Women-led Community Development Organizations (CDOs) in Miami-Dade County: A Model of Community Development Efforts Impacting the Economic Security of Women

Recent studies on the economic status of women in Miami-Dade County (MDC) reveal an alarming rate of economic insecurity and significant obstacles for women to achieve economic security. Consistent barriers to women’s economic security affect not only the health and wellbeing of women and their families, but also economic prospects for the community. A key study reveals in Miami-Dade County, “Thirty-nine percent of single female-headed families with at least one child are living at or below the federal poverty level” and “over half of working women do not earn adequate income to cover their basic necessities” (Brion 2009, 1). Moreover, conventional measures of poverty do not adequately capture women’s struggles to support themselves and their families, nor do they document the numbers of women seeking basic self-sufficiency. Even though there is lack of accurate data on women in the county, which is a critical problem, there is also a dearth of social science research on existing efforts to enhance women’s economic security in Miami-Dade County. My research contributes to closing the information gap by examining the characteristics and strategies of women-led community development organizations (CDOs) in MDC, working to address women’s economic insecurity. The research is informed by a framework developed by Marilyn Gittell, who pioneered an approach to study women-led CDOs in the United States. On the basis of research in nine U.S. cities, she concluded that women-led groups increased community participation and “by creating community networks and civic action, they represent a model for community development efforts” (Gittell, et al. 2000, 123). My study documents the strategies and networks of women-led CDOs in MDC that prioritize women’s economic security. Their strategies are especially important during these times of economic recession and government reductions in funding towards social services. The focus of the research is women-led CDOs that work to improve social services access, economic opportunity, civic participation and capacity, and women’s rights. Although many women-led CDOs prioritize building social infrastructures that promote change, inequalities in economic and political status for women without economic security remain a challenge (Young 2004). My research supports previous studies by Gittell, et al., finding that women-led CDOs in Miami-Dade County have key characteristics of a model of community development efforts that use networking and collaboration to strengthen their broad, integrated approach. The resulting community partnerships, coupled with participation by constituents in the development process, build a foundation to influence policy decisions for social change. In addition, my findings show that women-led CDOs in Miami-Dade County have a major focus on alleviating poverty and economic insecurity, particularly that of women. Finally, it was found that a majority of the five organizations network transnationally, using lessons learned to inform their work of expanding the agency of their constituents and placing the economic empowerment of women as central in the process of family and community development.

Essays in Economic Geography and Long-Term Development

This dissertation has two main themes: first, the economic impact of tourism on cities and, secondly, the determinants of European long-run development, with a focus on the pre-Industrial era. The common thread is the attempt to develop economic geography models that incorporate spatial frictions and are liable to be given empirical content. Chapter 1, written in conjunction with G. Alfredo Minerva, provides an empirical analysis of the relationship between tourism and economic activity across Italian municipalities, and lays down the basic elements of an urban theory of tourism in an a-spatial setting. Chapter 2 extends these ideas to a quantitative urban framework to study the economic impact and the welfare consequences of tourism into the city of Venice. The model is given empirical content thanks to a large collection of data at the Census tract level for the Municipality of Venice, and then used to perform counterfactual policty analysis. In chapter 3, with Matteo Santacesaria, we consider a setting where agents are continuously distributed over a two-dimensional heterogeneous geography, and are allowed to do business at a finite set of markets. We study the equilibrium partition of the economic space into a collection of mutually-exclusive market areas, and provide condition for this equilibrium partition to exist and to be unique. Finally, chapter 4 "The rise of (urban) Europe: a Quantitative-Spatial analysis", co-authored with Matteo Cervellati and Alex Lehner, sets up a quantitative economic geography model to understand the roots of the Industrial Revolution, in an attempt to match the evolution of the European urban network, and the corresponding city-size distribution, over the period A.D. 1000-1850. It highlights the importance of agricultural trade across cities for the emergence of large manufacturing hubs.

