Social Science Computer Simulation: Its History, Design, and Future

Garson, G. David

doi:10.1177/089443939401200104

Cited by 7 publications

(2 citation statements)

References 35 publications

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“…For instance, the arrival and service of a complicated queuing network, such as a hospital emergency room, is easily described through simulation but very difficult to describe using direct probabilistic queuing theory, except under trivial assumptions (Kelton, Sadowski, & Sadowski, 1998). The use of simulation is less frequent in the social sciences but can still be useful (Garson, 1994).Q-methodology is an area of social research where we propose that simulation could be quite useful. In short, Q-methodology treats data from an individual as an entire vector, rather than doing an analysis of each item.…”

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Simulating Pearson’s and Spearman’s Correlations in Q-Sorts Using Excel

Alberts

Ankenmann²

2001

Social Science Computer Review

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A widely believed result about Q-sorts is shown by simulation; namely, that the hard-to-compute but statistically correct Spearman's ranked correlation, r s , may be substituted by the more common Pearson's r correlation. Recent versions of Microsoft Excel are excellent for reasonably sized simulations, especially those used in classroom settings.S imulation is commonly used in engineering and other situations as a manner of finding quick answers to mathematically challenging (and perhaps unsolvable) problems. For instance, the arrival and service of a complicated queuing network, such as a hospital emergency room, is easily described through simulation but very difficult to describe using direct probabilistic queuing theory, except under trivial assumptions (Kelton, Sadowski, & Sadowski, 1998). The use of simulation is less frequent in the social sciences but can still be useful (Garson, 1994).Q-methodology is an area of social research where we propose that simulation could be quite useful. In short, Q-methodology treats data from an individual as an entire vector, rather than doing an analysis of each item.A Q-sort is a common tool in Q-methodology and can also be used outside of the methodology. It is a questionnaire variant in which participants are asked to complete a pseudo ranking of the items. To compare to the traditional questionnaire, consider the instrument modeled here. Sixty-four items are rated on a 7-point scale. However, instead of having a free distribution, exactly five items must be placed in each extreme category, eight in the next, and so forth, creating a 5-8-12-14-12-8-5 fixed distribution when completed. Brown (1980) and Block (1979) give more detailed information on the technical aspects of Q-sorts.Two common ways of doing the vector analysis in Q-sorts are factor analysis and correlation. Correlation among subjects is the more simple and intuitive method of analysis. Pearson's r is the correlation taught in most introductory statistics courses, so most students are already aware of it; however, it is only appropriate for normal, continuous data. Spearman's rank correlation, r s , which performs a standard Pearson correlation on ranks of data, is recommended for ordinal data such as that found in Q-sorts (Gibbons, 1985). Pearson's r uses about one third the resources and is less complex than Spearman's r s , mak-

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Simulating Pearson’s and Spearman’s Correlations in Q-Sorts Using Excel

Alberts

Ankenmann²

2001

Social Science Computer Review

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Social Dilemmas: Individual, Collective, and Dynamic Perspectives

Liebrand

Messick²

1996

Frontiers in Social Dilemmas Research

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Digital Computer: Impact on the Social Sciences

Gigerenzer

2001

International Encyclopedia of the Social &Amp; Behavioral Sciences

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The invention of the computer has been described as the third information revolution-after the advent of writing and the printing press. Computers transformed our world, in reality and fi ction: from online library catalogues and the World Wide Web to the vision of machines that will eventually surpass humans in intelligence and even replace us by self-replicating computers divorced from biological evolution. This revolution was diffi cult to foretell. Howard Aiken, the Harvard mathematician and builder of the Mark I calculator, predicted in 1948 that there would be no commercial market for electronic computers; he estimated that the USA would need only fi ve or six such machines, but no more. As early as the 1960s, electrical engineer Douglas Carl Engelbart had designed the fi rst interactive computer tools, including the mouse, on-screen editing, screen windows, hypertext, and electronic mail. However, at this time, human-computer interaction still seemed science fi ction-computers were for processing punched cards, not for interacting with humans. The impact computers had on society and science was diffi cult to imagine, and we may be in the same position with respect to the future.The impact goes in both directions: computers and humans coevolve. This coevolution is illustrated by the work of Charles Babbage (1791-1871), the English mathematician who is often credited with the invention of the digital computer. The Computer as a Factory of WorkersBabbage's Analytical Engine, a mechanical computer, was inspired by and modeled on a new social organization of work: the large-scale division of labor, as evidenced in the English machinetool industry and in the French government's manufacturing of logarithmic and trigonometric tables for the new decimal system in the 1790s. Inspired by Adam Smith's praise of the division of labor, French engineer Prony organized the project in a hierarchy of tasks. At the top were a handful of fi rst-rank mathematicians, including Adrien Legendre and Lazare Carnot, who devised the formulae; in the middle, seven or eight persons trained in analysis; and at the bottom, 70 or 80 unskilled persons who performed millions of additions and subtractions.Once it was shown that elaborate calculations could be carried out by an assemblage of unskilled workers-rather than by a genius such as Gauss-each knowing very little about the larger computation, it became possible for Babbage to conceive of replacing these workers with machinery. Babbage, an enthusiastic "factory tourist," explicitly referred to this division of mental labor as the inspiration for his mechanical computer, and he used terms from the textile industry, such as "mill" and "store" to talk about its parts. Similarly, he borrowed the use of punched cards from the Jacquard loom, the programmable weaving machines that used removable cards to weave different patterns. Thus, in the beginning there was a new social system of work, and the computer was created in its image.

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Social Science Computer Simulation: Its History, Design, and Future

Cited by 7 publications

References 35 publications

Simulating Pearson’s and Spearman’s Correlations in Q-Sorts Using Excel

Simulating Pearson’s and Spearman’s Correlations in Q-Sorts Using Excel

Social Dilemmas: Individual, Collective, and Dynamic Perspectives

Digital Computer: Impact on the Social Sciences

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