II. Pedia Sapiens: A Planetary Progeny Comes to Her/His Own Twintelligent Gaiable Knowledge

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

Grasswick, Heidi. Individuals-in-Communities: The Search for a Feminist Model of Epistemic Subjects. Hypatia. 19/3, 2004. As a response to the male, western emphasis of an “atomistic” view of knowing persons, feminist scholars have preferred to seek knowledge on a community scale (Nelson, Lynn. A Feminist Naturalized Philosophy of Science. Synthese. 17/3, 1995). Grasswick, philosophy chair at Middlebury College, seeks a complementary resolution via a dynamic reciprocity of distinct persons within a collectively learning society.

In short, the view of knowers as individuals-in-communities retains the idea that knowers are primarily individuals, yet rejects the generic and self-sufficient characteristics of the atomistic model, replacing them instead with the characteristics of situatedness and interactiveness. (99)

Gribben, John and Mary Gribben. Science: A History 1543-2001. London: Penguin Books, 2002. The story of how human inquiry proceeded out of the dark ages to explore and quantify a spherical planet within a vast, evolving universe. The book’s course runs from identifying the elements, especially carbon, hydrogen, oxygen and nitrogen, to plumbing galactic expanses, but in doing so the earth and human is seen to lose any special place or import.

Groenfeldt, D. The Future of Indigenous Values. Futures. 35/9, 2003. An essay on the importance that native animate, spiritual cosmologies survive in a perilous time when the Western rational/materialist dominance which denies any worldview of this kind.

Hakim, Joy. The Story of Science: Einstein Adds a New Dimension. Washington, DC: Smithsonian Books, 2007. The science writer and educator creates a sprightly written and vividly illustrated survey of the 20th century atomic, particle, quantum, and relativity physics revolution by way of the many personalities whom contributed to it. To inspire students it is averred that this quest and project goes on today as it may enter a novel phase of a communicative synthesis.

The understanding of information – the science of information theory – is evolving. John Wheeler explains, “I think of my lifetime in physics as divided into three periods. In the first period…I was in the grip of the idea that Everything is Particles…I call my second period Everything is Fields…Now I am in the grip of a new vision, that everything is Information." (430)

We started our scientific venture standing with Aristotle and Ptolemy on a giant Earth moored at the center of the world. Like royalty living in isolation in a huge castle, we were convinced we held the universe’s best real estate, although we didn’t have a clue as to what else was out there. Then along came Copernicus, Galileo, and Newton, and, in a surprising twist, as our vision expanded and our minds gained power, our place in the cosmos shrank. Now several hundred years after those giants walked this planet, science is telling us humans that we may actually be players in the universal drama. We may have a participatory role – and all because of a new science called information theory. (435)

Han, Barbara, et al. A synergistic future for AI and ecology.. PNAS Nexus. 120/38, 2023. Into the 2020s Cary Institute of Ecosystem Studies, Millbrook, NY, Lamont-Doherty Earth Observatory, Columbia University and U.S. Geological Survey (Jacob Zwart) suggest it is time for a novel confluence going forward between these fields since both have affinities to neural network forms and phenomena.

Research in both ecology and AI strives for predictive understanding of complex systems, where nonlinearities arise from entity interactions and feedbacks across multiple scales. After a century of advances in computational and ecological research, we foresee a need for intentional synergies to meet many societal challenges of global change. Persistent epistemic barriers would benefit from attention in both disciplines. The implications of a successful convergence go beyond advancing ecological disciplines or achieving an artificial general intelligence are critical for both persisting and thriving in an uncertain future. (Excerpt}

Harding, Sandra, ed. The Postcolonial Science and Technology Reader. Durham, NC: Duke University Press, 2011. A bandied phrase nowadays is “the West and the Rest.” As affirmed herein, of course the other continents have equally valid scientific and cultural traditions, which impoverished, imperiled, westerners could avail to their advantage. Four sections: Counterhistories, Other Cultures’ Sciences, Residues and Reinventions, and Moving Forward: Possible Pathways, proceed to so advise. A sample contribution might be “Mining Civilizational Knoweldge” by Susantha Goonatilake.

