Growing Flowers in the Frost: Civic Activity, Citizenship and Gender in Russia

This study analyzes civic activity, citizenship and their gendered manifestations in contemporary Russia. It is based on a case study conducted in the city of Tver , located in the vicinity of Moscow, during 2001-2005. The data consists of interviews with civic activists and municipal and regional authorities; observations of civic organizations; and a quantitative survey conducted among local civic groups. The theoretical and methodological framework of the study draws upon a micro perspective on organization, discourse analysis, gender and citizenship theories and Pierre Bourdieu s theory of fields and capital. This study develops theoretical understanding of the characteristics and logic of civic organization in Russia. It shows that social class centrally structures the field of civic activity. Organizations can be seen as a vehicle of the educated class to advocate their interests, help themselves and seek both social and individual-level change. The study also argues that civic organizations founded during the post-Soviet era are often an institutionalized form of informal social networks. Networks, which were a central element of everyday interaction in Soviet society, are a resource and often the only resource available that can be made use of in contemporary organizational activities. The study argues that gender operates as a key structuring principle in the Russian socio-political community. Civic activity is often discursively associated with femininity and institutional politics with masculinity. Women tend to participate more than men in civic organizations, while men dominate the formal political domain. The study shows that civic organizations are important loci of communality. This communality, however, differs from the communality envisioned in the communitarian and social capital debates in the West. It is selective communality , as it is restricted to the members of the organizations and does not create generalized reciprocity and trust. Civic organizations tend to build upon and reproduce the traditional Russian organizational form of circles , kruzhki. Along with the analysis of civic activities, the study also examines the redefinition of the role and functions of the state. The authorities interviewed in this study understand civic organizations as serving those goals and interests determined by the authorities, instead of viewing them as sites of citizens self-organization around interests and problems citizens themselves deem important, or as a counterforce to the state. By contrast, civic activists understand the core of organizational activity to be advocacy of their interests and rights, tackling social problems, the pursuit of wider social change and self-help. Co-operation between authorities and organizations tends to be personified and based upon unequal, hierarchical patron-client arrangements, which inhibits the development of democratic governance. The study will be published in Routledge Contemporary Russia and Eastern Europe Series later this year.

Communicative and Anticipatory Decision-making Supported by Bayesian Networks

The purpose of this research is to draw up a clear construction of an anticipatory communicative decision-making process and a successful implementation of a Bayesian application that can be used as an anticipatory communicative decision-making support system. This study is a decision-oriented and constructive research project, and it includes examples of simulated situations. As a basis for further methodological discussion about different approaches to management research, in this research, a decision-oriented approach is used, which is based on mathematics and logic, and it is intended to develop problem solving methods. The approach is theoretical and characteristic of normative management science research. Also, the approach of this study is constructive. An essential part of the constructive approach is to tie the problem to its solution with theoretical knowledge. Firstly, the basic definitions and behaviours of an anticipatory management and managerial communication are provided. These descriptions include discussions of the research environment and formed management processes. These issues define and explain the background to further research. Secondly, it is processed to managerial communication and anticipatory decision-making based on preparation, problem solution, and solution search, which are also related to risk management analysis. After that, a solution to the decision-making support application is formed, using four different Bayesian methods, as follows: the Bayesian network, the influence diagram, the qualitative probabilistic network, and the time critical dynamic network. The purpose of the discussion is not to discuss different theories but to explain the theories which are being implemented. Finally, an application of Bayesian networks to the research problem is presented. The usefulness of the prepared model in examining a problem and the represented results of research is shown. The theoretical contribution includes definitions and a model of anticipatory decision-making. The main theoretical contribution of this study has been to develop a process for anticipatory decision-making that includes management with communication, problem-solving, and the improvement of knowledge. The practical contribution includes a Bayesian Decision Support Model, which is based on Bayesian influenced diagrams. The main contributions of this research are two developed processes, one for anticipatory decision-making, and the other to produce a model of a Bayesian network for anticipatory decision-making. In summary, this research contributes to decision-making support by being one of the few publicly available academic descriptions of the anticipatory decision support system, by representing a Bayesian model that is grounded on firm theoretical discussion, by publishing algorithms suitable for decision-making support, and by defining the idea of anticipatory decision-making for a parallel version. Finally, according to the results of research, an analysis of anticipatory management for planned decision-making is presented, which is based on observation of environment, analysis of weak signals, and alternatives to creative problem solving and communication.

