UNESCO 571 demand-making process over a large number of countries having very different political systems,it is quite simple to check for the existence of conditions said to be prerequisite to those demands.The test reported here compiled and analyzed quantitative indicators of domestic conditions that might prompt creation of a science policy bureaucracy in a sample of forty-four countries chosen to be globally representative in terms of both geography and develop- ment levels.As suggested in the foregoing discussion,these were percentage of GDP spent on R&D;proportion of scientists and engineers in the population; per capita GDP;and percentage of gross national product(GNP)spent on defense.A complete description of the indicators used and the method of compiling them can be found in the appendix. Testing a global sample of states raises issues about comparability among the units of analysis,particularly comparability of developing and industrialized states.Cameroon and the United States,for example,are so different on so many measures that one may question whether the units of analysis are sufficiently alike to make comparison appropriate and meaningful. In this case,comparability of the units is ensured by the research questions being asked.The hypotheses being tested concern the behavior of states as a political and organizational form:What prompts states to adopt new tasks and construct new apparatuses to carry out those tasks?The hypotheses do not carry with them caveats about degrees of stateness,state capacity,or other potentially limiting characteristics.Instead they make arguments about the behavior of states qua states.Cameroon and the United States may be very different states,but they are both states nonetheless.In fact the article will suggest that what is going on in this case is a redefinition of the state as a political and organizational form;that is,a redefinition of what is necessary and appropriate behavior for a state. Figures 1-4 show the distribution of values for each of the indicators of state conditions at the time science policy bureaucracies were created in the countries studied.A quick look at figures reveals that none of the patterns corresponds to the expected patterns described above.If any of these conditions were both necessary and sufficient,there would be a large cluster of adoptions on the histogram at that necessary and sufficient value.Instead,the adoptions appear to occur at a very wide range of values for all four of the variables.No single value of any variable appears likely as a necessary and sufficient condition for adoption. In fact,countries adopted these science bureaucracies at wildly different levels of each of these domestic conditions.Some elaboration from the raw data will make the extremely wide range of variation in values even clearer: (1)Countries created these bureaucracies when they had as few as nine scientists employed in R&D(e.g.,Congo)or as many as half a million (e.g.,the United States and the Soviet Union). (2)R&D spending as a percentage of GDP ranged from 0.01 percent at the time of adoption (Bangladesh)to 1.5 percent(France). (3)Per capita GDP in constant U.S.dollars ranged from a low of $118/yearUNESCO 571 demand-making process over a large number of countries having very different political systems, it is quite simple to check for the existence of conditions said to be prerequisite to those demands. The test reported here compiled and analyzed quantitative indicators of domestic conditions that might prompt creation of a science policy bureaucracy in a sample of forty-four countries chosen to be globally representative in terms of both geography and develop￾ment levels. As suggested in the foregoing discussion, these were percentage of GDP spent on R&D; proportion of scientists and engineers in the population; per capita GDP; and percentage of gross national product (GNP) spent on defense. A complete description of the indicators used and the method of compiling them can be found in the appendix. Testing a global sample of states raises issues about comparability among the units of analysis, particularly comparability of developing and industrialized states. Cameroon and the United States, for example, are so different on so many measures that one may question whether the units of analysis are sufficiently alike to make comparison appropriate and meaningful. In this case, comparability of the units is ensured by the research questions being asked. The hypotheses being tested concern the behavior of states as a political and organizational form: What prompts states to adopt new tasks and construct new apparatuses to carry out those tasks? The hypotheses do not carry with them caveats about degrees of stateness, state capacity, or other potentially limiting characteristics. Instead they make arguments about the behavior of states qua states. Cameroon and the United States may be very different states, but they are both states nonetheless. In fact the article will suggest that what is going on in this case is a redefinition of the state as a political and organizational form; that is, a redefinition of what is necessary and appropriate behavior for a state. Figures 1-4 show the distribution of values for each of the indicators of state conditions at the time science policy bureaucracies were created in the countries studied. A quick look at figures reveals that none of the patterns corresponds to the expected patterns described above. If any of these conditions were both necessary and sufficient, there would be a large cluster of adoptions on the histogram at that necessary and sufficient value. Instead, the adoptions appear to occur at a very wide range of values for all four of the variables. No single value of any variable appears likely as a necessary and sufficient condition for adoption. In fact, countries adopted these science bureaucracies at wildly different levels of each of these domestic conditions. Some elaboration from the raw data will make the extremely wide range of variation in values even clearer: (1) Countries created these bureaucracies when they had as few as nine scientists employed in R&D (e.g., Congo) or as many as half a million (e.g., the United States and the Soviet Union). (2) R&D spending as a percentage of GDP ranged from 0.01 percent at the time of adoption (Bangladesh) to 1.5 percent (France). (3) Per capita GDP in constant U.S. dollars ranged from a low of $118/year