II. Pedia Sapiens: A Planetary Progeny Comes to Her/His Own Actual Factual Knowledge

B. The Spiral of Science: Manican to American to Earthicana Phases

Silva, Filipi, et al. Using Network Science and Text Analytics to Produce Surveys in a Scientific Topic. arXiv:1506.05690. Posted on the same day as Gregely Palla above (1506.05661), University of Sao Paulo physicists, including Luciano da F. Costa, again attest to the presence of universal complex dynamics at work in this collaborative milieu.

Sinha, Pawan, et al. Autism as a Disorder of Prediction. Proceedings of the National Academy of Sciences. 111/15220, 2014. Eight neuroscientists from Boston and New Delhi contend that this multifaceted syndrome is in much part due to an inability to make sensible connections between object things or past to future events. As I was reading, it dawned that this condition could well characterize the state of natural science, such as physical cosmology and evolutionary theory. These male left brain pursuits seem unable to connect dots or even imagine any encompassing, independent spatial or temporal patterns and purpose. We seem to be an autistic planetary species consumed by violent conflict of all against all that seems incapable of any whole brain, feminine, emphatic vision.

A rich collection of empirical findings accumulated over the past three decades attests to the diversity of traits that constitute the autism phenotypes. It is unclear whether subsets of these traits share any underlying causality. This lack of a cohesive conceptualization of the disorder has complicated the search for broadly effective therapies, diagnostic markers, and neural/genetic correlates. In this paper, we describe how theoretical considerations and a review of empirical data lead to the hypothesis that some salient aspects of the autism phenotype may be manifestations of an underlying impairment in predictive abilities. With compromised prediction skills, an individual with autism inhabits a seemingly “magical” world wherein events occur unexpectedly and without cause. Immersion in such a capricious environment can prove overwhelming and compromise one’s ability to effectively interact with it. If validated, this hypothesis has the potential of providing unifying insights into multiple aspects of autism, with attendant benefits for improving diagnosis and therapy. (Abstract)

Sirocko, Franko, et al. The Climate of Past Interglacials. Amsterdam: Elsevier, 2007. The work is Volume 7 in the “Developments in Quaternary Science” series, a recent age defined as: “Of or belonging to the geologic time, system of rocks, or sedimentary deposits of the second period of the Cenozoic Era, from the end of the Tertiary Period through the present, characterized by the appearance and development of humans and including the Pleistocene and Holocene epochs.” We note this project by European geologists in wonderment as to what kind of universe evolves a collaborative sentient capacity able to reconstruct how it and we came into being and becoming.

Sivasundaram, Sujit. Introduction: Global Histories of Science. Isis. 101/1, 2010. A London School of Economics historian previews this special section of papers which attempt to survey of the various human endeavors to quantify and qualify a seemingly amenable and ever expanding natural creation. Scholars wax about Amerindian Narratives, Deep Histories, When Science Became Western, African Genealogies, Scientific Enchantments in India, and such topics in quest of a proper 21st century worldwide vision.

Soler, Lena. Are the Results of Our Science Contingent or Inevitable? Studies in History and Philosophy of Science. 39/2, 2008. A report on a symposium with this title, along with four papers. Such postmodern discourse views scientific theorizing as just another relative concoction, a 'social construction,' and seems unable to imagine there could and must be a greater discernible reality to interpret, not in an arbitrary way but as it truly is. Another current article which defends a 'rational' approach is "Are the Laws of Physics Inevitable?" by University of Colorado physicist Allan Franklin in the journal Physics in Perspective, 10/2, 2008.

Sommers, Hoff Christina, ed. The Science on Women and Science. Washington, DC: AEI Press, 2009. To first set a context, this work contains the proceedings of an American Enterprise Institute follow up conference to a 2007 National Academy of Sciences report Beyond Bias and Barriers. Fulfilling the Potential of Women in Academic Science and Engineering. It should then be noted that AEI is a totally male club. Their Board of Trustees sports 26 men, including the Honorable Richard B. Cheney, and no women (allowed). The Council of Academic Advisors runs at 10 to 1 (Gertrude Himmelfarb), while its “Research Staff” is 72 men and 3 women, one whom is philosopher editor Sommers. Typical papers are “Gender, Math, and Science” by Elizabeth Spelke and Katherine Ellison, “Women, Men, and the Sciences” by Jerry Levy and Doreen Kimura, and “Why So Few Women in Math and Science” by Simon Baron-Cohen.

