Innovating from the War Economy: Formal, Informal, and Illicit Economic Activities of the Military in Colombia

Over the last decade, the Colombian military has successfully rolled back insurgent groups, cleared and secured conflict zones, and enabled the extraction of oil and other key commodity exports. As a result, official policies of both the Uribe and Santos governments have promoted the armed forces to participate to an unprecedented extent in economic activities intended to consolidate the gains of the 2000s. These include formal involvement in the economy, streamlined in a consortium of military enterprises and social foundations that are intended to put the Colombian defense sector “on the map” nationally and internationally, and informal involvement expanded mainly through new civic action development projects intended to consolidate the security gains of the 2000s. However, failure to roll back paramilitary groups other than through the voluntary amnesty program of 2005 has facilitated the persistence of illicit collusion by military forces with reconstituted “neoparamilitary” drug trafficking groups. It is therefore crucially important to enhance oversight mechanisms and create substantial penalties for collusion with illegal armed groups. This is particularly important if Colombia intends to continue its new practice of exporting its security model to other countries in the region. The Santos government has initiated several promising reforms to enhance state capacity, institutional transparence, and accountability of public officials to the rule of law, which are crucial to locking in security gains and revitalizing democratic politics. Efforts to diminish opportunities for illicit association between the armed forces and criminal groups should complement that agenda, including the following: Champion breaking existing ties between the military and paramilitary successor groups through creative policies involving a mixture of punishments and rewards directed at the military; Investigation and extradition proceedings of drug traffickers, probe all possible ties, including as a matter of course the possibility of Colombian military collaboration. Doing so rigorously may have an important effect deterring military collusion with criminal groups. Establish and enforce zero-tolerance policies at all military ranks regarding collusion with criminal groups; Reward military units that are effective and also avoid corruption and criminal ties by providing them with enhanced resources and recognition; Rely on the military for civic action and development assistance as minimally as possible in order to build long-term civilian public sector capacity and to reduce opportunities for routine exposure of military forces to criminal groups circulating in local populations.

Increasing Informal Learning Opportunities for Teachers in the School Setting

This paper comprehensively defines how to implement informal learning strategies into the classroom setting using Marsick and Watkins’s Incidental Learning Model (2001). Existing barriers that stand between educators and informal learning in the school setting are explained. Implications for removing said inhibitors while increasing learning are explicated.

Predictors of Independent Living Outcomes Among Older Women Receiving Informal Care

This study examined the predictors of independent living outcomes among community–living older women who received informal care. The central hypothesis was that older women’s level of functioning is influenced by their relationship with their informal caregiver. The study attempted to understand the independence of older women through the perspective of both informal caregivers and the older women themselves. The following eight variables were measured: 1) the older women’s independence (dependent variable); 2) the relationship between older women and their informal caregivers (independent variable); 3) roles of both the informal caregiver and older women (independent variable); 4) the older women’s attitudes toward aging (independent variable); 5) the older women’s age identity (independent variable); 6) the older women’s health (control variable); 7) the older women’s level of social support (control variable); and 8) the older women’s level of depression (control variable). The variables were measured from the perspective of the older woman herself and her informal caregiver. This study used an ecological and developmental framework along with role theory to understand the interaction among the aforementioned variables through a cross-sectional design. The recruited older women participants of this study were receiving ongoing care and personal assistance from two large home care agencies located in Miami, FL. An analysis was conducted through a mixed-methods incorporated into the study design. The present study aimed to contribute to the understanding of how the relationship between older women and their informal caregivers influences older women’s ability to maintain independent outcomes. The primary finding of this study was that there were both positive and negative experiences within the relationship dynamic of older women and their informal caregivers and that this relationship was either unidirectional or bi-directional.

Mobilização de competências na atividade informal do vendedor ambulante em praia de Natal (RN)

