weak ties decreases with distance. On later trips, the direction of effects for both individual and community social capital is negative for long distances but positive for short distances.

Learning Data-Driven Models of Non-Verbal Behaviors for Building Rapport Using an Intelligent Virtual Agent

There is a growing societal need to address the increasing prevalence of behavioral health issues, such as obesity, alcohol or drug use, and general lack of treatment adherence for a variety of health problems. The statistics, worldwide and in the USA, are daunting. Excessive alcohol use is the third leading preventable cause of death in the United States (with 79,000 deaths annually), and is responsible for a wide range of health and social problems. On the positive side though, these behavioral health issues (and associated possible diseases) can often be prevented with relatively simple lifestyle changes, such as losing weight with a diet and/or physical exercise, or learning how to reduce alcohol consumption. Medicine has therefore started to move toward finding ways of preventively promoting wellness, rather than solely treating already established illness. Evidence-based patient-centered Brief Motivational Interviewing (BMI) interven- tions have been found particularly effective in helping people find intrinsic motivation to change problem behaviors after short counseling sessions, and to maintain healthy lifestyles over the long-term. Lack of locally available personnel well-trained in BMI, however, often limits access to successful interventions for people in need. To fill this accessibility gap, Computer-Based Interventions (CBIs) have started to emerge. Success of the CBIs, however, critically relies on insuring engagement and retention of CBI users so that they remain motivated to use these systems and come back to use them over the long term as necessary. Because of their text-only interfaces, current CBIs can therefore only express limited empathy and rapport, which are the most important factors of health interventions. Fortunately, in the last decade, computer science research has progressed in the design of simulated human characters with anthropomorphic communicative abilities. Virtual characters interact using humans’ innate communication modalities, such as facial expressions, body language, speech, and natural language understanding. By advancing research in Artificial Intelligence (AI), we can improve the ability of artificial agents to help us solve CBI problems. To facilitate successful communication and social interaction between artificial agents and human partners, it is essential that aspects of human social behavior, especially empathy and rapport, be considered when designing human-computer interfaces. Hence, the goal of the present dissertation is to provide a computational model of rapport to enhance an artificial agent’s social behavior, and to provide an experimental tool for the psychological theories shaping the model. Parts of this thesis were already published in [LYL+12, AYL12, AL13, ALYR13, LAYR13, YALR13, ALY14].

Influência do jet lag social em marcadores circadianos de atividade - repouso e cardíaco em estudantes de medicina

Studies reveal that in recent decades a decrease in sleep duration has occurred. Social commitments, such as work and school are often not aligned to the "biological time" of individuals. Added to this, there is a reduced force of zeitgeber caused by less exposure to daylight and larger exposure to evenings. This causes a chronic sleep debt that is offset in a free days. Indeed, a restriction and extent of sleep called "social Jet lag" occurs weekly. Sleep deprivation has been associated to obesity, cancer, and cardiovascular risk. It is suggested that the autonomic nervous system is a pathway that connects sleep problems to cardiovascular diseases. However, beyond the evidence demonstrated by studies using models of acute and controlled sleep deprivation, studies are needed to investigate the effects of chronic sleep deprivation as it occurs in the social jet lag. The aim of this study was to investigate the influence of social jet lag in circadian rest-activity markers and heart function in medical students. It is a cross-sectional, observational study conducted in the Laboratory of Neurobiology and Biological Rhythmicity (LNRB) at the Department of Physiology UFRN. Participated in the survey medical students enrolled in the 1st semester of their course at UFRN. Instruments for data collection: Munich Chronotype Questionnaire, Morningness Eveningness Questionnaire of Horne and Östberg, Pittsburgh Sleep Quality Index, Epworth Sleepiness Scale, Actimeter; Heart rate monitor. Analysed were descriptive variables of sleep, nonparametric (IV60, IS60, L5 and M10) and cardiac indexes of time domain, frequency (LF, HF LF / HF) and nonlinear (SD1, SD2, SD1 / SD2). Descriptive, comparative and correlative statistical analysis was performed with SPSS software version 20. 41 students participated in the study, 48.8% (20) females and 51.2% (21) males, 19.63 ± 2.07 years. The social jet lag had an average of 02: 39h ± 00:55h, 82.9% (34) with social jet lag ≥ 1h and there was a negative correlation with the Munich chronotype score indicating greater sleep deprivation in subjects prone to eveningness. Poor sleep quality was detected in 90.2% (37) (X2 = 26.56, p <0.001) and 56.1% (23) excessive daytime sleepiness (X2 = 0.61, p = 0.435). Significant differences were observed in the values of LFnu, HFnu and LF / HF between the groups of social jet lag <2h and ≥ 2h and correlation of the social jet lag with LFnu (rs = 0.354, p = 0.023), HFnu (rs = - 0.354 , p = 0.023) and LF / HF (r = 0.355, p = 0.023). There was also a negative association between IV60 and indexes in the time domain and non-linear. It is suggested that chronic sleep deprivation may be associated with increased sympathetic activation promoting greater cardiovascular risk.