Social Networks and Everyday Practices in Russia

My doctoral dissertation in sociology and Russian studies, Social Networks and Everyday Practices in Russia, employs a "micro" or "grassroots" perspective on the transition. The study is a collection of articles detailing social networks in five different contexts. The first article examines Russian birthdays from a network perspective. The second takes a look at health care to see whether networks have become obsolete in a sector that is still overwhelmingly public, but increasingly being monetarised. The third article investigates neighbourhood relations. The fourth details relationships at work, particularly from the vantage point of internal migration. The fifth explores housing and the role of networks and money both in the Soviet and post-Soviet era. The study is based on qualitative social network and interview data gathered among three groups, teachers, doctors and factory workers, in St. Petersburg during 1993-2000. Methodologically it builds on a qualitative social network approach. The study adds a critical element to the discussion on networks in post-socialism. A considerable consensus exists that social networks were vital in state socialist societies and were used to bypass various difficulties caused by endemic shortages and bureaucratic rigidities, but a more debated issue has been their role in post-socialism. Some scholars have argued that the importance of networks has been dramatically reduced in the new market economy, whereas others have stressed their continuing importance. If a common denominator in both has been a focus on networks in relation to the past, a more overlooked aspect has been the question of inequality. To what extent is access to networks unequally distributed? What are the limits and consequences of networks, for those who have access, those outside networks or society at large? My study provides some evidence about inequalities. It shows that some groups are privileged over others, for instance, middle-class people in informal access to health care. Moreover, analysing the formation of networks sheds additional light on inequalities, as it highlights the importance of migration as a mechanism of inequality, for example. The five articles focus on how networks are actually used in everyday life. The article on health care, for instance, shows that personal connections are still important and popular in post-Soviet Russia, despite the growing importance of money and the emergence of "fee for service" medicine. Fifteen of twenty teachers were involved in informal medical exchange during a two-week study period, so that they used their networks to bypass the formal market mechanisms or official procedures. Medicines were obtained through personal connections because some were unavailable at local pharmacies or because these connections could provide medicines for a cheaper price or even for free. The article on neighbours shows that "mutual help" was the central feature of neighbouring, so that the exchange of goods, services and information covered almost half the contacts with neighbours reported. Neighbours did not provide merely small-scale help but were often exchange partners because they possessed important professional qualities, had access to workplace resources, or knew somebody useful. The article on the Russian work collective details workplace-related relationships in a tractor factory and shows that interaction with and assistance from one's co-workers remains important. The most interesting finding was that co-workers were even more important to those who had migrated to the city than to those who were born there, which is explained by the specifics of Soviet migration. As a result, the workplace heavily influenced or absorbed contexts for the worker migrants to establish relationships whereas many meeting-places commonly available in Western countries were largely absent or at least did not function as trusted public meeting places to initiate relationships. More results are to be found from my dissertation: Anna-Maria Salmi: Social Networks and Everyday Practices in Russia, Kikimora Publications, 2006, see www.kikimora-publications.com.

Optimal threshold policies for admission control in communication networks via discrete parameter stochastic approximation

The problem of admission control of packets in communication networks is studied in the continuous time queueing framework under different classes of service and delayed information feedback. We develop and use a variant of a simulation based two timescale simultaneous perturbation stochastic approximation (SPSA) algorithm for finding an optimal feedback policy within the class of threshold type policies. Even though SPSA has originally been designed for continuous parameter optimization, its variant for the discrete parameter case is seen to work well. We give a proof of the hypothesis needed to show convergence of the algorithm on our setting along with a sketch of the convergence analysis. Extensive numerical experiments with the algorithm are illustrated for different parameter specifications. In particular, we study the effect of feedback delays on the system performance.

