Census Division

Abstract: ion In computer science, abstraction means hiding information. In CSS, abstracting from the world “reality”—whether directly experienced (observing a riot downtown) or indirectly learning about it (reading history)—is a process involving stimulus signals, perceptions, interpretation, and cognition. CSS relies on several sources for abstracting key entities, ideas, and processes from raw stimulus signals from the real world. These sources span a hierarchy in terms of their social scientific status. At the very top of the hierarchy are social theories with demonstrable validity 10A little-known fact among many social scientists is that the theory of mechanics in physics is built around the abstraction of singleand two-body problems. Already three-body problems are hugely difficult by comparison; and, most interesting, N -body problems defy mathematical solution in closed form. 11Interestingly, humanistic fields such as music and ballet also use systems of specialized notation, far beyond what is used in traditional social science. In music, Guido d’Arezzo [b. A.D. 991 (or 992), d. 1050] is considered the founder of the modern music staff; in ballet, Rudolf von Laban [b. 1879, d. 1958] invented the symbolic system known as “labanotation” (Morasso and Tagliasco 1986). 2.7 Abstraction, Representation, and Notation 37 in terms of formal structure (internal validity) and empirical observation (external validity). Not all existing social theories meet these stringent requirements, although an increasing number of them do as research progresses. Examples of social theories that meet internal and external validity standards include Heider’s Theory of Cognitive Balance in psychology, Ricardo’s Theory of Comparative Advantage in economics, and Downs’s Median Voter Theory in political science, among others. Social theories are abstractions that point to relevant social entities, variables, and dynamics that matter in understanding and explaining social phenomena. A second source of abstraction consists of social laws. Examples of social laws include the Weber-Fechner Law in psychometrics, the Pareto Law in economics, and Duverger’s Law in political science. Theories explain; laws describe (Stephen Toulmin 1967).12 Some of the most scientifically usefully social laws can be stated mathematically, as in these examples. Social laws also contain relevant entities, variables, and functional relations for describing social phenomena. A third source of abstraction consists of observations that can range from formal (e.g., ethnography, content analysis, automated information extraction, text mining, among others) to informal (historical narratives, media, and other sources about social phenomena). Observations of social phenomena can describe actors, their beliefs, social relations, and other features ranging from individual to collective. Finally, a fourth source of abstraction consists of computational algorithms capable of emulating social phenomena, as in artificial intelligence (AI). Artificial (i.e., not really human) algorithms do not claim to be causal in the same sense as social theories. They “work,” but without causal claims in the same sense as social theories. They are efficient, in the sense that they (sometimes) can closely replicate social phenomena. AI algorithms are typically (and intentionally) efficient and preferably simple; extreme parsimony in this case comes at the expense of realism. Examples of AI algorithms include Heatbugs (Swarm, NetLogo, MASON), Boids (Reynolds 1987), and Conway’s (1970) Game of Life. In spite of their lack of social realism, AI algorithms can be useful sources for abstracting social entities, ideas, or processes because they can highlight features that either elude theories or are hard to observe. An example would be the agglomeration patterns generated in a Heatbugs model, as a function of varying parameters of “social” interaction among the set of agents, or the role of apparent “leadership” in a flock of boids.

Abstract: I used data from the National Center for Health Statistics to map the geographic distribution of age-adjusted, race- and gender-specific stroke mortality rates in the United States from 1939-1941 to 1979-1981. Over this interval, stroke mortality rates declined dramatically with convergence of age-adjusted, state-specific stroke rates both within and between the various race-gender groups. For each race-gender group, high age-adjusted stroke mortality rates were significantly clustered in the southeastern United States, particularly in the South Atlantic census division, with persistent extreme rates in Georgia and the Carolinas. For whites, low-rate states were concentrated in the Mountain census division and along the northern Atlantic coast. The nonrandom distribution of stroke mortality across the United States, the large magnitude of the difference between high- and low-rate areas, the persistence of the pattern over more than four decades, the similarity of the distribution for different race-gender groups, the lack of delimitation by administrative or political boundaries, and results of national cooperative studies completed in the late 1960s and early 1970s together suggest that the pattern of excess stroke mortality is not an artifact of different diagnostic and reporting practices. Some of the observed geographic variation may be due to both the effects of selective migration and variations in the distributions of stroke risk factors.

Abstract: Multiple sclerosis (MS) prevalence rates were examined for the fiscal years 1984/1985–1988/1989, in the province of Alberta, Canada, by age, sex and census division. Data were derived from the health