Part of the artificial confusion of our worlds comes from erratic superimposition spontaneously equally weighted of many concepts, in fact diverse, heterogeneous, unmatching and variably scaled. That is plenty of "lessons" are just flattening everythings and applied the same way and level whatever the scales. Unconscious analogies are applied, without care, flattening and imposing perspectives, promoting unsuitable confusion and hyperinflation of soft laws not anchored neither well rooted. Even if some selfsimilarities apply and is need the wise ones are not done and scales are not really cared. To match experts' registers there is the need to look like better when levels and scales should be. With this flattenings the essential can be missed, and follow lacks of respect of ethical and simple values. But also to the contrary, such compressed views can be followed blindly non legitimate and absurdly biased predetermined interests. These artificial and unethical complications promote almost ystematically free riders carelessly damaging envrionments, societies profiteers and communities crooks, helped in their transgressions by the distorsion and twisting of moral issues. These simple overreductions can even have been made superior under sophisticated jargons.
In organized societies, paradigms rule and norms on much of what it presented as coherent, self-justifying the overdeterminism behaviors shown wrong. Paradigms have nevertheless contributed to some degrees of coherence, by the merits of normality and distortions, gobbled so just asking flexibility on the weakest or least tolerant to mistakes. Margins and variations in the ways we socially work may generate tolerable frustrations within acceptable limits since societies sustainabilities need to allow freedom to individuals; especially those with cautious behaviors as well as let space to expressions, investigations, innovations research and help trials. Recent developments of economics, using methods developed in evolution of ecological populations can help to simulate processes of growth or diffusion along which phenomena of scaling, diffusion and expansion. Observe for example, in evolutionary psychology that:
- Some aspects of species and sexual behaviors can be understood as adaptations to evolutive environments. According to Wright and Wrangham, there is likely an evolutionary explanation for both complex and basic behaviors, such as military behavior or, indeed, moral.
- Rather than supporting Galton’s distinction of a dichotomy between nature and nurture, evolutionary psychology refutes it. Instead, it appears that, while certain behaviors are inherited, their expression in interactions is highly dependent on environmental conditions. Thus, evolutionary psychology may help us understand under what environmental conditions behaviors are expressed and by whom (see point 4).
- Violence or promiscuity may be natural, but they may also be “globally maladaptive.” These are adaptations that facilitate individuals in passing on their genes while they also harm the species generally. The example both authors use is the canine teeth of male baboons. The longer and sharper the teeth, the more successful a male will be in mating but the more likely he is inflict serious wounds on females and other males in his group.
- Evolutionary psychology provides little insight into individual behavior or into differentiation between human groups. Only distinctions that have occurred within an evolutionarily significant timescale, such as between the sexes or between species, can be analyzed with the tools of the field.
- Finally, while these theories clearly have policy implications, it is too soon to draw any hard and fast conclusions. Despite its close relationship to the field of biology, evolutionary psychology is very much a social science similar to anthropology, psychology, or sociology. Adopting standards of proof from these fields, evolutionary psychology can greatly inform the policymaking process
Wright discussed the 3 criticisms of evolutionary psychology in turn:
- The field has low standards of evidence.
- The field’s hypotheses are “just-so” stories and are ultimately untestable.
- Stephen J. Gould has criticized evolutionary psychologists for being too quick to assign observed behaviors to adaptation when they may be byproducts of other processes or adaptations.
Nowadays these sophisticated methods alone, in social sciences models, are unrealistic even with the narrow part of the differential calculus they use. Neither these well developed and interesting corpus of concepts have prevented jargons of misinterpretations, poor in methods, as well as full of inconsistent facts, meanwhile they miss much of more serious sorts of essential information; on which, some frames of social issues, can apply. Consistency in the economics of information is highly required. The problem with homogeneity of discipline register being the shortcuts made with the essentiel knowledge: decisions are taken for decision not according an assessment of what could mean a project. Neither they are helpful for making a difference between what have been reached with good means and good work, hence helpless when results come from bad work and wrong doings, so often observed at the origins of so many inequalities. Also away from considering the production of wealth with naughty and unfair competition, there is anyhow the need to make decisions for the unlucky ones, on better grounds that those offerend by prepotent bureaucracies and shortsighted by narrowminded big firms methods.