Greening the city: an ecosystem-based framework to support planning towards urban sustainability and resilience

Cities are small-scale complex socio-ecological systems, that host around 60% of world population. Ecosystem Services (ES) provided by urban ecosystems offer multiple benefits necessary to cope with present and future urban challenges. These ES include microclimate regulation, runoff control, as well as opportunities for mental and physical recreation, affecting citizen’s health and wellbeing. Creating a balance between urban development, land take containment, climate adaptation and availability of Urban Green Areas and their related benefits, can improve the quality of the lives of the inhabitants, the economic performance of the city and the social justice and cohesion aspects. This work starts analysing current literature around the topic of Ecosystem Services (ES), Green and Blue Infrastructure (GBI) and Nature-based Solutions (NBS) and their integration within current European and International sustainability policies. Then, the thesis focuses on the role of ES, GBI and NBS towards urban sustainability and resilience setting the basis to build the core methodological and conceptual approach of this work. The developed ES-based conceptual approach provides guidance on how to map and assess ES, to better inform policy making and to give the proper value to ES within urban context. The proposed interdisciplinary approach navigates the topic of mapping and assessing ES benefits in terms of regulatory services, with a focus on climate mitigation and adaptation, and cultural services, to enhance wellbeing and justice in urban areas. Last, this thesis proposes a trans-disciplinary and participatory approach to build resilience over time around all relevant urban ES. The two case studies that will be presented in this dissertation, the city of Bologna and the city of Barcelona, have been used to implement, tailor and test the proposed conceptual framework, raising valuable inputs for planning, policies and science.

Distributed non-cooperative robust economic predictive control for dynamically coupled linear systems.

In this thesis, a tube-based Distributed Economic Predictive Control (DEPC) scheme is presented for a group of dynamically coupled linear subsystems. These subsystems are components of a large scale system and control inputs are computed based on optimizing a local economic objective. Each subsystem is interacting with its neighbors by sending its future reference trajectory, at each sampling time. It solves a local optimization problem in parallel, based on the received future reference trajectories of the other subsystems. To ensure recursive feasibility and a performance bound, each subsystem is constrained to not deviate too much from its communicated reference trajectory. This difference between the plan trajectory and the communicated one is interpreted as a disturbance on the local level. Then, to ensure the satisfaction of both state and input constraints, they are tightened by considering explicitly the effect of these local disturbances. The proposed approach averages over all possible disturbances, handles tightened state and input constraints, while satisfies the compatibility constraints to guarantee that the actual trajectory lies within a certain bound in the neighborhood of the reference one. Each subsystem is optimizing a local arbitrary economic objective function in parallel while considering a local terminal constraint to guarantee recursive feasibility. In this framework, economic performance guarantees for a tube-based distributed predictive control (DPC) scheme are developed rigorously. It is presented that the closed-loop nominal subsystem has a robust average performance bound locally which is no worse than that of a local robust steady state. Since a robust algorithm is applying on the states of the real (with disturbances) subsystems, this bound can be interpreted as an average performance result for the real closed-loop system. To this end, we present our outcomes on local and global performance, illustrated by a numerical example.

Understanding, defining and assessing food systems’ social and economic sustainability indicators: implementation of mixed methodologies for policy insights

Sustainability encompasses the presence of three dimensions that must coexist simultaneously, namely the environmental, social, and economic ones. The economic and social dimensions are gaining the spotlight in recent years, especially within food systems. To assess social and economic impacts, indicators and tools play a fundamental role in contributing to the achievements of sustainability targets, although few of them have deepen the focus on social and economic impacts. Moreover, in a framework of citizen science and bottom-up approach for improving food systems, citizen play a key role in defying their priorities in terms of social and economic interventions. This research expands the knowledge of social and economic sustainability indicators within the food systems for robust policy insights and interventions. This work accomplishes the following objectives: 1) to define social and economic indicators within the supply chain with a stakeholder perspective, 2) to test social and economic sustainability indicators for future food systems engaging young generations. The first objective was accomplished through the development of a systematic literature review of 34 social sustainability tools, based on five food supply chain stages, namely production, processing, wholesale, retail, and consumer considering farmers, workers, consumers, and society as stakeholders. The second objective was achieved by defining and testing new food systems social and economic sustainability indicators through youth engagement for informed and robust policy insights, to provide policymakers suggestions that would incorporate young generations ones. Future food systems scenarios were evaluated by youth through focus groups, whose results were analyzed through NVivo and then through a survey with a wider platform. Conclusion addressed the main areas of policy interventions in terms of social and economic aspects of sustainable food systems youth pointed out as in need of interventions, spanning from food labelling reporting sustainable origins to better access to online food services.

