The Demographic Transition Model essentially sought to explain the behaviour of population density as it passes various phases of pre and post-industrial development and notably in developing countries. Whilst this model has been widely discussed throughout this degree programme and in a varying range of contexts, its reference here is a fine example of the types of models under discussion and which we are seeking to present. Kirk in Johnston 2001 informs us that early researches into Demographic Transition were taking place in 1929 by Warren Thompson. Further, that Adolph Landry in 1934 and also Frank Notestein in 1945 substantially developed his ideas.
Wrigley (1967) however, asserts that the use of such a model until the latter part of this century was unpopular. This was principally because the demographic behaviour of pre-industrial societies was such that it was of minor interest, largely predictable and that such a model was therefore unnecessary. Such thinking may be described as Malthusian, making reference to the concept of what is now described as a population’s carrying capacity as a broad explanation for the idea that the size of a population was limited to the extent to which that population could sustain itself with food from the land and technology available to it. A concept that Darwin himself was able to accept as the basic proposition for his Theory of Evolution. However, factors such as those introduced by Esther Boserup in 1965 in her book, The Conditions for Agricultural Growth controverted such a theory and demonstrated that there are indeed many other factors which need to be considered in constructing a model of this kind.
Hagget, Clift and Frey, have described the links between the Demographic Transition Model with the Quantitative Revolution as too generalised and abstract, satisfying the apparent need only to become general and compartmentalise finding into strategies: They argue that models must develop first in the construction of diagrams in geometrical form to offer a visual representation and secondly to represent in a MUCH more detailed format the spatial structures as statistical and mathematical models.
The broad history of the development and application of the Demographic Transition Model follows what is the generally accepted trend in the evolution of modelling as a concept. Thomas and Hugget (1980) have likewise stated that the development of models, and the ways in which they are used, have been as evolutionary as the subjects which the models themselves seek to explain. Thus, current thinking is that the Demographic Transition Model is outdated because there are now too many other factors which need to be fed into it in order to suitably explain demographic trends.
Overhead – Mathematical Model Building A more suitable plan for the construction of demographic models, and which emerged in the 1970s as a development from the Quantitative Revolution, is given by Thomas and Hugget and shown here in simplified form. They suggest other issues can and must be factored into demographic modelling, such as migration and disease. As may be seen, it is a major development in the progression of the Demographic Transition Model, principally because of it’s mathematical nature, but also because it is possible to introduce specific issues into the equation, test them and re-evaluate its construction if the assumptions made prove in reality to be inaccurate. For a fully detailed analysis of the nature of mathematical model building, Modelling In Geography A Mathematical Approach (1980) by Thomas and Hugget provides an excellent grounding and is to be recommended.
Although the nature of modelling may be different for each of the case studies provided here today, it may be seen from such examples that there is a fundamental link between all of them and poses a very important question. Is modelling of this kind necessary to provide answers for the phenomena we observe and seek to explain, or are they a method by which we can state observed phenomena so as to provide a framework from which an explanation may be extrapolated ? We would contend that a good model should provide a possible framework for both. In the context of a well-structured scientific study, a model should be able to clearly define a given set of circumstances so that an accurate and well-informed explanation may be made.
How, for example, could Malthus have foreseen the effects of the Industrial Revolution when proffering the proposition that the balance of human population would be self-regulating through famine or sexual abstinence ? How, can the ravaging and devastating effects of a World War be predicted in a model ? The answer to both is that unless and until it happens it cannot be, but a detailed study using a well-constructed model may well assist in projecting the FUTURE pattern of demographic transition having taken that data into account after the event.
Minshull (1975) informs us that the essence of a good model is precisely this, as there are too many “human” influences which act to produce a given phenomena for a well constructed model to explain in full under one roof, or more importantly to project without becoming so unwieldy as to be of no value at all. Matthew will now guide us through the next model we have chosen to examine, which is Rostow’s Model.