Behavioral science最新文献

Two expressive language structures have been identified mathematically in humans and chimpanzees. The first was found by measuring the waiting times between the invocation of new words or symbols, which consistently yielded individually characteristic rate constants and descending exponential curves that reflect a stochastically lawful Poisson process. The second was discovered by calculating the cumulative informational complexity (entropy) of word usage, which in all cases was a deterministically lawful logarithmic function of the number of words used to a given point in a communicative sequence. Individual and species differences in how this law is obeyed also characterized the sample. The results from the apes resembled those from the works of human poets like Shakespeare. The findings speak for deep, natural, unlearned expressive language structures in apes that are comparable to those seen in humans.

The dominant framework for Systems Design is seen to be problematic due to an underconceptualized definition of information. A more robust informational foundation is proposed. The Csanyi-Kampis notions of referential and nonreferential information are operationalized in terms of the informational aspects of Miller's living systems theory (LST). Following the work of Rosen, it is noted that a particular entailment ordering arises among the modeling relations of systems. This ordering renders the dominant approaches to systems design problematic. A new category of state-referential information is introduced in order to handle the entailment anomalies. The structure-process mappings in LST are seen as appropriate for preserving informational distinctions in living systems, and are proposed as a means of increasing the overlap between the ontological and epistemological bases of systems. Consequences for the theory and practice of social systems design are briefly discussed.

Conformity and independence in the large group may, in part, be due to collective phenomena analogous to those producing different physical phases like solid, liquid and vapor. This phase model of the large group explains several previous anecdotal observations: It predicts a suddenness in the decision-making, it explains the apparent contradiction between crowd suggestibility on the one hand and the difficulty of controlling a crowd on the other hand, and it provides a new rationalization for the phenomenon of splitting. The model is of use to both leaders and members of the large group. For example, it suggests what social parameters to change to disperse a violent crowd, and why “crowd crystals”, a concept examined by the writer Cannetti, can suddenly make the large group conform.

The nature of information is identified, and measures and measurement units for information are developed. There are five fundamental characteristics of information, which together comprise its nature: (1) it is an abstract concept, (2) it is weightless, (3) it does not occupy space, (4) it is observable only by the work it causes, and (5) it is transient and perishable.

Information is concisely defined as the ability to cause work. Because work can be measured, information can be measured by the work it causes. Neural information, in the form of electrochemical impulses, causes muscle tissue contraction which results in mechanical work. Biochemical information, in the form of enzymes, causes the biological work necessary to rearrange biochemical reactants (biochemical reactions). Genetic information, in the form of genes and codons, causes the work necessary to synthesize protoplasm.

Neural, biochemical, and genetic information can be measures by the work thry cause. These measures are equivalent to the extant measures of length, mass, time, temperature, charge, and energy. Units of measure are established for the three forms of information. These units are equivalent to the extant centimeter, gram, second, degree Centigrade, abcoulomb, erg, and calorie measurement units. An individual's behavior is observable by way of mechanical work in the form of muscle contractions, biochemical work in the form of biochemical reactions (metabolism), and work done in the synthesis of protoplasm. Measures of information and the information measurement units provide the basis for developing quantitative living systems and behavioral sciences that can join the community of quantitative hard sciences.

Like a powerful, hardly perceptible wall, the psychoanthropological barrier lies between the group formulations that characterize social psychology, sociology, and ethnology and the subjective reasoning that characterize individual modes of thought. More obviously, but equally as formidable, are the epistemological differences separating researchers within each of the scientific disciplines. As a consequence, humanities, behavioral sciences and biological sciences in general, and general systems in particular, lack the connectivity necessary for the broad unified approach that is prerequisite to applying multidisciplinary research to complex social, personal, ethnic, and gender problems. Eigen & Winkler's game theory optimization, together with recent developments in mathematics, microgenetics and ethnology, make it possible to integrate the social physics of Nicolas Rashevsky and the game theory formulations of Anatol Rapoport to produce Synchrony, a unified approach, which though not a seamless web, comes as close to a seamless web as is theoretically possible. But in accepting Synchrony, behavioral scientists must first learn to play GO, then adopt the concepts of dual cognition, dual time scales, self-reference, chance and necessity. Philosophers and ethnologists must deal with ecological “optimizations” of ethics and cultures. And, finally, as far as groups are concerned, all will have to give up permanent hierarchies, adopt a “feminine” mode of reasoning as optimal, then accept behavioral science's role of “Guardian of Time's Feminine Arrow”.

This article concerns the scientific value of the theory of autopoietic systems as developed by Maturana and Varela. In a first step, the explanatory power of the theory is investigated. It is argued that, due to the tautological nature of its core concept and the absence of the specification of the organization of the autopoietic system, the empirical counterparts of the theory's constructs cannot be determined. This renders the theory inadequate for descriptive and explanatory purposes. Proponents of autopoietic system theory do not agree with this kind of reasoning and its conclusion, since autopoietic systems, in their view, cannot be observed precisely because of its autopoietic nature. In a subsequent step, therefore, the epistemology advocated by Maturana and Varela on which this counter argument rests is discussed. It is shown that the interpretation of the ultrastable system, which underlies this epistemology, is not correct. Consequently, it is concluded that autopoietic system theory as developed by Maturana and Varela is unscientific.