Post-Soviet informality: towards theory-building

Purpose – The purpose of this paper is to suggest that informal practices and institutions of post-Soviet countries differ from informality in other post-socialist regions and, therefore, proposes categorizing it as “post-Soviet informality” – a composite definition that extends beyond the concept of “informal economy” and encompasses, along with economic activities, social and political spheres. Design/methodology/approach – The arguments of the paper are based on a comprehensive analysis of secondary sources. Findings – This paper shows that, owing to the effects of antecedent regime’s legacies and the problems of post-communist transition, for the proper analysis of informality in post-Soviet countries it needs to be based on an own concept. Originality/value – This study, in contrast to the existing literature on informality in post-communist spaces, specifically focuses on the informal sphere of post-Soviet countries, suggesting that the informal institutions and practices thriving across the vast post-Soviet space not only differ from the informal spheres elsewhere in the world, but also from informality in other post-communist regions

Power, theory building, and heuristics.

Avoir recours à une perspective en termes de pouvoir ouvre des opportunité nombreuses pour renouveler l'agenda de la recherche en management. Une des valeurs ajoutées trop souvent méconnues est d'ordre méthodologique ou heuristique. Enfin l'article énonce des pistes de recherche encore à explorer.Power can be used as a way to create fruitful opportunities for scientific agendas. Power also offers an analytical tool to make sense of social phenomena. This does not imply that power theory building only may derive heuristic benefits using it. The paper concludes by a series of still open issues for further research.Analytical tool; Scientific enigmas; Power; Organized action;

Rationality and the Foundations of Positive Political Theory

In this paper, we discuss and debunk the four most common critiques of the rational choice research program (which we prefer to call Positive Political Theory) by explaining and advocating its foundations: the rationality assumption, component analysis (abstraction), strategic behavior, and theory building, in turn. We argue that the rationality assumption and component analysis, properly understood, can be seen to underlie all social science, despite the protestations of critics. We then discuss the two ways that PPT most clearly contributes to political science (i.e., what distinguishes it from other research programs), namely the introduction of strategic behavior (people do not just act; they interact) and PPT’s more careful attention to the theory-building step within the scientific method. We explain the roles of theory- building and of empirical “testing,” respectively, in scientific inquiry, and the criteria by which theories should and should not be judged

Theory-Building With Cases

Theory-building with cases is (a) formulating new propositions that emerge from the empirical evidence in a sample of cases and (b) testing them in the same sample. The main difference with most other forms of generating new propositions (such as analyzing the theoretical literature, brainstorming, etc.) is its empirical character. The main difference with other forms of discovering new propositions in empirical evidence (such as in ‘exploratory’ research) is that only those theoretical formulations are accepted as a result of the theory-building study that are confirmed in a test in the sample from which the proposition was built. It is possible that a proposition about a relationship between two variables emerges from an exploratory single case study (e.g., when both variables have extreme values in that case), but it is not possible to test that new proposition in the same study because this would require a comparison in a sample of cases. The term theory-building study (as distinct from an exploratory study) is used here only for studies in which a proper test of the new proposition has been conducted

Experiment and theory building

I examine the role of inference from experiment in theory building. What are the options open to the scientific community when faced with an experimental result that appears to be in conflict with accepted theory? I distinguish, in Laudan's (1977), Nickels's (1981), and Franklin's (1993) sense, between the context of pursuit and the context of justification of a scientific theory. Making this distinction allows for a productive middle position between epistemic realism and constructivism. The decision to pursue a new or a revised theory in response to the new evidence may not be fully rationally determined. Nonetheless, it is possible to distinguish the question of whether there is reason to pursue a theory from the question of whether that theory, once it has been pursued over time, solves a problem of interest to science. I argue that, in this context, there is a solid way to distinguish between the contexts of pursuit and of justification, on the basis of a theory's evidential support and problem-solving ability

Structure or Noise?

We show how rate-distortion theory provides a mechanism for automated theory building by naturally distinguishing between regularity and randomness. We start from the simple principle that model variables should, as much as possible, render the future and past conditionally independent. From this, we construct an objective function for model making whose extrema embody the trade-off between a model's structural complexity and its predictive power. The solutions correspond to a hierarchy of models that, at each level of complexity, achieve optimal predictive power at minimal cost. In the limit of maximal prediction the resulting optimal model identifies a process's intrinsic organization by extracting the underlying causal states. In this limit, the model's complexity is given by the statistical complexity, which is known to be minimal for achieving maximum prediction. Examples show how theory building can profit from analyzing a process's causal compressibility, which is reflected in the optimal models' rate-distortion curve--the process's characteristic for optimally balancing structure and noise at different levels of representation.Comment: 6 pages, 2 figures; http://cse.ucdavis.edu/~cmg/compmech/pubs/son.htm

Nurturing the young shoots of talent: Using action research for exploration and theory building

This is an Author's Accepted Manuscript of an article published in European Early Childhood Education Research Journal, 19(4), 433-450, 2011, copyright Taylor & Francis, available online at: http://www.tandfonline.com/10.1080/1350293X.2011.623515.This paper reports the outcomes of a set of action research projects carried out by teacher researchers in 14 local education authorities in England, working collaboratively with university tutors, over a period of three years. The common aim of all the projects was to explore practical ways of nurturing the gifts and talents of children aged four–seven years. The project was funded by the Department of Education and Skills in England as part of the government's gifted and talented programme. The project teachers felt that their understanding of issues relating to nurturing the gifts and talents of younger children was enhanced through their engagement in the project. It was possible to map the findings of the projects to the English government's National Quality Standards for gifted and talented education which include: (1) identification; (2) effective provision in the classroom; (3) enabling curriculum entitlement and choice; (4) assessment for learning; (5) engaging with community, families and beyond. The findings are also analysed within the framework of good practice in educating children in the first years of schooling. Participating practitioners felt that action research offered them a suitable methodology to explore the complexity of the topic of giftedness through cycles of planning, action and reflection and personal theory building