Search for the Higgs Boson Using Neural Networks in Events with Missing Energy and b-Quark Jets in pp̅ Collisions at √s=1.96 TeV

We report on a search for the standard model Higgs boson produced in association with a $W$ or $Z$ boson in $p\bar{p}$ collisions at $\sqrt{s} = 1.96$ TeV recorded by the CDF II experiment at the Tevatron in a data sample corresponding to an integrated luminosity of 2.1 fb$^{-1}$. We consider events which have no identified charged leptons, an imbalance in transverse momentum, and two or three jets where at least one jet is consistent with originating from the decay of a $b$ hadron. We find good agreement between data and predictions. We place 95% confidence level upper limits on the production cross section for several Higgs boson masses ranging from 110$\gevm$ to 150$\gevm$. For a mass of 115$\gevm$ the observed (expected) limit is 6.9 (5.6) times the standard model prediction.

Comparative analysis of thermophilic and mesophilic proteins using Protein Energy Networks

Background: Thermophilic proteins sustain themselves and function at higher temperatures. Despite their structural and functional similarities with their mesophilic homologues, they show enhanced stability. Various comparative studies at genomic, protein sequence and structure levels, and experimental works highlight the different factors and dominant interacting forces contributing to this increased stability. Methods: In this comparative structure based study, we have used interaction energies between amino acids, to generate structure networks called as Protein Energy Networks (PENs). These PENs are used to compute network, sub-graph, and node specific parameters. These parameters are then compared between the thermophile-mesophile homologues. Results: The results show an increased number of clusters and low energy cliques in thermophiles as the main contributing factors for their enhanced stability. Further more, we see an increase in the number of hubs in thermophiles. We also observe no community of electrostatic cliques forming in PENs. Conclusion: In this study we were able to take an energy based network approach, to identify the factors responsible for enhanced stability of thermophiles, by comparative analysis. We were able to point out that the sub-graph parameters are the prominent contributing factors. The thermophiles have a better-packed hydrophobic core. We have also discussed how thermophiles, although increasing stability through higher connectivity retains conformational flexibility, from a cliques and communities perspective.

Comparative analysis of thermophilic and mesophilic proteins using Protein Energy Networks

Background: Thermophilic proteins sustain themselves and function at higher temperatures. Despite their structural and functional similarities with their mesophilic homologues, they show enhanced stability. Various comparative studies at genomic, protein sequence and structure levels, and experimental works highlight the different factors and dominant interacting forces contributing to this increased stability. Methods: In this comparative structure based study, we have used interaction energies between amino acids, to generate structure networks called as Protein Energy Networks (PENs). These PENs are used to compute network, sub-graph, and node specific parameters. These parameters are then compared between the thermophile-mesophile homologues. Results: The results show an increased number of clusters and low energy cliques in thermophiles as the main contributing factors for their enhanced stability. Further more, we see an increase in the number of hubs in thermophiles. We also observe no community of electrostatic cliques forming in PENs. Conclusion: In this study we were able to take an energy based network approach, to identify the factors responsible for enhanced stability of thermophiles, by comparative analysis. We were able to point out that the sub-graph parameters are the prominent contributing factors. The thermophiles have a better-packed hydrophobic core. We have also discussed how thermophiles, although increasing stability through higher connectivity retains conformational flexibility, from a cliques and communities perspective.

Global and EU governance for sustainable forest management with special reference to capacity building in Ethiopia and Southern Sudan