The central issue of this dissertation is to investigate the labor activity of beach hawker, in order to identify the main professional competencies mobilized in this activity, traversed by both the precariousness of the means of labor exercise, as for complex and structured routines. In the town of Natal (RN) the beaches serve as workplace for thousands of informal workers, who use various professional skills, translated into the ability to mobilize and articulate knowledge, skills and behaviors to solve problems in concrete work situations. This research therefore had as main objective to investigate the work of beach hawkers, trying to identify the core competencies mobilized for facing demands and obstacles in such a context. The beach of Ponta Negra (Natal-RN) was chosen as field of observation, in which a group of hawkers took part as voluntary subjects. Methodologically, quantitative and qualitative methods of production and analysis of data were combined in three stages. In the quantitative phase an occupational questionnaire was applied to a sample of 60 subjects, generating a set of data analyzed with quantitative univariate and multidimensional descriptive statistical tools, complemented by inferential statistical analysis. The results of this phase indicate a predominance of men sellers with salary varying in a range from one to two minimum wage Brazilian salary, age and education quite heterogeneous, extended working hours and the choice of only this activity and this beach throughout the year. Concurrently with this step of analysis, unsystematic observations of the activity of vendors were held and then driven to the technique of Instruction Impersonator with four chosen subjects. This phase had a clinicalinterpretive analysis, rooted in historical-cultural Vygotskian psychological perspective and in the french approach of skills and abilities. The main results point to several strategies for overcoming obstacles, use of technics anchored in everyday work experience and practical knowledge, building rules of conduct and collective mobilization of diverse professional skills similar to those found in formal work, such as business and time management, use of communicative tools, flexibility in problem solving, creativity and teamwork competence. We conclude that informality investigated in context can not be seen exclusively as a synonym of precariousness. It also covers skills and knowledge in a complex culture that situates informal labor in a complementary way with respect to formal work. This conclusion, therefore, contributes to overcome the notion of antinomy between formal and informal labor activity, since they both can be considered as a way to achieve job satisfaction, and even a personal representation of well done job, which is an important psychological generator of identity and social place.

El papel de la coacción informal en el tratamiento ambulatorio: un estudio transcultural con profesionales de la salud mental

Entendemos por coerción como la presión ejercida sobre alguien para forzar su voluntad o su conducta. El concepto de coerción transciende la Salud Mental y afecta a distintas disciplinas como la filosofía, ética, derecho o política. Dentro de las medidas coercitivas que se usan en el campo de la Salud Mental distinguimos entre aquellas que se ejercen dentro de un marco normativo, a las que nos referimos como medidas formales de coerción (hospitalización involuntaria, aislamiento, contención mecánica y química) y otras, objeto de este estudio, denominadas informales o encubiertas, que son aquellas estrategias coercitivas utilizadas como forma de presión sobre el paciente, principalmente ambulatorio, y que se escapan a cualquier normativa o jurisprudencia. Szmukler y Appelbaum definen cuatro niveles diferentes de coerción informal: persuasión, influencia interpersonal, inducción y amenaza. Aunque existe bastante investigación sobre coerción formal en los últimos treinta años, no es así en el caso de la coerción informal, si bien se ha intensificado en la última década. Es más, apenas existen estudios que recojan las opiniones de los profesionales sobre la misma y los que existen se concentran países desarrollados, ignorando aspectos socioculturales, de tradición psiquiátrica y organización asistencial que pueden influir en el uso de este tipo de estrategias...

The Bennachie Colony : A Nineteenth-Century Informal Community in Northeast Scotland

Acknowledgments The investigation of the Bennachie Colony is part of a broader initiative called the Bennachie Landscape Project, a collaborative endeavour between the Bailies of Bennachie and the University of Aberdeen. To date, funding for the project has been generously provided by the Arts and Humanities Research Council (AHRC) in the form of a Connected Communities Grant (G. Noble PI) and more recently through a larger Development Grant (J. Oliver PI). The research that this paper is based on could not have been undertaken without the generous assistance of a large number of volunteers, university students and staff members. While it would be impossible to name everyone who has contributed, we would like to acknowledge the regular members of the “landscape group” whose infective enthusiasm for the project has provided a stimulating environment for learning and co-production. Particular thanks go to Jackie Cumberbirch, Barry Foster, Chris Foster, Angela Groat, David Irving, Alison Kennedy, Harry Leal, Ken Ledingham, Colin Miller, Iain Ralston, Colin Shepherd, Sue Taylor and Andrew Wainwright. Further assistance with fieldwork was provided by Ágústa Edwald, Patrycia Kupiec, Barbora Wouters, Óskar Sveinbjarnarson, members of Northlight Heritage and several cohorts worth of University of Aberdeen undergraduate and graduate students. We are indebted to the RCAHMS for assistance with plane table survey and to Óskar Sveinbjarnarson for help with mapping. Others have supported additional aspects of the Bennachie Landscape project or have provided specialist advice. Thanks go to Neil Curtis, Liz Curtis, Rowan Ellis, Marjory Harper, Siobhan Convery and the University of Aberdeen Special Collections staff. Access to undertake fieldwork was graciously provided by the Forestry Commission Scotland. Helpful comments on earlier drafts of this paper were provided by Barry and Chris Foster, Ken Ledingham, Collin Miller, Collin Shepherd, Sue Taylor, Andrew Wainwright and two anonymous reviewers.