Hardwicke, Tom, et al. Calibrating the Scientific Ecosystem through Meta-Research. Annual Review of Statistics. 7/11, 2020. As a big data tsunami engulfs quantum to genomic to astromic fields, Meta-Research Innovation Center Berlin and Stanford University scholars scope out ways to reorient and empower methods that can distill evidential patterns and findings. See also in this volume 21st Century Statistical and Computational Challenges in Astrophysics by Eric Feigelson, et al.

Modern astronomy has been rapidly increasing our ability to see deeper into the universe as it acquires enormous samples of cosmic populations. Gaining astrophysical insights from these datasets requires a wide range of sophisticated statistical and machine learning methods. Bayesian inference, central to linking astronomical data to nonlinear astrophysical models, addresses problems in solar physics, properties of star clusters, and exoplanet systems. The field of astrostatistics needs increased collaboration and joint development of new methodologies. Together, they will draw more astrophysical insights into astronomical populations and the cosmos itself.

While some scientists study insects, molecules, brains, or clouds, other scientists study science itself. Meta-research, or research-on-research, is an active discipline that investigates efficiency, quality, and bias in the scientific ecosystem, which is under some attack today. We introduce a translational framework that involves (a) identifying problems, (b) investigating problems, (c) developing solutions, and (d) evaluating solutions. In each of these areas, we review key meta-research endeavors and discuss examples of prior and ongoing work. (Abstract excerpt)

Hasan, Farhanul, et al.. Filaments of The Slime Mold Cosmic Web and How They Affect Galaxy Evolution. arXiv:2311.01443. We note this entry by New Mexico State University, UC, Santa Cruz, Yale University, Hebrew University, and Simon Fraser University computational astrophysicists for its innovative application of a common organism-based search procedure as a good method to also study all manner of celestial phenomena, as the title cites and the quotes describe. Our planatural interest is a 21st century implication that a revolutionary ecosmic genesis seems to be amenable to the same genetic algorithms in each and every space and time.

We present a novel method for identifying cosmic web filaments by using the IllustrisTNG (below) galactic simulations. We compare the cosmic density field from the Delaunay Tessellation Field Estimator (DTFE) and Monte Carlo Physarum Machine (MCPM), which is inspired by the slime mold organism program which identifies filaments with higher fidelity reconstruction. Our results indicate that most galaxies are quenched and gas-poor near high-line density filaments at z<=1. We discuss applying our method to galaxy surveys. to elucidate the large-scale structure of galaxy formation. (Excerpt)

Galaxy evolution can be analyzed in the context of the universe’s large-scale structure, known as the ”cosmic web.” This structure consists of an interconnected network of filaments, which are bridges of intergalactic matter, and nodes, which are dense intersections of filaments where the cosmic density distribution is highest. In this paper, we present a new technique for reconstructing the cosmic web from galaxy catalogs. Our approach uses a novel model called the Monte Carlo Physarum Machine to estimate the cosmic density field. MCPM is inspired by the feeding habits of the biological organism Physarum polycephalum or slime mold, which generates highly efficient interconnected networks when searching for food. This behavior has been used in various fields from neuroscience to civil engineering. (1)

Perhaps even more exciting is that our new method can be applied to observational datasets to identify the cosmic web in the real universe. With rich datasets of from state-of-the-art current and upcoming observatories such as SDSS, DESI, Subaru PFS, JWST, Euclid, SPHEREx, and Roman, we will be in a position to identify filaments across most of cosmic time. This has the potential to unlock a rich array of investigations in research areas of extragalactic astrophysics and cosmology. (25)

The IllustrisTNG project is a series of cosmologica simulations of galaxy formation. TNG aims to illuminate the physical processes to understand when and how galaxies evolve into the structures that are observed in the night sky, and to make predictions for current and future observational programs.

