پلی بین مایعات و سیستم های اقتصادی - اجتماعی: نقش کلیدی نقاط قوت تعامل

One distinctive and pervasive aspect of social systems is the fact that they involve several kinds of agents. Thus, in order to draw parallels with physical systems one is led to consider binary (or multi-component) compounds. Recent views about the mixing of liquids in solutions gained from neutron and X-ray scattering show these systems to have a number of similarities with socio-economic systems. It appears that such phenomena as rearrangement of bonds in a solution, gas condensation, and selective evaporation of molecules can be transposed in a natural way to some socio-economic phenomena. These connections provide with a novel perspective for looking at social systems which we illustrate through examples. For instance, we interpret suicide as an escape phenomenon and in order to test this interpretation we consider social systems characterized by very low levels of social interaction. For these systems suicide rates are found to be 10 to 100 times higher than in the general population. Another interesting parallel concerns the phase transition that occurs when locusts gather together to form swarms which may contain several billion insects. What hinders the thorough investigation of such cases from the standpoint of collective phenomena that we advocate is the lack or inadequacy of statistical data; up to now socio-economic data were collected for completely different purposes. Most essential, for further progress, are the statistics which would permit to estimate the strength of social ties and interactions. Once adequate data become available, rapid advancement may be expected. At the end of the paper, we will discuss whether or not the ergodic principle applies to social systems.

Over the past decade econophysics and sociophysics have been developed by theoretical physicists mainly coming from statistical physics. Recent research in econophysics is comprised of a large body of empirical inquiries on topics which so far had been largely ignored by economists or sociologists. In addition, a number of theoretical tools developed in polymer physics, spin glass studies, Ising model simulations or discrete scaling were tentatively applied to problems in economics and sociology. This paper develops the idea that there is a connection between some of the phenomena studied in statistical physics and processes which occur in human societies. If persuasive, this argument would strongly support the claim (which is at the root of econophysics) made by physicists that the insight they have gained in studying physical systems can indeed be of value in the social sciences as well. Apart from this broad contention, our investigation will also tell us which phenomena are most likely to provide a good starting point for studying social systems in a fruitful way. In the course of this paper we will see that it is the liquid state which seems to provide the best bridge to social systems. This is easy to understand intuitively. Crystallized solids have a structure whose regularity and symmetries have no match in social systems. On the other hand, gases are characterized by a complete lack of structure which is at variance with the existence of social networks. With their non-trivial and adaptive intermolecular interactions, liquids and more specifically solutions offer a better analog to socio-economic systems. Glasses, that is to say solids without crystal structure, could also be possible candidates but in the present paper we restrict our attention to solutions. Subsequently we give other, more technical, arguments in favor of a parallel between solutions and social systems. Unfortunately, the liquid state is probably the less understood. It has been suspected for a long time (see for instance Moelwyn-Hughes, 1961) that the departure from ideal (or even regular) solution behavior is due to the formation of complex molecular assemblages even for non-ionic solutions. This was the central assumption on which Dolezalek's theory was based; however, it is only in recent decades that neutron and X-ray scattering as well as infrared spectroscopy provided a more accurate picture of such molecular clusters. The new picture which progressively emerged from these studies gave us an insight into microscopic mechanisms at molecular level. It is at this level that the parallel with social systems becomes natural. That is why, throughout this paper, we try to stick to molecular mechanisms and refrain from using such concepts as entropy, energy or temperature which become meaningful only at macroscopic level. So far, these concepts have no clear equivalent in social systems. At molecular level the only notions which make sense are those of distance and molecular attraction, stretching and vibrations, molecular assemblage, and so on. In the first part of this paper I describe some physical phenomena involving liquids in terms which can be easily transposed to social systems; in the second, I invite the reader to take the plunge and outline some social parallels. The paper proceeds as follows. In Section 2, I recall that the key variable which accounts for a whole range of phenomena as diverse as boiling temperature, vapor pressure, surface tension, or viscosity is the strength of the intermolecular interaction. This is particularly true in the liquid state. This observation is a strong incentive to develop methods for measuring the strength of social ties. Then I explain why viewing the mixing of two liquids merely as an irreversible operation, which increases disorder prevents us from seeing the major role played by amalgamating and combining, two mechanisms which play a key role in biological as well as social phenomena. In