Narratividade e estruturas cognitivas: o encontro entre a linguagem, a cognição e a experiência sociocultural

This work is within the framework of Cognitive Linguistics, which, as opposed to generative modular approach posits that language is not autonomous but part of human cognition manifest mental processing, socio-cultural and bodily experiences. Our goal is to describe and analyze cognitive mechanisms of understanding who work in the formal and meaningful organization of the narrative. In order to study and verification of this phenomenon, this project was based in the theoretical framework of Rapaport et al (1994) with the treatment of deictic center, Zwaan (1999) and Zwaan and Radvansky (1998) with situation models, Minsky (1974) with the concept frame, Johnson (1987) and Duke and Costa (2012) with pictorial schemes. To this end, we focused on the deictic perspective (WHERE, WHEN, WHO), social cognitive structures (frames) and body (pictorial diagrams) and the situation of models built by compreendedor from these cognitive structures. Methodologically, it is a qualitative research (BAUER and GASKELL, 2002), of interpretive base (MOITA LOPES, 1994), based on introspection (Talmy, 2005). The corpus selected is a sample of twelve texts written by 8th grade students, whose production consists of fictional narrative, the production of diary pages. The analyses were conducted by cognitive structures known as constructional blocks (BCs)(SANTOS, 2011), which guid the discussion about how we build understanding and creation of meanings in narratives. The result shows that the narrative events are mentally represented by the understander that conceives a deictic center and that, guided by it, has access to understanding and construction of meaning in narrative by means of cognitive domains established by bodily and socio-cultural experiences.

Economia criativa e estratégia como prática social: uma abordagem teórico-empírico-conceitual a partir de ambientes criativos de grupos musicais

This study seeks to identify how creative environments of musical groups are configured in the Strategy as Practice perspective as theoretical, empirical and conceptual models. It develops within the theoretical framework, discussions on the context of the Creative Economy, Creative Industries, creative environment, organizational paradigm of Creative Economy, music as a creative environment and business, design and dynamics of Strategy as Practice and conjecture about the contextualism and other epistemological currents. The study is shaped as an exploratory and descriptive research, utilizing the qualitative method and being characterized as a Grounded Theory. A total of four musical groups of different styles, markets and areas of operation with over ten years of activity were surveyed. The Grounded Theory and simple observation methods were used for both data collection and analysis. The software ATLAS.ti. was used to help with the analysis. The research shows that the bands perceive the specialized expertise in the virtual social media as a strategic differentiator. It also shows that the groups nourish individuation and the differentiation in their relationship with the individual. Finally, it validates that these organizations get teams involved and value the dynamic design of their routines in strategic decision making, paying attention to a strategic social bias. Strategy and Creative Practice is the main category that emerged from the data. This category is explained through the three aforementioned results. It shows that organizations that are part of the Creative Economy perform simultaneously and dynamically creative and strategic making at both artistic and managerial levels.The theory created is validated by the principles of degree of coherence, functionality, relevance, flexibility, density and integration, and it is inserted in the contextualism principle, which points the knowledge as related to the context in which it is placed and discussed.

