The Representation of Social Processes by Markov Models

In this paper we consider a class of issues which are central to modeling social phenomena by continuous-time Markov structures. In particular, we discuss (a) embeddability, or how to determine whether observations on an empirical process could have arisen via the evolution of a continuous-time Markov structure; and (b) identification, or what to do if the observations are consistent with more than one continuous-time Markov structure. With respect to the latter topic, we discuss how to select the specific structure from the list of alternatives which should be associated with the empirical process. We point out that the issues of embeddability and identification are especially pertinent to modeling empirical processes when one has available only fragmentary data and when the observations contain "noise" or other sources of error. These characteristics, of course, describe the typical work situation of sociologists. Finally, we note the type of situation in which a continuous-time model is the proper structure to employ and indicate that issues analogous to the ones we describe here apply to modeling social processes with discrete-time structures

The Representation of Social Processes by Markov Models

In this paper we consider a class of issues which are central to modeling social phenomena by continuous-time Markov structures. In particular, we discuss (a) embeddability, or how to determine whether observations on an empirical process could have arisen via the evolution of a continuous-time Markov structure; and (b) identification, or what to do if the observations are consistent with more than one continuous-time Markov structure. With respect to the latter topic, we discuss how to select the specific structure from the list of alternatives which should be associated with the empirical process. We point out that the issues of embeddability and identification are especially pertinent to modeling empirical processes when one has available only fragmentary data and when the observations contain "noise" or other sources of error. These characteristics, of course, describe the typical work situation of sociologists. Finally, we note the type of situation in which a continuous-time model is the proper structure to employ and indicate that issues analogous to the ones we describe here apply to modeling social processes with discrete-time structures

Mathematical Representations of Development Theories

In this chapter we explore the consequences of particular stage linkage structures for the evolution of a population. We first argue the importance of constructing dynamic models of development theories and show the implications of various stage connections for population movements. A second focus concerns inverse problems: How the stage linkage structure may be recovered from survey data of the kind collected by developmental psychologists

Agricultural settlement and soil quality in the Brazilian Amazon

This paper discusses the implications of poor or non-existent information on soil quality, at the proper scale, during the planning and implementation of settlement projects in the Brazilian Amazon. Based on data from the Machadinho settlement project, Rondônia, we show that most settlers had no knowledge about the agricultural capability of the area, did not receive technical information, could not afford agricultural inputs, planted inadequate crops in the early years of occupation, and did not manage to stay in their plot for a long period of time. Satellite images indicated that patches of land with good soil quality were not necessarily the first to be utilized. Inadequately planned settlements face many challenges (poor soil being one of them) and are likely to result in land turnover, conversion of land into pasture, land concentration among wealthier persons, invasion of areas by poorer people, and deforestation, defying the main purpose of agrarian reform

Clustering on the Main Diagonal in Mobility Matrices

In this paper we compare Markov, semi-Markov, and heterogeneity formulations. We demonstrate that the familiar phenomenon of clustering on the main diagonal is an inherent consequence of the structure of certain model types. Further, underprediction of the main diagonal elements should be associated with other kinds of stochastic models, beyond Markovian, that are also applicable to social processe

Health impact assessment of industrial development projects: a spatio-temporal visualization

Development and implementation of large-scale industrial projects in complex eco-epidemiological settings typically require combined environmental, social and health impact assessments. We present a generic, spatio-temporal health impact assessment (HIA) visualization, which can be readily adapted to specific projects and key stakeholders, including poorly literate communities that might be affected by consequences of a project. We illustrate how the occurrence of a variety of complex events can be utilized for stakeholder communication, awareness creation, interactive learning as well as formulating HIA research and implementation questions. Methodological features are highlighted in the context of an iron ore development in a rural part of Afric