Section 4, I consider the phenomenon of suicide in situations where one has a good reason to expect a low level of social interaction and accordingly high suicide rates. Then I devote a few words to social or biological situations which are similar to gas condensation or solvation. Needless to say, each of these phenomena would deserve a more detailed study. Our objective in this paper is to draw a possible agenda for future research rather than to offer detailed case studies. Part I. Physical background Studying social phenomena is often frustrating because for each law or regularity that one tentatively tries to propose there are usually many exceptions and outliers. The situation is fairly similar in physical chemistry. No model has a broad validity and exceptions abound even for the most basic effects. In this sense physical chemists are certainly better prepared to cope with social systems than for instance particle physicists or solid state physicists. The background presentation in the first part is entirely based on experimental evidence. The discussions I have had with colleagues in my lab convinced me that even experienced theoretical physicists may not necessarily be familiar with these facts and their interpretations. However, this first part may be safely skipped by physical chemists. The next section about interaction strength offers a pedestrian, and a fairly self-contained approach. In the section about the structure of liquids we limit ourselves to giving a number of important references about salient features.1

Although I have not proposed any model (time is not yet ripe for this) I hope this paper will help us to see a number of socio-economic phenomena in a more unified and less anthropocentric way. The potential usefulness of the parallels developed in this paper is that it gives us the incentive to compare phenomena which at first sight seem to have little in common. In this concluding section I would firstly like to discuss the question of ergodicity, an important theoretical issue on which depends the applicability of statistical mechanics, and secondly to suggest an agenda for future research. 7.1. Does the ergodicity hypothesis hold for socio-economic systems? The success of statistical mechanics is entirely based on the fact that ensemble averages can be identified with time averages. On the theoretical side we compute the most probable configurations of the system on the basis of a collection of similar systems characterized by the same initial conditions and macroscopic constraints. A classical example is gas in a container in a state of equilibrium. Strictly speaking, the probability of finding all the molecules in one half of the container is not null, but it is overwhelmingly smaller than the probability of the situations where the molecules are uniformly distributed (except for small random fluctuations). The assumption that the time the system under observation spends in each macrostate is proportional to the probability of this state is of practical usefulness only if the system randomly explores all accessible microstates “quickly enough”. As we have seen, for molecules in a gas or in a liquid the typical duration of a given configuration is of the order of one picosecond which means that within the time it takes to make a measurement the system explores over 10121012 configurations. No matter how we define the configuration space, it is obvious that it will be explored much more slowly in the case of socio-economic systems. For instance, on stock markets, probably one of the economic systems with the highest transition rate, there is on average less than 10 transactions per second even for the most heavily traded stocks. For the other socio-economic systems the number of transitions may be smaller by several orders of magnitude. This has at least two consequences. (i) The time it may take for equilibrium to be reached may be large compared to the time scale of human observation. (ii) Consequently, there is a substantial probability of seeing the system in some metastable state rather than in its “true” equilibrium state. As a matter of fact, this problem is not specific to social systems; it also exists for some physical systems such as selenium, sulfur or tin which have different allotropic forms. For instance the transition from white tin to gray tin is supposed to occur at View the MathML source13∘C, but it may take centuries for a plate of white tin to decompose into gray tin even at temperatures as low as View the MathML source-18∘C ([44]http://www.natmus.dk). Most of the tools developed in statistical mechanics are not well suited to such systems. 7.2. Weak links, strong links Over the past decade, in the wake of the Internet revolution a vast literature has developed which is concerned with the structure of networks. However, its objectives and fields of applicability are altogether different from those considered in the present paper. Network theory is of relevance when there is a finite and well-defined set of links; this is often the case in cultural fields such as the network of cross-references in academic journals. On the contrary, the set of interactions of a given individual with the rest of society is neither countable nor well-defined. In such cases, trying to enumerate all links would lead nowhere. Consider the following example. Within a community, households interact indirectly with one another through the classmates their children have at school. Is this a weak or a strong link? In a sense it is weak because it is fairly indirect; however, we also know that it is strong enough to make families move to another area when for some reason the population of classmates becomes unsatisfactory. In order to test the strength of this kind of link one needs an operational definition; for instance, by measuring the relocation effects of a change in school population one would get a strength estimate. On this basis the link will be called a strong one, if a shift in school population makes many families move away. In physics one is in a very similar situation. All atoms have gravitational interactions with all other atoms in the universe. Yet, for many phenomena those gravitation networks are of no relevance. What really matters is the strength of a given set of interactions relative to other sets. Thus, the network of gravitational interactions becomes important only when no stronger fields (for instance due to electric forces) are present. In short, the geometry of a network and its strength are two very different issues. 