arXiv subjects

Klaus Jaffe

Publications and source records attributed to Klaus Jaffe.

At least 19 recordsLinked to original sources

arXiv2021

Relation between Constitutions, Socioeconomics and The Rule of Law: a quantitative thermodynamic approach

Based on what we know about thermodynamics of synergy, we explored the relationship between countries socio-cultural order (negentropy), estimated through their constitutions, indicators of Rule of Law and their academic development; with countries indicators of Free Energy (amount of useful work, productivity, socioeconomic health). The analysis of 219 indicators unveiled strong correlations between estimates of the Rule of Law and the number of Academic Publications, with the socioeconomic health indicators: GDP, Human Development Index and Infant Mortality. In contrast, correlations with the length of constitutions (number of words and of articles), suggest that the proliferation of legal rules hinders the rule of law and socioeconomic development, or that under-development and/or the lack of the rule of law foments the proliferation of legal rules. These findings suggest that not any order favors productivity (Free Energy) and that excess regulations and state tutelage increase social entropy decreasing socioeconomic health.

physics.soc-ph↗

arXiv2018

A New Index of Human Capital to Predict Economic Growth

The accumulation of knowledge required to produce economic value is a process that often relates to nations economic growth. Such a relationship, however, is misleading when the proxy of such accumulation is the average years of education. In this paper, we show that the predictive power of this proxy started to dwindle in 1990 when nations schooling began to homogenized. We propose a metric of human capital that is less sensitive than average years of education and remains as a significant predictor of economic growth when tested with both cross-section data and panel data. We argue that future research on economic growth will discard educational variables based on quantity as predictor given the thresholds that these variables are reaching.

econ.EM↗

arXiv2017

The thermodynamic roots of synergy and its impact on society

Synergy arises from positive reciprocal complementary and synchronized feedback loops in a network of diverse actors that exchange information, energy and matter. Its effect is to increase in a non-linear way (greater than the sum of the parts) useful work (free energy) and order (decrease entropy) of the system After an extensive exploration of synergy and from the analysis of examples in many areas of science, including physics, biology and economy, I postulate that the common elements in all those examples are essential for the existence of synergy. These fundamental elements or roots of synergy are: 1. Open stable systems 2. Cohesion 3. Diversity and Assortation 4. Complementarity 5. Communication and Synchrony 6. Freedom and Self-Organization 7. Dynamics with decreasing entropy and growing free energy. This point may be considered essential in defining synergy, as it can be measured and thus, the proposal is falsifiable and might be refuted empirically. Here we explore ways to nurture synergy in different settings.

physics.soc-ph↗

arXiv2017

The Wealth of Nations: Complexity Science for an Interdisciplinary Approach in Economics

Classic economic science is reaching the limits of its explanatory powers. Complexity science uses an increasingly larger set of different methods to analyze physical, biological, cultural, social, and economic factors, providing a broader understanding of the socio-economic dynamics involved in the development of nations worldwide. The use of tools developed in the natural sciences, such as thermodynamics, evolutionary biology, and analysis of complex systems, help us to integrate aspects, formerly reserved to the social sciences, with the natural sciences. This integration reveals details of the synergistic mechanisms that drive the evolution of societies. By doing so, we increase the available alternatives for economic analysis and provide ways to increase the efficiency of decision-making mechanisms in complex social contexts. This interdisciplinary analysis seeks to deepen our understanding of why chronic poverty is still common, and how the emergence of prosperous technological societies can be made possible. This understanding should increase the chances of achieving a sustainable, harmonious and prosperous future for humanity. The analysis evidences that complex fundamental economic problems require multidisciplinary approaches and rigorous application of the scientific method if we want to advance significantly our understanding of them. The analysis reveals viable routes for the generation of wealth and the reduction of poverty, but also reveals huge gaps in our knowledge about the dynamics of our societies and about the means to guide social development towards a better future for all.

q-fin.GN↗

arXiv2017

Synergy from reproductive division of labor and genetic complexity drive the evolution of sex