Scales of Complexity as Landscapes in Heterogeneous Frames
"The interdisciplinary nature of complexity theory can be readily understood from the fact that complex systems exist in natural worlds (fluids, ecosystems, weather), social worlds (organizations, markets, societies) and artificial worlds (technologies, institutions, languages). How complexities, that hard to understand, measure, conceive, should be consider in projects managment ? We can well made a logical system of it and this may be a waste of time. Regarding the topic of technological innovation, two frames of reference are relevant: 1) Complexity can refer to complex interaction structures of components in a technological system, and 2) Complexity can refer to structure of interactions between agents in innovation networks. Complexity theory proves to be applicable in both domains". Observe all the simplifications that look like complex but pertaining to the domain of definition of simple things. They are plenty; receive some care from the organization of industrial paradigm (which technologically cannot be too irrational respect to its material flows. These work well if most behave the same way while managing their own range of complexity, thus not much in fixed models. Paradigms anyhow produce in the "remaining reality" more mistakes, biases and fallacies.
Complex systems adapt, but are nevertheless distorted and go on being distorted, up to an uncomprehensive complexity, often with unavoidable inertia to end of their time, as God's last sunset. After our (self) unit of maximum complexity; with sustainable perspective of management, be it biological as oneself, or one's family, or one's group ... the complex program: "the integration of both the collective and individual dimension in a similar framework the real challenge for cognitive economics. On computer simulated perspective ground. Actually, even if it is possible to model population dynamics with adaptive agents as with an "Agent based Computational Economics" (ACE) framework, the conceptual and formal integration of the 2 dimensions within a significant and coherent analytical framework need more development. If we want to keep a link between analytical and ACE modelling, the connection between the two dimensions needs much integration in simple cases; such as the reference and departure points. Without such a reference, ACE will be widely disconnected from a more standard approach. Such a disconnection is a possible issue for modelling economic problems, where ACE would be a complete substitute for an analytical approach. The strategy suggested is to keep the connection between these 2 approaches and to use ACE as a complement of the analytical one, in particular to investigate complex dynamics linked with both social interactions and belief revisions. Unfortunately, cognitive economy, which provides powerful models separately in an epistemic and an evolutionary perspective, failed, at this time, to provide an integrated analytic framework of reference (2003 adapted from Phan)".
To cope with scale and structural effects many registers have developed by side of probabilities methods and other formal methods; many tools for studying those kinds of effects exist too slowly diffuse out their respective register. This is of course menaingful in engineering of physics sciences, where fundamental effects apply accross different levels of scale. Only after gross empirical estimates to purify the essentiel values of core physical principles, where essential principles controled consistently help then to appreciate the correct effect of locallity. From these multiscaled effects also come the moder study of complex phenonema. To mention for exemple:
- Study of fundamental principles accross scales with methods of renormalization,
- Approximated calculus of structures approach by finite elements methods,
- New methods of signal study like using wavelets,
- Fractal for self-similar patterns oover different levels of scale, etc.
Social Sciences also use probabilities methods to apply structural methods to the construction of scales of their corpus of concepts but with the mistake to stay winthin those ones, since the assumption of purity of register enunciated in social sciences by Durkheim. When scientism was dangerously mixing and confusing arrogant believes that everything would be explained just confusing positivve arbitrary moral methods, interpretating complex issues oversimplifying categorical classifications derived from exact sciences to apply prejudgments as racism, eugenism and such speculative ones then Durkheim care was good. but now we need more deepness and like multidisciplinarian structural analysis. Structural analysis have started since some decades, for example probabilist structurel models have been created with compartments and hydraulics analogies. LISREL methods came to complete what started in econometrics concepts (explained and explained variables, endogenous-exogenous factors and so on.
Many such formal systems are like artificial neural networks, where basic structures contain hidden layer(s) of neurons. Complexity often be seen as black boxes or hidden layers. They are prone to effects unexpectedly emerging from hidden relations like phenomena called catastrophes in mathematics (bifurcations or nonlinear trajectories). Natural systems give many examples of these mechanisms. Naturally, “structure” and “function” are interconnected. But, even within complexity, the “structure” will not show all possible function(s) acting at any moment of time. Realist mathematical functions of the right sort would be so complicated that, at the same time you have succeeded in explaining all of them, your system will have gone (or be dead). Factoring out virtual positivist assumptions of rhetoric on pure mathematics: function in reality is not always fully explicit. This explains the need for shorter intermediate terms like of "use” and perhaps how the human's mind works. Any mind is selective and probably fluctuates over small sets of elementary values, it engages variably. Specific knowledge is recruited and can be organized partly according to similar rules. Cognitive processes are also constructions and humans do not have perfect, complete, invariable memories. Disposals have to do with details, approximations and slight differences. Olicognography, like cognitive processes, tries to help individual memory as well as collective management of knowledge restricting it only to "complexity at a glance", situations.