The Financial Services Regime in International Economic Law: on the Difficult Relationship between Trade Liberalization and Prudential Measures

The PhD thesis analyses the financial services regime in international economic law from the perspective of the difficult relationship between trade liberalisation and prudential measures. Financial stability plays a fundamental role for the well-being and well-functioning of the global economy, but, it is at the same time a complex sector to regulate and supervise and, especially after the 2007-08 economic crisis, States have tightened up their regulation of financial services, introducing more severe and protectionist prudential measures. However, in an increasingly interconnected global economy, the harmonization of prudential regulation at the international level is an essential step to guarantee integrity, fairness and stability of financial markets and trade. The research analyses the tools at disposition to achieve this aim, the related problematic issues and the perspectives and possible solutions for the future, starting from the World Trade Organization (WTO) legal framework and its General Agreement on Trade in Services (GATS), devoted to discipline trade in services among the WTO Members. Then, the research moves to a second legal instrument, the Free Trade Agreements (FTAs), which has witnessed a remarkable spread in the last decades. Finally, the research addresses the international standards, developed by supranational entities and implemented by an increasing number of States, as they offer rules and guidelines adequate to update the international financial scenario. Nevertheless, the international standards alone cannot be the solution because, first, they are not mandatory, as governments decide voluntarily to apply them and, second, their decision-making process do not respect the requirements of transparency and representative membership. In light of this analysis, the thesis aims at providing an answer to its research question: how to give more certainty to States and economic operators in the planning of the domestic disciplines and business activities in order to provide a sound and stable international financial system.

Multi-Principal Agency and the Compliance with Professional Guidelines in Health Systems: Economic and Regulatory Perspectives

Amid the trend of rising health expenditure in developed economies, changing the healthcare delivery models is an important point of action for service regulators to contain this trend. Such a change is mostly induced by either financial incentives or regulatory tools issued by the regulators and targeting service providers and patients. This creates a tripartite interaction between service regulators, professionals, and patients that manifests a multi-principal agent relationship, in which professionals are agents to two principals: regulators and patients. This thesis is concerned with such a multi-principal agent relationship in healthcare and attempts to investigate the determinants of the (non-)compliance to regulatory tools in light of this tripartite relationship. In addition, the thesis provides insights into the different institutional, economic, and regulatory settings, which govern the multi-principal agent relationship in healthcare in different countries. Furthermore, the thesis provides and empirically tests a conceptual framework of the possible determinants of (non-)compliance by physicians to regulatory tools issued by the regulator. The main findings of the thesis are first, in a multi-principal agent setting, the utilization of financial incentives to align the objectives of professionals and the regulator is important but not the only solution. This finding is based on the heterogeneity in the financial incentives provided to professionals in different health markets, which does not provide a one-size-fits-all model of financial incentives to influence clinical decisions. Second, soft law tools as clinical practice guidelines (CPGs) are important tools to mitigate the problems of the multi-principal agent setting in health markets as they reduce information asymmetries while preserving the autonomy of professionals. Third, CPGs are complex and heterogeneous and so are the determinants of (non-)compliance to them. Fourth, CPGs work but under conditions. Factors such as intra-professional competition between service providers or practitioners might lead to non-compliance to CPGs – if CPGs are likely to reduce the professional’s utility. Finally, different degrees of soft law mandate have different effects on providers’ compliance. Generally, the stronger the mandate, the stronger the compliance, however, even with a strong mandate, drivers such as intra-professional competition and co-management of patients by different professionals affected the (non-)compliance.