The general surmise, which would conveniently please AEI, is that women are indeed deficient to men with regard to scientific and mathematical aptitudes and abilities. Now I personally have spent over four decades in real technical industry in laboratory, project, and managerial capacities and have never seen anything of the kind. In fact, women scientists and engineers are equal or superior to men. But the actual truth could be that women do have difficulties with the reigning male material machine paradigm in physics and technology because of its emphasis on particles or quanta alone, such as the sorry Large Hadron Collider. We hear so often lately “why did not anyone connect the dots?” For this is not what the left brain does, while the feminine mind, with a bicameral balance of both left and right, a key insight not much appreciated, is better at. (Which Levy and Kimura aver, but Baron-Cohen misses.)

Soos, Sandor, et al. Large-Scale Temporal Analysis of Computer and Information Science. European Physical Journal Special Topics. 222/6, 2013. In a special issue on “Advances in Dynamic Temporal Networks,” Sandor Soos, Hungarian Academy of Sciences, with George Kampis and Laszlo Gulyas, Eotvos Lorand University, Budapest, find these nonlinear topologies can serve to map and define collaborative research projects, now of team and worldwide expanse. With an earlier arXiv:1101.3684 post by Soos and Kampis “Bio-Inspired Methods for Dynamic Network Analysis in Science Mapping,” one might perceive, we add, a similarly evolving mindscape and sciencescape composed of bibliometric coupling, co-citation flow analysis, global paradigms, conceptual structures, and so on. The payoff is to realize that the same webwork geometries from proteins to cities of nodes, links, hubs, modules, and communities are found to equally hold for this cerebral knowledge realm.

The main aim of the project reported in this paper was twofold. One of the primary goals was to produce an extensive source of network data for bibliometric analyses of field dynamics in the case of Computer and Information Science. To this end, we rendered the raw material of the DBLP computer and infoscience bibliography into a comprehensive collection of dynamic network data, promptly available for further statistical analysis. The other goal was to demonstrate the value of our data source via its use in mapping Computer and Information Science (CIS). An analysis of the evolution of CIS was performed in terms of collaboration (co-authorship) network dynamics. Dynamic network analysis covered three quarters of the XX. century (76 years, from 1936 to date). Network evolution was described both at the macro- and the mezo level (in terms of community characteristics). Results show that the development of CIS followed what appears to be a universal pattern of growing into a “mature” discipline. (Abstract)

We apply bio-inspired methods for the analysis of different dynamic bibliometric networks (linking papers by citation, authors, and keywords, respectively). Biological species are clusters of individuals defined by widely different criteria and in the biological perspective it is natural to (1) use different categorizations on the same entities (2) to compare the different categorizations and to analyze the dissimilarities, especially as they change over time. We employ the same methodology to comparisons of bibliometric classifications. We constructed them as analogs of three species concepts: cladistic or lineage based, similarity based, and "biological species" (based on co-reproductive ability). We use the Rand and Jaccard indexes to compare classifications in different time intervals. The experiment is aimed to address the classic problem of science mapping, as to what extent the various techniques based on different bibliometric indicators, such as citations, keywords or authors are able to detect convergent structures in the litrerature, that is, to identify coherent specialities or research directions and their dynamics. (arXiv Abstract)

Stafford, Ned. Science in the Digital Age. Nature. 467/519, 2010. With the help of 2007 medicine Laureate Oliver Smithies, and historian Liu Dun of the Chinese Academy of Sciences, a broad review from ancient Asia to the sudden transition from paper journals to instant, available preprints on the Internet. From the days of “Xue-Fu-Wu-Che” for wandering scholars with carts of bamboo scrolls to the arXiv e-print archive, our worldwide vantage can now view humanity’s singular scientific project, now accelerating into this radical new mode, as if a global brain stirring and learning on her/his own.

Steffes, David. Panpsychic Organicism: Sewall Wright’s Philosophy for Understanding Complex Genetic Systems. Journal of the History of Biology. 40/2, 2007. With a neoDarwinian mechanical materialism as today’s victor, it is often forgotten that leading founders of the modern evolutionary synthesis such as Theodosius Dobzhansky (The Biology of Ultimate Concern), and Wright, were of a quite different opinion. A geneticist at the University of Chicago from 1925 to 1955, Sewall Wright (1889-1988) was much taken by a Romantic view (as actually was Darwin, see Robert Richards) of a self-organized, animate, multi-tiered nature, suffused with mind, more holistic than atomic, whereof interactions were as important as component parts. As this well-written article explains, Wright presciently anticipated a dynamical systems biology which portends an inclusive 21st century synthesis.