7.3. An agenda for future research: gauging interaction strengths One may wonder whether the three manifestations of suicide that we examined can be accounted for by the same mechanism, in spite of the fact, that they correspond to very different time scales ranging from a few hours to several decades. To try to build a model at this point would probably be premature. If the model “explains” observed suicide rates in terms of social bonds that we cannot estimate in an independent way, this would be no more than a form of circular reasoning. This shows that one of our most urgent tasks is to develop methods for estimating the strength of social interaction. That this objective has so far been largely ignored by sociologists may seem surprising. How, for instance, is it possible to understand revolutions which basically consist in a rearrangement of social networks, if one has no real means for assessing the strength of social ties? What methods can we think of for that purpose? There are two very different approaches. The one which is favored by most sociologists (if one excepts a few outsiders such as Stanley Milgram) consists in listing and studying different channels of interactions: family ties, neighborhood links, institutional connections, etc. This approach could seem fairly natural because it appeals to our intuition. We already know how family ties work (or so we think). However, that approach will not lead us very far. The variety of links is just too vast. In physics, we encounter the same difficulty when we try to look into the details of the interactions between molecules (in addition, keep in mind that molecular assemblages change every picosecond). The physical methods for measuring the strength of molecular bonds suggest a completely different route. Whether we consider infrared spectroscopy, ultrasonic spectrography or X-ray/neutron scattering, these techniques are similar in their principle. A wave is sent through the medium and the ways in which it is affected are recorded and used to measure various characteristics of the medium. Through such measurements, one gets global estimates without having to worry about the minute details of the interactions. Infrared spectroscopy is slightly different from the two other techniques in the sense that it relies on the absorption which occurs when the frequency of the source coincides with the stretching or vibration modes of the molecular structure. So far, we do not know much about the eigenfrequencies (if any) of socio-economic systems which means that this technique does not provide a straightforward approach (at least for the time being). The two other techniques have broader applicability. For instance, in ultrasonic spectrography an ultrasonic wave is transmitted through the medium, its velocity and attenuation are recorded, and from these measurements one may derive many properties of the medium, for instance its density, the size of emulsion droplets or the existence of a temperature gradient. If one wants to extend this kind of approach to the social sciences there is a crucial requirement. In order to be able to use light or sound waves as probes, one must already know how these signals are affected by the physical characteristics of the medium. In other words, it is only once we have gained some kind of understanding (even if it is only an empirical understanding) of how a given signal is affected by a society, that we can use it as a probe. Once this condition is fulfilled, this probe will then become a useful tool for further explorations in a kind of cumulative process where any new knowledge about social interactions is used as a springboard for additional discoveries. There are many social signals which should enable us to transpose the previous approach to the social sciences. For instance, the way an epidemic propagates in a society can reveal a lot about the interactions that take place in a population. As an example, one can mention the fact that if two population groups show very different levels of prevalence for a sexually transmissible disease such as gonorrhea, chlamydia or HIV one can be almost sure that the two groups have little interactions through marriage or non-marital sexual contacts. Such assessments can be checked by confronting them against inter-marriage rates. Alternatively, they can replace such statistics in countries which, for some reason, do not record this kind of data. Naturally, this example concerns only one particular aspect of social interaction. One would have to develop similar approaches for other aspects as well. The transmission of rumors, innovations or new fashions can provide other possible probes. In this paper, I tried to convince the reader of the key role of interaction strength in social phenomena. I am convinced that once we get a clearer picture of this factor many socio-economic phenomena will become more transparent and to some extent more predictable.