The purpose of this study was to produce information on and practical recommendations for informed decision-making on and capacity building for sustainable forest management (SFM) and good forest governance. This was done within the overall global framework for sustainable development with special emphasis on the EU and African frameworks and on Southern Sudan and Ethiopia in particular. The case studies on Southern Sudan and Ethiopia focused on local, national and regional issues. Moreover, this study attempted to provide both theoretical and practical new insight. The aim was to build an overall theoretical framework and to study its key contents and main implications for SFM and good forest governance at all administration levels, for providing new tools for capacity building in natural resources management. The theoretical framework and research approach were based on the original research problem and the general and specific aims of the study. The key elements of the framework encompass sustainable development, global and EU governance, sustainable forest management (SFM), good forest governance, as well as international and EU law. The selected research approach comprised matrix-based assessment of international, regional (EU and Africa) and national (Southern Sudan and Ethiopia) policy and legal documents. The specific case study on Southern Sudan also involved interviews and group discussions with local community members and government officials. As a whole, this study attempted to link the global, regional, national and local levels in forest-sector development and especially to analyse how the international policy development in environmental and forestry issues is reflected in field-level progress towards SFM and good forest governance, for the specific cases of Southern Sudan and Ethiopia. The results on Southern Sudan focused on the existing situation and perceived needs in capacity building for SFM and good forest governance at all administration levels. Specifically, the results of the case study on Southern Sudan presented the current situation in selected villages in the northern parts of Renk County in Upper Nile State, and the implications of Multilateral Environmental Agreements (MEAs) and of the new forest policy framework for capacity building actions. The results on Ethiopia focused on training, extension, research, education and new curriculum development within higher education institutions and particularly at the Wondo Genet College of Forestry and Natural Resources (WGCF-NR), which administratively lies under Hawassa University. The results suggest that, for both cases studies, informed decision-making on and capacity building for SFM and good forest governance require comprehensive, long-term, cross-sectoral, coherent and consistent approaches within the dynamic and evolving overall global framework, including its multiple inter-linked levels. The specific priority development and focus areas comprised the establishment of SFM and good forest governance in accordance with the overall sustainable development priorities and with more focus on the international trade in forest products that are derived from sustainable and legal sources with an emphasis on effective forest law enforcement and governance at all levels. In Upper Nile State in Southern Sudan there were positive development signals such as the will of the local people to plant more multipurpose trees on farmlands and range lands as well as the recognition of the importance of forests and trees for sustainable rural development where food security is a key element. In addition, it was evident that the local communities studied in Southern Sudan also wanted to establish good governance systems through partnerships with all actors and through increased local responsibilities. The results also suggest that the implementation of MEAs at the local level in Southern Sudan requires mutually supportive and coherent approaches within the agreements as well as significantly more resources and financial and technical assistance for capacity building, training and extension. Finally, the findings confirm the importance of full utilization of the existing local governance and management systems and their traditional and customary knowledge and practices, and of new development partnerships with full participation of all stakeholders. The planned new forest law for Southern Sudan, based on an already existing new forest policy, is expected to recognize the roles of local-level actors, and it would thus obviously facilitate the achieving of sustainable forest management.

Truthful and Quality Conscious Query Incentive Networks

Query incentive networks capture the role of incentives in extracting information from decentralized information networks such as a social network. Several game theoretic tilt:Kids of query incentive networks have been proposed in the literature to study and characterize the dependence, of the monetary reward required to extract the answer for a query, on various factors such as the structure of the network, the level of difficulty of the query, and the required success probability.None of the existing models, however, captures the practical andimportant factor of quality of answers. In this paper, we develop a complete mechanism design based framework to incorporate the quality of answers, in the monetization of query incentive networks. First, we extend the model of Kleinberg and Raghavan [2] to allow the nodes to modulate the incentive on the basis of the quality of the answer they receive. For this qualify conscious model. we show are existence of a unique Nash equilibrium and study the impact of quality of answers on the growth rate of the initial reward, with respect to the branching factor of the network. Next, we present two mechanisms; the direct comparison mechanism and the peer prediction mechanism, for truthful elicitation of quality from the agents. These mechanisms are based on scoring rules and cover different; scenarios which may arise in query incentive networks. We show that the proposed quality elicitation mechanisms are incentive compatible and ex-ante budget balanced. We also derive conditions under which ex-post budget balance can beachieved by these mechanisms.