Sun, Xiaoling, et al. Social Dynamics of Science. Nature Scientific Reports. 3/1069, 2013. Of which this journal is a good example, Dalian University of Technology, China, and Indiana University, USA, information specialists contend that even science itself is arranged and moved by the animate self-organizing complex systems as everywhere else in nature. The same node and link, modular, community network topology and fluidity as a thinking, learning brain is thus found to equally distinguish collaborative, cumulative scientific progress. In this second decade of the 21st century, such thought and education is hemispherical and worldwide in scope, taking on the lineaments of a nascent global cerebration. As the quotes allude, these findings augur for the exemplary presence and operation of universally creative phenomena and forces springing from a self-existing, independence of any certain instance or field.

The birth and decline of disciplines are critical to science and society. How do scientific disciplines emerge? No quantitative model to date allows us to validate competing theories on the different roles of endogenous processes, such as social collaborations, and exogenous events, such as scientific discoveries. Here we propose an agent-based model in which the evolution of disciplines is guided mainly by social interactions among agents representing scientists. Disciplines emerge from splitting and merging of social communities in a collaboration network. We find that this social model can account for a number of stylized facts about the relationships between disciplines, scholars, and publications. These results provide strong quantitative support for the key role of social interactions in shaping the dynamics of science. (Abstract)

Other models focus on the synthesis of elements of preexisting disciplines, as in bioinformatics and quantum computing. All of these models point to the self-organizing development of science exhibiting growth and emergent behavior. No matter the cause or specific dynamics leading to the birth of a new discipline, such an event is reflected in the social community of scholars. New journals emerge, new collaborations are established, and new departments are created. Some theories emphasize the formation of social groups of scientists as the driving force behind the evolution of disciplines. Here we offer a first quantitative model to describe the various dynamics of discipline evolution independently of their underlying causes. We assume a purely social dynamics of science, without explicit references to exogenous events such as scientific discoveries, technological advances, and availability of new data or methods. In our model, agents represent scholars who choose their collaborators, while groups of collaborating scholars represent scientific disciplines. (1)

Tenachi, Wassim, et al. Deep symbolic regression for physics guided by units constraints: Toward the automated discovery of physical laws. arXiv:2303.03192. Into these 2020s as scientific collaborations from infinite, infinitesimal and viable complexity realms are engaged in an emergent passage to global endeavors which then begin to proceed on their own, University of Strasbourg and CISRO, Australia astrophysicists describe intelligent methods so to guide and empower this epic transition. In regard, this entry is an instance of the collective planatural intelligence as it rises to an Earthropic era. Its contents will then be composed of such subject articles.

Symbolic Regression is the study of algorithms that automate the search for analytic expressions to fit myriad results. While recent advances in deep learning have made progress, they have not been focused on physics data. Here we present Φ-SO, a Physical Symbolic Optimization framework for recovering analytical symbolic expressions using deep reinforcement learning techniques. Our system is built, from the ground up, to propose solutions where the physical units are consistent by construction. This algorithm can apply to noiseless data when attempting to derive an analytical property of a physical condition. (Excerpt)

Thessen, Anne, et al. From Reductionism to Reintegration. PLoS Biology. March, 2021. An interdisciplinary team from across the USA and onto Austraiia including Paul Bogdan introduce a current endeavor meant to achieve a “Reintegrative Biology,” The result will joins all manner of genes, organisms, variants, phenotypes, environments, along with informative software resources such as CyVerse: Open Science Workspace for Collaborative Data-driven Discovery. See also The Case for Research Integration, from Genomics to Remote Sensing, to Understand Biodiversity Change and Functional Dynamics in the World's Lakes by Stephen Thackeray and Stephanie Hampton in Global Change Biology (26/6, 2020) for approach to a scientific integrative synthesis.

Decades of reductionist approaches in biology have achieved spectacular progress, but the proliferation of subdisciplines, each with its own technical and social practices regarding data, impedes the growth of the multidisciplinary and interdisciplinary approaches now needed to address pressing societal challenges. Data integration is key to a reintegrated biology able to address global issues such as climate change, biodiversity loss, and sustainable ecosystem management. We identify major challenges to data integration and present a vision for a “Data as a Service”-oriented architecture to promote reuse of data for discovery. The proposed architecture includes standards development, new tools and services, and strategies for career-development and sustainability. (Abstract)

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