The Bennachie Colony : A Nineteenth-Century Informal Community in Northeast Scotland

Acknowledgments The investigation of the Bennachie Colony is part of a broader initiative called the Bennachie Landscape Project, a collaborative endeavour between the Bailies of Bennachie and the University of Aberdeen. To date, funding for the project has been generously provided by the Arts and Humanities Research Council (AHRC) in the form of a Connected Communities Grant (G. Noble PI) and more recently through a larger Development Grant (J. Oliver PI). The research that this paper is based on could not have been undertaken without the generous assistance of a large number of volunteers, university students and staff members. While it would be impossible to name everyone who has contributed, we would like to acknowledge the regular members of the “landscape group” whose infective enthusiasm for the project has provided a stimulating environment for learning and co-production. Particular thanks go to Jackie Cumberbirch, Barry Foster, Chris Foster, Angela Groat, David Irving, Alison Kennedy, Harry Leal, Ken Ledingham, Colin Miller, Iain Ralston, Colin Shepherd, Sue Taylor and Andrew Wainwright. Further assistance with fieldwork was provided by Ágústa Edwald, Patrycia Kupiec, Barbora Wouters, Óskar Sveinbjarnarson, members of Northlight Heritage and several cohorts worth of University of Aberdeen undergraduate and graduate students. We are indebted to the RCAHMS for assistance with plane table survey and to Óskar Sveinbjarnarson for help with mapping. Others have supported additional aspects of the Bennachie Landscape project or have provided specialist advice. Thanks go to Neil Curtis, Liz Curtis, Rowan Ellis, Marjory Harper, Siobhan Convery and the University of Aberdeen Special Collections staff. Access to undertake fieldwork was graciously provided by the Forestry Commission Scotland. Helpful comments on earlier drafts of this paper were provided by Barry and Chris Foster, Ken Ledingham, Collin Miller, Collin Shepherd, Sue Taylor, Andrew Wainwright and two anonymous reviewers.

Informal Qualitative Models: A Systematic Approach to their Generation

Postprint

Strong inference from transect sign surveys : combining spatial autocorrelation and misclassification occupancy models to quantify the detectability of a recovering carnivore

Funding — Forest Enterprise Scotland and the University of Aberdeen provided funding for the project. The Carnegie Trust supported the lead author, E. McHenry, in this research through the award of a tuition fees bursary.

The contradictions and complementarities of combining ERP systems with enterprise 2.0 supported informal systems

The chapter discusses both the complementary factors and contradictions of adopting ERP based systems with enterprise 2.0. ERP is characterized as achieving efficient business performance by enabling a standardized business process design, but at a cost of flexibility in operations. It is claimed that enterprise 2.0 can support flexible business process management and so incorporate informal and less structured interactions. A traditional view however is that efficiency and flexibility objectives are incompatible as they are different business objectives which are pursued separately in different organizational environments. Thus an ERP system with a primary objective of improving efficiency and an enterprise 2.0 system with a primary aim of improving flexibility may represent a contradiction and lead to a high risk of failure if adopted simultaneously. This chapter will use case study analysis to investigate the use of a combination of ERP and enterprise 2.0 in a single enterprise with the aim of improving both efficiency and flexibility in operations. The chapter provides an in-depth analysis of the combination of ERP with enterprise 2.0 based on social-technical information systems management theory. The chapter also provides a summary of the benefits of the combination of ERP systems and enterprise 2.0 and how they could contribute to the development of a new generation of business management that combines both formal and informal mechanisms. For example, the multiple-sites or informal communities of an enterprise could collaborate efficiently with a common platform with a certain level of standardization but also have the flexibility in order to provide an agile reaction to internal and external events.

Bayesian Inference in Large-scale Problems

Many modern applications fall into the category of "large-scale" statistical problems, in which both the number of observations n and the number of features or parameters p may be large. Many existing methods focus on point estimation, despite the continued relevance of uncertainty quantification in the sciences, where the number of parameters to estimate often exceeds the sample size, despite huge increases in the value of n typically seen in many fields. Thus, the tendency in some areas of industry to dispense with traditional statistical analysis on the basis that "n=all" is of little relevance outside of certain narrow applications. The main result of the Big Data revolution in most fields has instead been to make computation much harder without reducing the importance of uncertainty quantification. Bayesian methods excel at uncertainty quantification, but often scale poorly relative to alternatives. This conflict between the statistical advantages of Bayesian procedures and their substantial computational disadvantages is perhaps the greatest challenge facing modern Bayesian statistics, and is the primary motivation for the work presented here.