A novel approach for large-scale polypeptide folding based on elastic networks using continuous optimization

We present a new computationally efficient method for large-scale polypeptide folding using coarse-grained elastic networks and gradient-based continuous optimization techniques. The folding is governed by minimization of energy based on Miyazawa–Jernigan contact potentials. Using this method we are able to substantially reduce the computation time on ordinary desktop computers for simulation of polypeptide folding starting from a fully unfolded state. We compare our results with available native state structures from Protein Data Bank (PDB) for a few de-novo proteins and two natural proteins, Ubiquitin and Lysozyme. Based on our simulations we are able to draw the energy landscape for a small de-novo protein, Chignolin. We also use two well known protein structure prediction software, MODELLER and GROMACS to compare our results. In the end, we show how a modification of normal elastic network model can lead to higher accuracy and lower time required for simulation.

Clustering in Concept Association Networks

We view association of concepts as a complex network and present a heuristic for clustering concepts by taking into account the underlying network structure of their associations. Clusters generated from our approach are qualitatively better than clusters generated from the conventional spectral clustering mechanism used for graph partitioning.

Detecting Earnings Management Using Neural Networks

Detecting Earnings Management Using Neural Networks. Trying to balance between relevant and reliable accounting data, generally accepted accounting principles (GAAP) allow, to some extent, the company management to use their judgment and to make subjective assessments when preparing financial statements. The opportunistic use of the discretion in financial reporting is called earnings management. There have been a considerable number of suggestions of methods for detecting accrual based earnings management. A majority of these methods are based on linear regression. The problem with using linear regression is that a linear relationship between the dependent variable and the independent variables must be assumed. However, previous research has shown that the relationship between accruals and some of the explanatory variables, such as company performance, is non-linear. An alternative to linear regression, which can handle non-linear relationships, is neural networks. The type of neural network used in this study is the feed-forward back-propagation neural network. Three neural network-based models are compared with four commonly used linear regression-based earnings management detection models. All seven models are based on the earnings management detection model presented by Jones (1991). The performance of the models is assessed in three steps. First, a random data set of companies is used. Second, the discretionary accruals from the random data set are ranked according to six different variables. The discretionary accruals in the highest and lowest quartiles for these six variables are then compared. Third, a data set containing simulated earnings management is used. Both expense and revenue manipulation ranging between -5% and 5% of lagged total assets is simulated. Furthermore, two neural network-based models and two linear regression-based models are used with a data set containing financial statement data from 110 failed companies. Overall, the results show that the linear regression-based models, except for the model using a piecewise linear approach, produce biased estimates of discretionary accruals. The neural network-based model with the original Jones model variables and the neural network-based model augmented with ROA as an independent variable, however, perform well in all three steps. Especially in the second step, where the highest and lowest quartiles of ranked discretionary accruals are examined, the neural network-based model augmented with ROA as an independent variable outperforms the other models.

Essays on the Costs and Benefits of Large Shareholders in Corporate Governance (summary section only)

“Corporate governance deals with the ways in which suppliers of finance to firms assure themselves of getting a return on their investment” (Shleifer and Vishny (1997, p. 737). According to La Porta et al. (1999), research in corporate finance relevant for most countries should focus on the incentives and capabilities of controlling shareholders to treat themselves preferentially at the expense of minority shareholders. Accordingly, this thesis sets out to answer a number of research questions regarding the role of large shareholders in public firms that have received little attention in the literature so far. A common theme in the essays stems from the costs and benefits of individual large-block owners and the role of control contestability from the perspective of outside minority shareholders. The first essay empirically examines whether there are systematic performance differences between family controlled and nonfamily controlled firms in Western Europe. In contrast to the widely held view that family control penalizes firm value, the essay shows that publicly traded family firms have higher performance than comparable firms. In the second essay, we present both theoretical and empirical analysis on the effects of control contestability on firm valuation. Consistent with the theoretical model, the empirical results show that minority shareholders benefit from a more contestable control structure. The third essay explores the effects of individual large-block owners on top management turnover and board appointments in Finnish listed firms. The results indicate that firm performance is an important determinant for management and board restructurings. For certain types of turnover decisions the corporate governance structure influences the performance / turnover sensitivity. In the fourth essay, we investigate the relation between the governance structure and dividend policy in Finnish listed firms. We find evidence in support of the outcome agency model of dividends stating that lower agency conflicts should be associated with higher dividend payouts.