Regularization meets GreenAI: a new framework for image reconstruction in life sciences applications

Ill-conditioned inverse problems frequently arise in life sciences, particularly in the context of image deblurring and medical image reconstruction. These problems have been addressed through iterative variational algorithms, which regularize the reconstruction by adding prior knowledge about the problem's solution. Despite the theoretical reliability of these methods, their practical utility is constrained by the time required to converge. Recently, the advent of neural networks allowed the development of reconstruction algorithms that can compute highly accurate solutions with minimal time demands. Regrettably, it is well-known that neural networks are sensitive to unexpected noise, and the quality of their reconstructions quickly deteriorates when the input is slightly perturbed. Modern efforts to address this challenge have led to the creation of massive neural network architectures, but this approach is unsustainable from both ecological and economic standpoints. The recently introduced GreenAI paradigm argues that developing sustainable neural network models is essential for practical applications. In this thesis, we aim to bridge the gap between theory and practice by introducing a novel framework that combines the reliability of model-based iterative algorithms with the speed and accuracy of end-to-end neural networks. Additionally, we demonstrate that our framework yields results comparable to state-of-the-art methods while using relatively small, sustainable models. In the first part of this thesis, we discuss the proposed framework from a theoretical perspective. We provide an extension of classical regularization theory, applicable in scenarios where neural networks are employed to solve inverse problems, and we show there exists a trade-off between accuracy and stability. Furthermore, we demonstrate the effectiveness of our methods in common life science-related scenarios. In the second part of the thesis, we initiate an exploration extending the proposed method into the probabilistic domain. We analyze some properties of deep generative models, revealing their potential applicability in addressing ill-posed inverse problems.

An Integrated Framework To Improve The Concept Of Resource Specialisation.

Resource specialisation, although a fundamental component of ecological theory, is employed in disparate ways. Most definitions derive from simple counts of resource species. We build on recent advances in ecophylogenetics and null model analysis to propose a concept of specialisation that comprises affinities among resources as well as their co-occurrence with consumers. In the distance-based specialisation index (DSI), specialisation is measured as relatedness (phylogenetic or otherwise) of resources, scaled by the null expectation of random use of locally available resources. Thus, specialists use significantly clustered sets of resources, whereas generalists use over-dispersed resources. Intermediate species are classed as indiscriminate consumers. The effectiveness of this approach was assessed with differentially restricted null models, applied to a data set of 168 herbivorous insect species and their hosts. Incorporation of plant relatedness and relative abundance greatly improved specialisation measures compared to taxon counts or simpler null models, which overestimate the fraction of specialists, a problem compounded by insufficient sampling effort. This framework disambiguates the concept of specialisation with an explicit measure applicable to any mode of affinity among resource classes, and is also linked to ecological and evolutionary processes. This will enable a more rigorous deployment of ecological specialisation in empirical and theoretical studies.

Survival Extrapolation In The Presence Of Cause Specific Hazards.

Health economic evaluations require estimates of expected survival from patients receiving different interventions, often over a lifetime. However, data on the patients of interest are typically only available for a much shorter follow-up time, from randomised trials or cohorts. Previous work showed how to use general population mortality to improve extrapolations of the short-term data, assuming a constant additive or multiplicative effect on the hazards for all-cause mortality for study patients relative to the general population. A more plausible assumption may be a constant effect on the hazard for the specific cause of death targeted by the treatments. To address this problem, we use independent parametric survival models for cause-specific mortality among the general population. Because causes of death are unobserved for the patients of interest, a polyhazard model is used to express their all-cause mortality as a sum of latent cause-specific hazards. Assuming proportional cause-specific hazards between the general and study populations then allows us to extrapolate mortality of the patients of interest to the long term. A Bayesian framework is used to jointly model all sources of data. By simulation, we show that ignoring cause-specific hazards leads to biased estimates of mean survival when the proportion of deaths due to the cause of interest changes through time. The methods are applied to an evaluation of implantable cardioverter defibrillators for the prevention of sudden cardiac death among patients with cardiac arrhythmia. After accounting for cause-specific mortality, substantial differences are seen in estimates of life years gained from implantable cardioverter defibrillators.

Innovation and entrepreneurship in scientific research

This research wants to lay emphasis on topics that historicize and rescue concepts, in addition, shows the relation between innovation and socioeconomic development resulted; reviews the legal framework to stimulate new innovation into Brazilian society; considers the definition and the entrepreneur university's new paradigm; and finally, this research highlights the importance of teaching entrepreneur at universities, with straight society benefits. The results suggests that innovation is directly enrolled with a successful development of certain society, as well, is actually the biggest business competitive differential into corporative universe. In one way of getting results of social advancement to inform entrepreneur research practice, it appears that entrepreneurs concepts, necessarily, must be incorporated into the array of Science/Technology/Innovation for the effective development of supported formula. This article develops a thought about actual scientific researches paradigm, the way that is built on today, and if it's sufficient to effectively get the results that society expects from main bodies to create human resource and researches, especially those with innovation aspects, at Brazilian economic improvement.