Computer experiments that mirror the evolutionary dynamics of sexual and asexual organisms as they occur in nature, tested features proposed to explain the evolution of sexual recombination. Results show that this evolution is better described as a network of interactions between possible sexual forms, including diploidy, thelytoky, facultative sex, assortation, bisexuality, and division of labor between the sexes, rather than a simple transition from parthenogenesis to sexual recombination. Diploidy was shown to be fundamental for the evolution of sex; bisexual reproduction emerged only among anisogamic diploids with a synergistic division of reproductive labor; and facultative sex was more likely to evolve among haploids practicing assortative mating. Looking at the evolution of sex as a complex system through individual based simulations, explains better the diversity of sexual strategies known to exist in nature, compared to classical analytical models

q-bio.PE↗

arXiv2016

Simulating the interaction of road users: A glance to complexity of Venezuelan traffic

Automotive traffic is a classical example of a complex system, being the simplest case the homogeneous traffic where all vehicles are of the same kind, and using different means of transportation increases complexity due to different driving rules and interactions between each vehicle type. In particular, when motorcyclists drive in between the lanes of stopped or slow-moving vehicles. This later driving mode is a Venezuelan pervasive practice of mobilization that clearly jeopardizes road safety. We developed a minimalist agent-based model to analyze the interaction of road users with and without motorcyclists on the way. The presence of motorcyclists dwindles significantly the frequency of lane changes of motorists while increasing their frequency of acceleration-deceleration maneuvers, without significantly affecting their average speed. That is, motorcyclist "corralled" motorists in their lanes limiting their ability to maneuver and increasing their acceleration noise. Comparison of the simulations with real traffic videos shows good agreement between model and observation. The implications of these results regarding road safety concerns about the interaction between motorists and motorcyclists are discussed.

physics.soc-ph↗

arXiv2015

Emergence, self-organization and network efficiency in gigantic termite-nest-networks build using simple rules

Termites, like many social insects, build nests of complex architecture. These constructions have been proposed to optimize different structural features. Here we describe the nest network of the termite Nasutitermes ephratae, which is among the largest nest-network reported for termites and show that it optimizes diverse parameters defining the network architecture. The network structure avoids multiple crossing of galleries and minimizes the overlap of foraging territories. Thus, these termites are able to minimize the number of galleries they build, while maximizing the foraging area available at the nest mounds. We present a simple computer algorithm that reproduces the basics characteristics of this termite nest network, showing that simple rules can produce complex architectural designs efficiently.

nlin.AO↗

arXiv2015

Corruption and Wealth: Unveiling a national prosperity syndrome in Europe

Data mining revealed a cluster of economic, psychological, social and cultural indicators that in combination predicted corruption and wealth of European nations. This prosperity syndrome of self-reliant citizens, efficient division of labor, a sophisticated scientific community, and respect for the law, was clearly distinct from that of poor countries that had a diffuse relationship between high corruption perception, low GDP/capita, high social inequality, low scientific development, reliance on family and friends, and languages with many words for guilt. This suggests that there are many ways for a nation to be poor, but few ones to become rich, supporting the existence of synergistic interactions between the components in the prosperity syndrome favoring economic growth. No single feature was responsible for national prosperity. Focusing on synergies rather than on single features should improve our understanding of the transition from poverty and corruption to prosperity in European nations and elsewhere.

q-fin.GN↗

arXiv2015

Music Viewed by its Entropy Content: A Novel Window for Comparative Analysis

Polyphonic music files were analyzed using the set of symbols that produced the Minimal Entropy Description which we call the Fundamental Scale. This allowed us to create a novel space to represent music pieces by developing: a) a method to adjust a description from its original scale of observation to a general scale, b) the concept of higher order entropy as the entropy associated to the deviations of a frequency ranked symbol profile from a perfect Zipf profile. We called this diversity index the "2nd Order Entropy". Applying these methods to a variety of musical pieces showed how the space of "symbolic specific diversity-entropy" and that of "2nd order entropy" captures characteristics that are unique to each music type, style, composer and genre. Some clustering of these properties around each musical category is shown. This method allows to visualize a historic trajectory of academic music across this space, from medieval to contemporary academic music. We show that description of musical structures using entropy and symbolic diversity allows to characterize traditional and popular expressions of music. These classification techniques promise to be useful in other disciplines for pattern recognition and machine learning, for example.