Efeito de diferentes divisões territoriais na flutuação aleatória de indicadores socioeconômicos relacionados à determinação social da saúde

This research aimed to analyse the effect of different territorial divisions in the random fluctuation of socio-economic indicators related to social determinants of health. This is an ecological study resulting from a combination of statistical methods including individuated and aggregate data analysis, using five databases derived from the database of the Brazilian demographic census 2010: overall results of the sample by weighting area. These data were grouped into the following levels: households; weighting areas; cities; Immediate Urban Associated Regions and Intermediate Urban Associated Regions. A theoretical model related to social determinants of health was used, with the dependent variable Household with death and as independent variables: Black race; Income; Childcare and school no attendance; Illiteracy; and Low schooling. The data was analysed in a model related to social determinants of health, using Poisson regression in individual basis, multilevel Poisson regression and multiple linear regression in light of the theoretical framework of the area. It was identified a greater proportion of households with deaths among those with at least one black resident, lower-income, illiterate, who do not attend or attended school or day-care and less educated. The analysis of the adjusted model showed that most adjusted prevalence ratio was related to Income, where there is a risk value of 1.33 for households with at least one resident with lower average personal income to R$ 655,00 (Brazilian current). The multilevel analysis demonstrated that there was a context effect when the variables were subjected to the effects of areas, insofar as the random effects were significant for all models and with different prevalence rates being higher in the areas with smaller dimensions - Weighting areas with coefficient of 0.035 and Cities with coefficient of 0.024. The ecological analyses have shown that the variable Income and Low schooling presented explanatory potential for the outcome on all models, having income greater power to determine the household deaths, especially in models related to Immediate Urban Associated Regions with a standardized coefficient of -0.616 and regions intermediate urban associated regions with a standardized coefficient of -0.618. It was concluded that there was a context effect on the random fluctuation of the socioeconomic indicators related to social determinants of health. This effect was explained by the characteristics of territorial divisions and individuals who live or work there. Context effects were better identified in the areas with smaller dimensions, which are more favourable to explain phenomena related to social determinants of health, especially in studies of societies marked by social inequalities. The composition effects were better identified in the Regions of Urban Articulation, shaped through mechanisms similar to the phenomenon under study.

Coupled symplectic maps as models for subdiffusive processes in disordered Hamiltonian lattices

Acknowledgements One of us (T. B.) acknowledges many interesting discussions on coupled maps with Professor C. Tsallis. We are also grateful to the anonymous referees for their constructive feedback that helped us improve the manuscript and to the HPCS Laboratory of the TEI of Western Greece for providing the computer facilities where all our simulations were performed. C. G. A. was partially supported by the “EPSRC EP/I032606/1” grant of the University of Aberdeen. This research has been co-financed by the European Union (European Social Fund - ESF) and Greek national funds through the Operational Program “Education and Lifelong Learning” of the National Strategic Reference Framework (NSRF) - Research Funding Program: THALES - Investing in knowledge society through the European Social Fund.

Coupled symplectic maps as models for subdiffusive processes in disordered Hamiltonian lattices

Acknowledgements One of us (T. B.) acknowledges many interesting discussions on coupled maps with Professor C. Tsallis. We are also grateful to the anonymous referees for their constructive feedback that helped us improve the manuscript and to the HPCS Laboratory of the TEI of Western Greece for providing the computer facilities where all our simulations were performed. C. G. A. was partially supported by the “EPSRC EP/I032606/1” grant of the University of Aberdeen. This research has been co-financed by the European Union (European Social Fund - ESF) and Greek national funds through the Operational Program “Education and Lifelong Learning” of the National Strategic Reference Framework (NSRF) - Research Funding Program: THALES - Investing in knowledge society through the European Social Fund.