Hayes, Brian. Undisciplined Science. American Scientist. July/August, 2004. Through the 18th century, physics reigned as the foundational science, of which aspects such as astronomy and botany were a particular kind. In the 19th and 20th centuries, separate subdisciplines proliferated into the hundreds. A grand 21st century reconvergence is underway because physics has come to characterize nature in terms of algorithmic computation because these generic statistical models apply equally well from atoms to societies to galaxies. Rather than a “postage stamp” collection, biological, cultural and celestial realms can be known as expressions of the same universal patterns and processes.

Heng, Kevin. The Nature of Scientific Proof in the Age of Simulations. American Scientist. May-June, 2014. The University of Bern, Center for Space and Habitability, Exoplanets and Exoclimes Group leader, describes the novel occurrence, after rationalism and empiricism, of a “third, modern way of testing and establishing scientific truth.” This is possible by the use of computational networks to mathematically simulate cosmoses, galaxies, planetary atmospheres, and so on. In such “synthetic universes” one can study, as not before, the formations of worlds from atomic to celestial realms. For a reference, visit the Millennium Simulation Project of the MPI for Astrophysics. And it is a sure sign of our revolutionary times when a professorship in planetary “habitability” exists.

Hey, Tony, et al, eds. The Fourth Paradigm: Data-Intensive Scientific Discovery. http://research.microsoft.com/en-us/collaboration/fourthparadigm, 2009. An e-book accessed on December 15, 2009 (re the New York Times Science Tuesday for that day) from Microsoft Research about computer capabilities that can process huge amounts of data from, e.g., the atom colliders, neuroscience, or multiple telescopes. An initial Experimental phase millennia ago is succeeded by Theoretical centuries since Newton, a Computational mode of the past years, and now this fourth Data Exploration or eScience faculty. A typical chapter might be “From Web 2.0 to the Global Database” by Timo Hannay or “Instrumenting the Earth: Next-Generation Sensor Networks and Environmental Science” by Michael Lehning, et al. But with its usual 10:1 men to women authors, the chapters highlight a “particle” emphasis as if via a left, half brain unable to imagine any abiding patterns or creation that the myriad pieces might fit together to reveal. To reflect, are we in fact seeing a radically new stage of human scientific inquiry, as if a worldwide cerebral faculty, beginning to think and learn on its own?

A good book review by physicist turned open source advocate Michael Neilsen appears in Nature (December 10, 2009), from which the next quote. On his blog can be found recent talks and thoughts that relate to his onw 2011 book Reinventing Discovery. But are we stuck in a mindset that there is nothing extant TO find? How might our worldwide mindkind, namely Mary and Charles Earthwin, finally both meld data and vision, part and whole, so as to realize a genesis universe?

Hundreds of projects in fields ranging from genomics to computational linguistics to astronomy demonstrate a major shift in the scale at which scientific data are taken, and in how they are processed, shared and communicated to the world. Most significantly, there is a shift in how researchers find meaning in data, with sophisticated algorithms and statistical techniques becoming part of the standard scientific toolkit. (722) The most interesting theme that emerges here is a vision of an increasingly linked web of information: all of the world's scientific knowledge as one big database. (722)

Heylighen, Francis and Katarina Petrovic. Foundations of ArtScience. Foundations of Science. 26/2, 2021. Free University of Brussels scholars (search FH) propose a frontier synthesis of these iconic cultural approaches, which as the Abstracts cites, could be attributed to our complementary brain hemispheres, each with a significant, vital contribution to make. This project is vital today as the two modes are far apart so that a male mechanistic, Ptolemaic physics rules, with any feminine sense of an organic image and message is excluded.

While art and science went on side-by-side during the Renaissance, their methods and perspectives parted leading to a long separation between the "two cultures". Recently, A collaboration between artists and scientists is promoted by the ArtScience movement to join the intuitive, imaginative ways of art and a rational, rule-governed science. Science and art are united in their creative investigation, where coherence, pattern and meaning play a vital role in the development of concepts. According to the standard view, science seeks an understanding that is universal, objective and unambiguous, while art focuses on unique, subjective and open-ended experiences. Both offer prospect and coherence, mystery and complexity, albeit with science preferring the former and art, the latter. (Abstract excerpt)

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