cs.SD↗

arXiv2015

Calculating entropy at different scales among diverse communication systems

We evaluated the impact of changing the observation scale over the entropy measures for text descriptions. MIDI coded Music, computer code and two human natural languages were studied at the scale of characters, words, and at the Fundamental Scale resulting from adjusting the symbols length used to interpret each text-description until it produced minimum entropy. The results show that the Fundamental Scale method is comparable with the use of words when measuring entropy levels in written texts. However, this method can also be used in communication systems lacking words such as music. Measuring symbolic entropy at the fundamental scale allows to calculate quantitatively, relative levels of complexity for different communication systems. The results open novel vision on differences among the structure of the communication systems studied.

cs.IT↗

arXiv2015

Agent based simulations visualize Adam Smith's invisible hand by solving Friedrich Hayek's Economic Calculus

Inspired by Adam Smith and Friedrich Hayek, many economists have postulated the existence of invisible forces that drive economic markets. These market forces interact in complex ways making it difficult to visualize or understand the interactions in every detail. Here I show how these forces can transcend a zero-sum game and become a win-win business interaction, thanks to emergent social synergies triggered by division of labor. Computer simulations with the model Sociodynamica show here the detailed dynamics underlying this phenomenon in a simple virtual economy. In these simulations, independent agents act in an economy exploiting and trading two different goods in a heterogeneous environment. All and each of the various forces and individuals were tracked continuously, allowing to unveil a synergistic effect on economic output produced by the division of labor between agents. Running simulations in a homogeneous environment, for example, eliminated all benefits of division of labor. The simulations showed that the synergies unleashed by division of labor arise if: Economies work in a heterogeneous environment; agents engage in complementary activities whose optimization processes diverge; agents have means to synchronize their activities. This insight, although trivial if viewed a posteriori, improve our understanding of the source and nature of synergies in real economic markets and might render economic and natural sciences more consilient.

econ.GN↗

arXiv2015

Extended Inclusive Fitness Theory bridges Economics and Biology through a common understanding of Social Synergy

Inclusive Fitness Theory (IFT) was proposed half a century ago by W.D. Hamilton to explain the emergence and maintenance of cooperation between individuals that allows the existence of society. Contemporary evolutionary ecology identified several factors that increase inclusive fitness, in addition to kin-selection, such as assortation or homophily, and social synergies triggered by cooperation. Here we propose an Extend Inclusive Fitness Theory (EIFT) that includes in the fitness calculation all direct and indirect benefits an agent obtains by its own actions, and through interactions with kin and with genetically unrelated individuals. This formulation focuses on the sustainable cost/benefit threshold ratio of cooperation and on the probability of agents sharing mutually compatible memes or genes. This broader description of the nature of social dynamics allows to compare the evolution of cooperation among kin and non-kin, intra- and inter-specific cooperation, co-evolution, the emergence of symbioses, of social synergies, and the emergence of division of labor. EIFT promotes interdisciplinary cross fertilization of ideas by allowing to describe the role for division of labor in the emergence of social synergies, providing an integrated framework for the study of both, biological evolution of social behavior and economic market dynamics.

q-bio.PE↗

arXiv2015

Visualizing the Invisible Hand of Markets: Simulating complex dynamic economic interactions

In complex systems, many different parts interact in non-obvious ways. Traditional research focuses on a few or a single aspect of the problem so as to analyze it with the tools available. To get a better insight of phenomena that emerge from complex interactions, we need instruments that can analyze simultaneously complex interactions between many parts. Here, a simulator modeling different types of economies, is used to visualize complex quantitative aspects that affect economic dynamics. The main conclusions are: 1- Relatively simple economic settings produce complex non-linear dynamics and therefore linear regressions are often unsuitable to capture complex economic dynamics; 2- Flexible pricing of goods by individual agents according to their micro-environment increases the health and wealth of the society, but asymmetries in price sensitivity between buyers and sellers increase price inflation; 3- Prices for goods conferring risky long term benefits are not tracked efficiently by simple market forces. 4- Division of labor creates synergies that improve enormously the health and wealth of the society by increasing the efficiency of economic activity. 5- Stochastic modeling improves our understanding of real economies, and didactic games based on them might help policy makers and non specialists in grasping the complex dynamics underlying even simple economic settings.

cs.MA↗

arXiv2015

A Fundamental Scale of Descriptions for Analyzing Information Content of Communication Systems