Multilevel structural equation models for longitudinal data where predictors are measured more frequently than outcomes : an application to the effects of stress on the cognitive function of nurses

Funded by Chief Scientist Office, Scotland. Grant Number: CZH/4/394 Economic and Social Research Council grant as part of the National Centre for Research Methods. Grant Number: RES-576-25-0032

Models and empirical data for the production of referring expressions

Article Accepted Date: 29 May 2014 Acknowledgements The authors gratefully acknowledge the support of the Cognitive Science Society for the organisation of the Workshop on Production of Referring Expressions: Bridging the Gap between Cognitive and Computational Approaches to Reference, from which this special issue originated. Funding Emiel Krahmer and Albert Gatt thank The Netherlands Organisation for Scientific Research (NWO) for VICI grant Bridging the Gap between Computational Linguistics and Psycholinguistics: The Case of Referring Expressions (grant number 277-70-007).

Cash or non-cash: that is the question - the story of e-payment for social welfare in Ireland part 2

E-Government in its various forms and extensions, notably T-Government, is often presented as the panacea for resolving such complex social problems as social exclusion, lack of governance transparency, poor value for money and other ailments of modern societies. Yet, E-Government has not been adopted up to predicted levels. Many case studies investigating success factors, maturity models, and the application of acceptance models have been presented over the last 15 years, but a deep understanding of the potential impact and consequences of E-Government is still lacking. This is especially true for those initiatives that involve socio-economic and cultural contexts, which makes their evaluation and the prediction of their impact difficult. This paper reports on an on-going E-Government initiative in Ireland aimed at implementing E-payments for G2C, notably in the social welfare area. Three sets of personal surveys have been carried out to understand the perceived impact of governmental plans of moving from an almost fully cash-based payment system to a fully electronic based solution. Early results indicate that perceived pre-requisites for the planned change may be misleading. The impact on recipients’ lives cannot solely be measured in terms of economic gains: the consequences of such implementation may well reach further than expected.

Forces of agglomeration and dispersal in rural business networks: a social network analysis

Two concepts in rural economic development policy have been the focus of much research and policy action: the identification and support of clusters or networks of firms and the availability and adoption by rural businesses of Information and Communication Technologies (ICT). From a theoretical viewpoint these policies are based on two contrasting models, with clustering seen as a process of economic agglomeration, and ICT-mediated communication as a means of facilitating economic dispersion. The study’s conceptual framework is based on four interrelated elements: location, interaction, knowledge, and advantage, together with the concept of networks which is employed as an operationally and theoretically unifying concept. The research questions are developed in four successive categories: Policy, Theory, Networks, and Method. The questions are approached using a study of two contrasting groups of rural small businesses in West Cork, Ireland: (a) Speciality Foods, and (b) firms in Digital Products and Services. The study combines Social Network Analysis (SNA) with Qualitative Thematic Analysis, using data collected from semi-structured interviews with 58 owners or managers of these businesses. Data comprise relational network data on the firms’ connections to suppliers, customers, allies and competitors, together with linked qualitative data on how the firms established connections, and how tacit and codified knowledge was sourced and utilised. The research finds that the key characteristics identified in the cluster literature are evident in the sample of Speciality Food businesses, in relation to flows of tacit knowledge, social embedding, and the development of forms of social capital. In particular the research identified the presence of two distinct forms of collective social capital in this network, termed “community” and “reputation”. By contrast the sample of Digital Products and Services businesses does not have the form of a cluster, but matches more closely to dispersive models, or “chain” structures. Much of the economic and social structure of this set of firms is best explained in terms of “project organisation”, and by the operation of an individual rather than collective form of “reputation”. The rural setting in which these firms are located has resulted in their being service-centric, and consequently they rely on ICT-mediated communication in order to exchange tacit knowledge “at a distance”. It is this factor, rather than inputs of codified knowledge, that most strongly influences their operation and their need for availability and adoption of high quality communication technologies. Thus the findings have applicability in relation to theory in Economic Geography and to policy and practice in Rural Development. In addition the research contributes to methodological questions in SNA, and to methodological questions about the combination or mixing of quantitative and qualitative methods.

