| In the context of sociology of science, scientists themselves have been often ignored by mainstream concerns for understanding scientific activities and their institutions. Here the action agents of scientific activities, scientists as categorically differentiable populations (including specialists in a broader sense), become the focus of my analyses through their interaction structure. For this particular purpose, first some plausible models are constructed (also modified and extended) from analogous ecological ideas and related structural equation model. One of the main advantages in the model construction approach, specially dealing with mathematical models, seems to appear when further analyses implies theoretical extensions based on the speculated models. In addition, empirical predictions also becomes specified from them. Every later development throughout the paper derived from or related to such model construction approach. Theoretically, scientists' interaction pattern (competitive vs. cooperative through different levels of interaction, horizontal or hierarchical) could be better understood by looking at their interaction structure, assuming that the consistent structure, as a social system, emerges from interacting populations. Accordingly, the issue of whether such emergent system is stable or not is raised. Methodologically, the relevancy issue of traditional hypothesis testing on the interaction parameters is first raised. Stimulated by such problem, the error distributions of the interaction parameters are examined. While the effort to include more reality into my models was continued after the model construction effort, most distinctive ones seem to comprise different resource inclusion effects (and also different pattern of resource inclusion effect) into the model systems. Such model extension is continuously considered throughout later simulation studies, which makes sensible when the population dynamics is determined by the nonlinear differential structural equation model systems. Finally, to support the utility of the above model approach, an empirical data set, "Human Factors Specialists Education and Utilization (1991)," is cautiously examined. |