The complexity of a system description is a function of the entropy of its symbolic description. Prior to computing the entropy of the system description, an observation scale has to be assumed. In natural language texts, typical scales are binary, characters, and words. However, considering languages as structures built around certain preconceived set of symbols, like words or characters, is only a presumption. This study depicts the notion of the Description Fundamental Scale as a set of symbols which serves to analyze the essence a language structure. The concept of Fundamental Scale is tested using English and MIDI music texts by means of an algorithm developed to search for a set of symbols, which minimizes the system observed entropy, and therefore best expresses the fundamental scale of the language employed. Test results show that it is possible to find the Fundamental Scale of some languages. The concept of Fundamental Scale, and the method for its determination, emerges as an interesting tool to facilitate the study of languages and complex systems.

cs.IT↗

arXiv2014

Social and Natural Sciences Differ in Their Research Strategies, Adapted to Work for Different Knowledge Landscapes

Do different fields of knowledge require different research strategies? A numerical model exploring different virtual knowledge landscapes, revealed two diverging optimal search strategies. Trend following is maximized when the popularity of new discoveries determine the number of individuals researching it. This strategy works best when many researchers explore few large areas of knowledge. In contrast, individuals or small groups of researchers are better in discovering small bits of information in dispersed knowledge landscapes. Bibliometric data of scientific publications showed a continuous bipolar distribution of these strategies, ranging from natural sciences, with highly cited publications in journals containing a large number of articles, to the social sciences, with rarely cited publications in many journals containing a small number of articles. The natural sciences seem to adapt their research strategies to landscapes with large concentrated knowledge clusters, whereas social sciences seem to have adapted to search in landscapes with many small isolated knowledge clusters. Similar bipolar distributions were obtained when comparing levels of insularity estimated by indicators of international collaboration and levels of country-self citations: researchers in academic areas with many journals such as social sciences, arts and humanities, were the most isolated, and that was true in different regions of the world. The work shows that quantitative measures estimating differences between academic disciplines improve our understanding of different research strategies, eventually helping interdisciplinary research and may be also help improve science policies worldwide.

physics.soc-ph↗

arXiv2014

On the biological and cultural evolution of shame: Using internet search tools to weight values in many cultures

Shame has clear biological roots and its precise form of expression affects social cohesion and cultural characteristics. Here we explore the relative importance between shame and guilt by using Google Translate to produce translation for the words shame, guilt, pain, embarrassment and fear to the 64 languages covered. We also explore the meanings of these concepts among the Yanomami, a horticulturist hunter-gatherer tribe in the Orinoquia. Results show that societies previously described as 'guilt societies' have more words for guilt than for shame, but the large majority, including the societies previously described as 'shame societies', have more words for shame than for guilt. Results are consistent with evolutionary models of shame which predict a wide scatter in the relative importance between guilt and shame, suggesting that cultural evolution of shame has continued the work of biological evolution, and that neither provides a strong adaptive advantage to either shame or guilt. We propose that the study of shame will improve our understanding of the interaction between biological and cultural evolution in the evolution of cognition and emotions.

cs.CY↗

arXiv2014

Quantifying literature quality using complexity criteria

We measured entropy and symbolic diversity for English and Spanish texts including literature Nobel laureates and other famous authors. Entropy, symbol diversity and symbol frequency profiles were compared for these four groups. We also built a scale sensitive to the quality of writing and evaluated its relationship with the Flesch's readability index for English and the Szigriszt's perspicuity index for Spanish. Results suggest a correlation between entropy and word diversity with quality of writing. Text genre also influences the resulting entropy and diversity of the text. Results suggest the plausibility of automated quality assessment of texts.

cs.CL↗

arXiv2013

Complexity measurement of natural and artificial languages

We compared entropy for texts written in natural languages (English, Spanish) and artificial languages (computer software) based on a simple expression for the entropy as a function of message length and specific word diversity. Code text written in artificial languages showed higher entropy than text of similar length expressed in natural languages. Spanish texts exhibit more symbolic diversity than English ones. Results showed that algorithms based on complexity measures differentiate artificial from natural languages, and that text analysis based on complexity measures allows the unveiling of important aspects of their nature. We propose specific expressions to examine entropy related aspects of tests and estimate the values of entropy, emergence, self-organization and complexity based on specific diversity and message length.

cs.CL↗