Dynamic Programming Approaches for Estimating and Applying Large-scale Discrete Choice Models

People go through their life making all kinds of decisions, and some of these decisions affect their demand for transportation, for example, their choices of where to live and where to work, how and when to travel and which route to take. Transport related choices are typically time dependent and characterized by large number of alternatives that can be spatially correlated. This thesis deals with models that can be used to analyze and predict discrete choices in large-scale networks. The proposed models and methods are highly relevant for, but not limited to, transport applications. We model decisions as sequences of choices within the dynamic discrete choice framework, also known as parametric Markov decision processes. Such models are known to be difficult to estimate and to apply to make predictions because dynamic programming problems need to be solved in order to compute choice probabilities. In this thesis we show that it is possible to explore the network structure and the flexibility of dynamic programming so that the dynamic discrete choice modeling approach is not only useful to model time dependent choices, but also makes it easier to model large-scale static choices. The thesis consists of seven articles containing a number of models and methods for estimating, applying and testing large-scale discrete choice models. In the following we group the contributions under three themes: route choice modeling, large-scale multivariate extreme value (MEV) model estimation and nonlinear optimization algorithms. Five articles are related to route choice modeling. We propose different dynamic discrete choice models that allow paths to be correlated based on the MEV and mixed logit models. The resulting route choice models become expensive to estimate and we deal with this challenge by proposing innovative methods that allow to reduce the estimation cost. For example, we propose a decomposition method that not only opens up for possibility of mixing, but also speeds up the estimation for simple logit models, which has implications also for traffic simulation. Moreover, we compare the utility maximization and regret minimization decision rules, and we propose a misspecification test for logit-based route choice models. The second theme is related to the estimation of static discrete choice models with large choice sets. We establish that a class of MEV models can be reformulated as dynamic discrete choice models on the networks of correlation structures. These dynamic models can then be estimated quickly using dynamic programming techniques and an efficient nonlinear optimization algorithm. Finally, the third theme focuses on structured quasi-Newton techniques for estimating discrete choice models by maximum likelihood. We examine and adapt switching methods that can be easily integrated into usual optimization algorithms (line search and trust region) to accelerate the estimation process. The proposed dynamic discrete choice models and estimation methods can be used in various discrete choice applications. In the area of big data analytics, models that can deal with large choice sets and sequential choices are important. Our research can therefore be of interest in various demand analysis applications (predictive analytics) or can be integrated with optimization models (prescriptive analytics). Furthermore, our studies indicate the potential of dynamic programming techniques in this context, even for static models, which opens up a variety of future research directions.

An overview of top-down vs. bottom-up models for informal settlement upgrading in South Africa

The paper explores informal settlement upgrading approaches in South Africa and presents a review of top-down vs. bottom-up models, using experience and lessons learned from the Durban metropolitan area. Reflections on past upgrading efforts suggest that top-down policies in South Africa have not been successful to date. By contrast, participatory techniques, such as planning activism, can be used to enhance community empowerment and a sense of local ownership. This paper reveals that although the notion of ‘bottom-up’, participatory methods for community improvement is often discussed in international development discourses, the tools, processes and new knowledge needed to ensure a successful upgrade are under-utilised. Participation and collaboration can mean various things for informal housing upgrading and often the involvement of local communities is limited to providing feedback in already agreed development decisions from local authorities and construction companies. The paper concludes by suggesting directions for ‘co-producing’ knowledge with communities through participatory, action-research methods and integrating these insights into upgrading mechanisms and policies for housing and infrastructure provision. The cumulative impacts emerging from these approaches could aggregate into local, regional, and national environmental, social and economic benefits able to successfully transform urban areas and ensure self-reliance for local populations.