Economic impact of treatment for surgical site infections in cases of total knee arthroplasty in a tertiary public hospital in Brazil

The aim of this study was to estimate the additional cost of treatment of a group of nosocomial infections in a tertiary public hospital. A retrospective observational cohort study was conducted by means of analyzing the medical records of 34 patients with infection after total knee arthroplasty, diagnosed in 2006 and 2007, who met the criteria for nosocomial infection according to the Centers for Disease Control and Prevention. To estimate the direct costs of treatment for these patients, the following data were gathered: length of hospital stay, laboratory tests, imaging examinations, and surgical procedures performed. Their costs were estimated from the minimum values according to the Brazilian Medical Association. The estimated cost of the antibiotics used was also obtained. The total length of stay in the ward was 976 days, at a cost of US$ 18,994.63, and, in the intensive care unit, it was 34 days at a cost of US$ 5,031.37. Forty-two debridement procedures were performed, at a cost of US$ 5,798.06, and 1965 tests (laboratory and imaging) were also performed, at a cost of US$ 15,359.25. US$ 20,845.01 was spent on antibiotics and US$ 1,735.16 on vacuum assisted closure therapy, microsurgical flaps, implant removal, spacer use, and surgical revision. The total additional cost of these cases of hospital infection in 2006 and 2007 was of US$ 91,843.75. Based on that, we demonstrate that the high cost of treatment for hospital infections emphasizes the importance of taking measures to prevent and control hospital infection.

Nutritional reserves of Vochysiaceae seeds: chemical diversity and potential economic uses

Contents of proteins, carbohydrates and oil of seeds of 57 individuals of Vochysiaceae, involving one species of Callisthene, six of Qualea, one of Salvertia and eight of Vochysia were determined. The main nutritional reserves of Vochysiaceae seeds are proteins (20% in average) and oils (21. 6%). Mean of carbohydrate contents was 5. 8%. Callisthene showed the lowest protein content (16. 9%), while Q. cordata was the species with the highest content (30% in average). The contents of ethanol soluble carbohydrates were much higher than those of water soluble carbohydrates. Oil contents lay above 20% for most species (30. 4% in V. pygmaea and V. pyramidalis seeds). The predominant fatty acids are lauric (Q. grandiflora), oleic (Qualea and Salvertia) or acids with longer carbon chains (Salvertia and a group of Vochysia species). The distribution of Vochysiaceae fatty acids suggests for seeds of some species an exploitation as food sources (predominance of oleic acid), for other species an alternative to cocoa butter (high contents or predominance of stearic acid) or the production of lubricants, surfactants, detergents, cosmetics and plastic (predominance of acids with C20 or C22 chains) or biodiesel (predominance of monounsaturated acids). The possibility of exploitation of Vochysiaceae products in a cultivation regimen and in extractive reserves is discussed.

Trade unions and the economic performance of brazilian establishments

Este artigo analisa, pela primeira vez na literatura, o impacto dos sindicatos de trabalhadores em vários indicadores de desempenho econômico de firmas industriais brasileiras. Realizou-se uma pesquisa retrospectiva sobre a densidade sindical de 1000 estabelecimentos industriais brasileiros e seus resultados foram combinados aos indicadores de desempenho econômico da Pesquisa Industrial Anual (PIA) de 1990 a 2000. Os resultados indicam que a relação entre a densidade sindical na firma e seus salários, emprego e produtividade, é não-linear, ou seja, um aumento no grau de sindicalização leva a um melhor desempenho, porém a taxas decrescentes. Observou-se, também, uma relação negativa entre sindicalização e rentabilidade. Finalmente, estabelecimentos que introduziram mecanismos de 'participação nos lucros' aumentaram sua produtividade e rentabilidade no período e pagaram maiores salários nas firmas onde o grau de sindicalização era maior.