personnel essentially yield the model proposed. I cannot accept the label Westholm gives the flow diagram; it is a way of systematizing what we need to know, but it is not a theory. It is actually the cross-classification, which he says is too ambitious, of inflow and outflow information with detailed breakdowns by, for example, type of personnel, occupation, sector of employment, educational background, age, gender, nationality, etc., which would allow an explanatory or predictive theory to be developed. Such cross-tabulation is the only way to generate a model specifying what factors influence the patterns of inflow and outflow.
The schematic, as it stands, focuses solely upon the extent to which the active stock of S&T personnel (STP) is maintained. Another complementary schematic is needed to represent movement within the active stock between categories or career or job. Such a schematic would need to represent changes in the structure of the STP stock in terms of age, gender, sector of employment, fields of qualification, location, etc., across time. These changes in the structure of the stock are important in policymaking.
Once the changes in the structure of the STP stock are treated seriously, another question is raised. The topic of this conference is trends in S&T careers, not jobs. The concept of career implies the need to consider what happens to a person over time in terms of education and employment. The model of data collection implicit in Westholm's schematic is cross-sectional, not longitudinal. It would make it difficult to establish anything about trends in scientific and technical careers except through tenuous extrapolation. A simple example serves to illustrate this point. Let's say that half of the STP stock occupied research and development jobs and the other half did not (I realize this is unimaginable) at time one (1993) and the same proportions exactly were found to apply at time two (2093). (It could be that the individuals in each sector had remained the same or it could be that some proportion of individuals had switched sectors. As long as the proportions switching were identical, the results would be the same.) From such data, we know nothing about careers per se. In order to understand something about careers, we need information on one individual across his or her life span. This is, of course, the area where Nagahama's report offers great hope. It is evident, even from the very brief descriptions given, that the Japanese research is focusing upon the structure of scientific careers.
Nagahama's summary of research activity at NISTEP reveals an emphasis on modeling the factors that influence changes in the inflow and outflow of STP. The studies of public understanding of science, the assessment of the impact of educational policy, and the effectiveness of intervention techniques are all motivated by the need to understand how people come to choose and maintain effective careers in S&T. Of course, such studies are based on quite different types of information from the stock and flow model of Westholm. These data are probably even less open to tight international comparability. In fact, comparability in such studies at the level of the operational definition of indexes might be pointless. Cultural differences in the factors affecting career decisions may make cross-cultural comparability in data collection redundant as well as impossible. Cross-cultural comparability will probably have to be achieved at the level of theoretical rather than operational constructs. This may not be too severe a problem if the forecasts within cultures are good. After all, these data are designed to serve a different function from the statistics on overall stocks and flows. While stocks and flows data primarily reveal availability, these data are the basis for manipulating availability.
The ultimate objective of such modeling of the factors influencing career choice and change would be prediction and manipulation of trends in STP stocks. Westholm regards prediction or forecasting as hazardous and too difficult. Yet I am glad to see Nagahama's Institute attempting it at some levels. Without forecasting, such exercises become merely descriptive—a sort of statistical historicism. Since the data are always retrospective, they come to have a less influential role in policymaking.
Specification of the problems takes us some way toward their solution. In fact, it seems we know pretty well what sorts of data are needed on stocks and flows of STP. We also know what factors should be explored in establishing predictive models. The difficulties lie at the pragmatic rather than the conceptual level. It is the financial and political constraints that make progress slow. We should be discussing how to overcome them.