Thomas K. Burch

Demography in a new key: a theory of population theory.

The widespread opinion that demography is lacking in theory is based in part on a particular view of the nature of scientific theory, generally known as logical empiricism [or positivism]. A newer school of philosophy of science, the model-based view, provides a different perspective on demography, one that enhances its status as a scientific discipline. From this perspective, much of formal demography can be seen as a collection of substantive models of population dynamics [how populations and cohorts behave], in short, theoretical knowledge. And many theories in behavioural demography - often discarded as too old or too simplistic - can be seen as perfectly good scientific theory, useful for many purposes, although often in need of more rigorous statement.

Computer Modelling of Theory: Explanation for the 21st Century

The words theory, model, and explanation are used in different ways by different writers. Complete agreement on their meanings among natural scientists, social scientists, philosophers of science, engineers and others seems unlikely, since meaning depends partly on context and on discipline-specific conventions. Accepted meanings of these words often depend on subject matter, and on the purposes of research. In practice, a theory, model, or explanation—or a good theory, model, or explanation—for a physicist or chemist may differ in some respects from a theory, model, or explanation for a biologist, a meteorologist, or a demographer. These differences may appear all the greater if one looks at the use of models and theories in practical decision making, as in engineering or policy formation.

Early Life Transitions of Canadian Youth: Effects of Family Transformation and Community Characteristics

This paper looks at the impact of family transformation and community characteristics on the timing and sequences of early life transitions of Canadians born in 1971-75. Using event history techniques of analysis, the effects on school completion, start of regular work, and home-leaving are examined using a data set that merged the 1995 General Social Survey of the Family with data derived from the enumeration areas of the 1996 Census. The results show that family disruption impacts negatively on the transition to adulthood. And, mother=s work status and community-level characteristics indicative of availability of material resources and opportunities have significant effect on the timing of transition to adulthood mainly through longer period of education.

Teaching Demography: Ten Principles and Two Rationales

This chapter present ten general principles for improving the teaching of demography. Support for these principles is found in (a) the ideas of the semantic or model-based school of the philosophy of science, and (b) the design of courses and textbooks in the physical and biological sciences. Demography courses and texts based on these principles would present demography as a complete science, with abundant theoretical models as well as technique, data and descriptive findings.

Does demography need differential equations

The starting point for this essay is the observation—partly impressionistic—that demography as a discipline has tended to neglect the predator-prey equations in courses, textbooks, compendia, and research papers. This is surprising, since the equations bear the name of A. J. Lotka, one of the acknowledged founders of modern demography. This relative neglect is unfortunate, since a central fact about the human species is that we are deeply implicated in nature as both predator and prey. Possible explanations for this situation are discussed, including a general neglect of systematic theory, and of differential equations, a branch of mathematics especially suited to the statement and exploration of theories of demographic processes.

The model-based view of science: an encouragement to interdisciplinary work

Widely thought to have made social science more scientific, logical empiricism has tended rather to hamper its balanced development. Its emphasis on the ‘truth’ of ‘scientific laws’ has promoted competition within and among disciplines, and to the rejection and neglect of valuable scientific ideas. The ‘semantic’ or ‘model-based’ school of philosophy of science provides a convincing alternative to logical empiricism. A leading exponent of this school is Ronald Giere in Science Without Laws. For Giere it is the model not the law that is the central element of scientific knowledge. Models are also ‘true’ only in the sense that definitions are true; they are not empirically true. Models are to be judged, not in terms of truth, but in terms of whether they fit some real-world system closely enough for a given purpose. One can have, says Giere, ‘realism without truth’. There can be more than one realistic model pertaining to a given real-world system. Several examples from demography illustrate the negative influence of logical empiricism on cumulative theory and on openness to models from other disciplines. The model-based view, by contrast, encourages a ‘tool kit’ approach to theory and models. All reasonable models are carefully developed and kept ready at hand for use as appropriate. Some may be useful for explanation, others for prediction, still others for policy formation or for teaching. The same spirit leads to openness across disciplines. One values the leading theories and principles of ones own discipline, but one also recognises their inherent limits, as abstract representations of concrete reality. There follows greater appreciation of the tools of other disciplines.

The Cohort-Component Population Projection: A Strange Attractor for Demographers

The cohort-component population projection algorithm has generally been viewed as having one purpose, namely population forecasting. And it has been ‘canonized’ as the one best method for this purpose. A more fruitful view might be to see it first and foremost as a theoretical model of population dynamics, useful for many different purposes. At the same time, other approaches to population forecasting should be given greater attention, approaches with both advantages and disadvantages compared to the cohort-component approach (See Chap. 4 above).

Men's life course trajectories: Exploring the differences by cohort and social class

Abstract Making use of retrospective information gathered through a 2001 national survey in Canada, we examined the timing of transitions and life course trajectories starting from events experienced early in life to events that usually happen later in life. The subjects of the study were men born from 1926 to 1975, and the analyses were done by 5‐year birth cohorts and by social status. Results of the analysis showed that there have been significant changes over cohorts and that the life course trajectories of the poor were different from those economically better off. Men from higher social class were more likely to experience family life events ‐ such as start of regular work and entry into union ‐ at older ages, and were also more likely to follow a normative life course trajectory. We explore the factors affecting such differences in the context of constraints on decision‐making.

On Teaching Demography: Some Non-Traditional Guidelines

This chapter repeats some of ideas from Chaps. 11 and 12, but with slightly different emphasis and concrete examples. A key section compares the exponential model (formal demography) and the Easterlin fertility model (behavioral demography), arguing for the similarity of their epistemological status as abstract models. This chapter also contains a brief reprise of the model-based view of science contrasted with logical empiricism. It can serve as a brief summary of the earlier chapters.

Computer Modeling of Theory: Explanation for the Twenty-First Century

Twenty-first century computing has given us new ways of doing science. Old notions of elegance and simplicity are not completely outmoded. But they need to be complemented by a greater awareness of the complexity of social, economic and demographic systems, and the realization that simple models, while tractable and intellectually satisfying, often are not adequate to the task at hand – explanation, prediction, or policy guidance. In the words of one biologist, ‘It is only now that we have the ability to do complex calculations and simulations that we are discovering that a great many systems seem to have an inherent complexity that cannot be simplified…’ (Rowe GW, Theoretical models in biology: the origin of life, the immune system, and the brain. Oxford University Press, Oxford, 1994).