Open Mind, Work Hard, Care Around, Do not Miss the Basic
You may dispose some systemical rapid methods of assessment and maintain an ability to care about complexities. This can have much to do with the flexibility of methods, openess of mind, redesign of frames; including critical discriminating qualities which are essential to configuration(s) and changing skills to produce and implement efficiently mainframes adapted to situations. Sometimes it can be more efficient to wait and incorporate in the flows and cycles of activities or transformations; rather than force transformations too soon. Other situations can consist in implementing, with strength and great efforts then drive dynamically when having succeeded to move inertia. Plenty of managing strategies have been grounded on ideologies. The problem of ideology being with the difficulties to intent to redesign on supposedly better scientific grounds, out the normative strength of paradigms, or on reductive dynamics carried by private informal interests as well as non scientific ones.
Qualify complexities' management is not so easy. Since these are driven by determinism, many may pretend to be driven by care of complexity, while strongly reducing. So there, these ambitions, worth the lack of complex of "simple minded deciders", already well equiped with the dialectic to self-justify their criteria and make prevail their points. By side of studies on complex mechanisms, there are forms of strange or simulated weird phenomena and formal expressions of modern organization, may have qualified them to put them into programs of simplifications. Similarities and analogies are also tools coming at the rescue of simplified complexity. In fact, formalism in complex realities does not wait much at producing the required helpful model. Complex mechanisms are common in humans realities, may have not yet been detected as complex. Also there are plenty of sophisticated models mispecified but enough looking like observed complex behaviors.
Sort of frames that could theoretically help to design olicognograhic sort of formal modelling would observe:
- Basic level of differentiation of micro-meso-macrolevel (see for micro the basic physics thermodynamics transformations sort of thermoeconomics; for meso the standart economics unit of human being, may be not too idealized as the average human being, but a complex distribution with the non linear dynamics preserving its essentiel complexity and perturbations produced by anthropic transformations around; macro-level made of community - able to catch enough of its environmental complexity and including the sort of superior ethical frame of criteria and constraints as democratically accepted and applied to activities making the anthropic transformations ... this should appear more simple than here said),
- Extend systems of relations between levels in a way that can support some general solutions (so not too specific and to hard or too develop or too unspecified systems of calculus and that can receive the computer aided calculus),
- Find social robustness especially assuming locally democratic definitions of concepts, patterns of policies using less rigid pseudo-demonstrative rethoretic (but support reasoning and review of synthesis of genuine explanations),
- Promote essential knowledge, critical thinking respectful of humane common values, empathy and economics of information, so do not pretending to oversimplify in global speeches, just enough to act consistently with the values.
Sort of complexities simulations that could be manageable and controled like, via:
- Perturbations (shaking the circumstances for observing behaviors and adapt methods),
- Synchronizations (not to engaged transformations before having identified in the existing flows circumstances...
- ... Opportunate conditions that can help to compromise activities, programs),
- Strange attractors and processes patterns (say like cellular automata),
- Care the basics of essential maintenance of critical schemes making our existence,
- Combine different dynamics, keep openness, and so on.
- Keep essence of institutions but not preserved from free critics,
- Preserve means from non democratic misappropriations.
Care complexities also means putting emphasis on "evidence-based approaches. 3 pilars: 1) Systems thinking and complexity science, which orient us to looking at the whole and its relationship to the parts of an issue; 2) Participative methods, which recognise that all the stakeholders have a contribution to make in understanding and, often, decision making about an issue; and 3) Knowledge management, exchange and implementation, which involves appreciating that there are patterns of knowledge and ways of knowing (diverse epistemologies), providing enhanced methods for accessing knowledge realizing that both volume and diversity are current barriers, and involves developing better understanding of how action occurs".
So, out ideological balances; displacement of equilibria can be made in: planning, programming, commitment and opportunities. Planning can waste a lot if too extensive and poorly robust; but ordered transformations barelly happen without. Programming may look like well when abilities to set processes for catching opportunities or applying plans, caring the details of what seems possible to drive toward strategies and goals. Large scale of programming can waste plenty of energy, ressources or create scarcity when efforts are too dispersed, without sense of synergy, cooperation and common positive purpose. Opportunities if called so all what not have been well imagined neither planned or programmed, should nevertheless serve the transformations; not just individual interests. Others can have some good use to support positive results, factors enhancing results, prevent the development of advserse effects.