Two general strategies for scaling Bayesian inference are considered. The first is the development of methods that lend themselves to faster computation, and the second is design and characterization of computational algorithms that scale better in n or p. In the first instance, the focus is on joint inference outside of the standard problem of multivariate continuous data that has been a major focus of previous theoretical work in this area. In the second area, we pursue strategies for improving the speed of Markov chain Monte Carlo algorithms, and characterizing their performance in large-scale settings. Throughout, the focus is on rigorous theoretical evaluation combined with empirical demonstrations of performance and concordance with the theory.

One topic we consider is modeling the joint distribution of multivariate categorical data, often summarized in a contingency table. Contingency table analysis routinely relies on log-linear models, with latent structure analysis providing a common alternative. Latent structure models lead to a reduced rank tensor factorization of the probability mass function for multivariate categorical data, while log-linear models achieve dimensionality reduction through sparsity. Little is known about the relationship between these notions of dimensionality reduction in the two paradigms. In Chapter 2, we derive several results relating the support of a log-linear model to nonnegative ranks of the associated probability tensor. Motivated by these findings, we propose a new collapsed Tucker class of tensor decompositions, which bridge existing PARAFAC and Tucker decompositions, providing a more flexible framework for parsimoniously characterizing multivariate categorical data. Taking a Bayesian approach to inference, we illustrate empirical advantages of the new decompositions.

Latent class models for the joint distribution of multivariate categorical, such as the PARAFAC decomposition, data play an important role in the analysis of population structure. In this context, the number of latent classes is interpreted as the number of genetically distinct subpopulations of an organism, an important factor in the analysis of evolutionary processes and conservation status. Existing methods focus on point estimates of the number of subpopulations, and lack robust uncertainty quantification. Moreover, whether the number of latent classes in these models is even an identified parameter is an open question. In Chapter 3, we show that when the model is properly specified, the correct number of subpopulations can be recovered almost surely. We then propose an alternative method for estimating the number of latent subpopulations that provides good quantification of uncertainty, and provide a simple procedure for verifying that the proposed method is consistent for the number of subpopulations. The performance of the model in estimating the number of subpopulations and other common population structure inference problems is assessed in simulations and a real data application.

In contingency table analysis, sparse data is frequently encountered for even modest numbers of variables, resulting in non-existence of maximum likelihood estimates. A common solution is to obtain regularized estimates of the parameters of a log-linear model. Bayesian methods provide a coherent approach to regularization, but are often computationally intensive. Conjugate priors ease computational demands, but the conjugate Diaconis--Ylvisaker priors for the parameters of log-linear models do not give rise to closed form credible regions, complicating posterior inference. In Chapter 4 we derive the optimal Gaussian approximation to the posterior for log-linear models with Diaconis--Ylvisaker priors, and provide convergence rate and finite-sample bounds for the Kullback-Leibler divergence between the exact posterior and the optimal Gaussian approximation. We demonstrate empirically in simulations and a real data application that the approximation is highly accurate, even in relatively small samples. The proposed approximation provides a computationally scalable and principled approach to regularized estimation and approximate Bayesian inference for log-linear models.

Another challenging and somewhat non-standard joint modeling problem is inference on tail dependence in stochastic processes. In applications where extreme dependence is of interest, data are almost always time-indexed. Existing methods for inference and modeling in this setting often cluster extreme events or choose window sizes with the goal of preserving temporal information. In Chapter 5, we propose an alternative paradigm for inference on tail dependence in stochastic processes with arbitrary temporal dependence structure in the extremes, based on the idea that the information on strength of tail dependence and the temporal structure in this dependence are both encoded in waiting times between exceedances of high thresholds. We construct a class of time-indexed stochastic processes with tail dependence obtained by endowing the support points in de Haan's spectral representation of max-stable processes with velocities and lifetimes. We extend Smith's model to these max-stable velocity processes and obtain the distribution of waiting times between extreme events at multiple locations. Motivated by this result, a new definition of tail dependence is proposed that is a function of the distribution of waiting times between threshold exceedances, and an inferential framework is constructed for estimating the strength of extremal dependence and quantifying uncertainty in this paradigm. The method is applied to climatological, financial, and electrophysiology data.

The remainder of this thesis focuses on posterior computation by Markov chain Monte Carlo. The Markov Chain Monte Carlo method is the dominant paradigm for posterior computation in Bayesian analysis. It has long been common to control computation time by making approximations to the Markov transition kernel. Comparatively little attention has been paid to convergence and estimation error in these approximating Markov Chains. In Chapter 6, we propose a framework for assessing when to use approximations in MCMC algorithms, and how much error in the transition kernel should be tolerated to obtain optimal estimation performance with respect to a specified loss function and computational budget. The results require only ergodicity of the exact kernel and control of the kernel approximation accuracy. The theoretical framework is applied to approximations based on random subsets of data, low-rank approximations of Gaussian processes, and a novel approximating Markov chain for discrete mixture models.

Data augmentation Gibbs samplers are arguably the most popular class of algorithm for approximately sampling from the posterior distribution for the parameters of generalized linear models. The truncated Normal and Polya-Gamma data augmentation samplers are standard examples for probit and logit links, respectively. Motivated by an important problem in quantitative advertising, in Chapter 7 we consider the application of these algorithms to modeling rare events. We show that when the sample size is large but the observed number of successes is small, these data augmentation samplers mix very slowly, with a spectral gap that converges to zero at a rate at least proportional to the reciprocal of the square root of the sample size up to a log factor. In simulation studies, moderate sample sizes result in high autocorrelations and small effective sample sizes. Similar empirical results are observed for related data augmentation samplers for multinomial logit and probit models. When applied to a real quantitative advertising dataset, the data augmentation samplers mix very poorly. Conversely, Hamiltonian Monte Carlo and a type of independence chain Metropolis algorithm show good mixing on the same dataset.

Bayesian Emulation for Sequential Modeling, Inference and Decision Analysis

The advances in three related areas of state-space modeling, sequential Bayesian learning, and decision analysis are addressed, with the statistical challenges of scalability and associated dynamic sparsity. The key theme that ties the three areas is Bayesian model emulation: solving challenging analysis/computational problems using creative model emulators. This idea defines theoretical and applied advances in non-linear, non-Gaussian state-space modeling, dynamic sparsity, decision analysis and statistical computation, across linked contexts of multivariate time series and dynamic networks studies. Examples and applications in financial time series and portfolio analysis, macroeconomics and internet studies from computational advertising demonstrate the utility of the core methodological innovations.

Chapter 1 summarizes the three areas/problems and the key idea of emulating in those areas. Chapter 2 discusses the sequential analysis of latent threshold models with use of emulating models that allows for analytical filtering to enhance the efficiency of posterior sampling. Chapter 3 examines the emulator model in decision analysis, or the synthetic model, that is equivalent to the loss function in the original minimization problem, and shows its performance in the context of sequential portfolio optimization. Chapter 4 describes the method for modeling the steaming data of counts observed on a large network that relies on emulating the whole, dependent network model by independent, conjugate sub-models customized to each set of flow. Chapter 5 reviews those advances and makes the concluding remarks.

Santeria as an Informal Psychosocial Support Among Latinas Living with Cancer

Among Latinos, Santería functions as both a religion and a health care system in occurrences of health versus illness within various Latino sub-groups in the U.S. This exploratory study offers a comprehensive analysis of the function of the folk healing tradition Santería as a culturally congruent informal mental health support that assists with coping with the psychosocial sequelae of living with cancer among Latinas in Miami-Dade County, FL. It (a) determined the attitudes of Latinas living with cancer towards Santería as an informal mental health support and (b) explored how Santería offers Latinas effective mental health support that assists in coping with the psychosocial sequelae of living with cancer. The mechanisms and characteristics underlying the motivations of Latinas living with cancer to seek and integrate this informal modality for their cancer care were identified. A purposive sample of 15 Latinas ages 18 and older in Miami-Dade County who had received a diagnosis of cancer were recruited from sites in Miami-Dade offering formal mental health support services and botánicas. Data collection incorporated in-depth interviews and a validation focus group. In an effort to generate theory through a modified Grounded Theory approach, data analysis was accomplished by means of multiple coding passes and the constant comparison method which resulted in higher levels codes that were grouped into three major themes: 1) Participants’ Experience with Folk Healers, 2) Influence of Santería on the Cancer Experience, and 3) Participants’ Experience with Conventional Healthcare and Mental Healthcare. Results illustrate how, among Latinas, the folk healing tradition of Santería co-occurs with professional medical and mental health treatment in what Arthur Kleinman defines as the popular sector, which identifies and sets the parameters for culturally acceptable forms of healthcare and mental health treatment options.