Darwin had male chauvinism down to a science?

 Darwin: Why Women Are Inferior

Nancy Pearcy 

Editor’s note: We are delighted to present a preview adapted from Nancy Pearcey’s forthcoming book The Toxic War on Masculinity. The book will be published on June 27, but you can pre-order now!

Any list of toxic male behavior includes disrespect for women, and Darwin bears some responsibility for that as well. He was convinced that males are superior to females — that man attains “a higher eminence, in whatever he takes up, than can woman.” He concluded that “the average of mental power in man must be above that of woman.” 

Darwin explained male superiority by proposing that among social animals, young males have to pass through many contests to win a female — and many additional battles to retain their females. Over time, he said, natural selection will favor the stronger, more courageous males. Although modern men do not literally fight for a mate, he wrote,

yet they generally have to undergo, during manhood, a severe struggle in order to maintain themselves and their families; and this will tend to keep up or even increase their mental powers, and, as a consequence, the present inequality between the sexes. 

By contrast, Darwin wrote, women at home nurturing the young are out of reach of natural selection; thus they have evolved more slowly and their mental powers are lower. (It was assumed in his day that males pass on more of their traits to their sons, and females, to their daughters.) 

Darwin did acknowledge that women have “greater tenderness and less selfishness” than men, and even greater “powers of intuition, and rapid perception.” But he dismissed these traits as “characteristic of the lower races, and therefore of a past and lower state of civilization.” Even women’s positive traits were devalued as evidence of their inferiority. 

Darwin’s theory thus gave supposedly scientific authority to the idea that women are intellectually inferior to men — that women have no ideas or insights that warrant male respect. Women were pushed off their Victorian pedestal and relegated to a lower rung on the evolutionary ladder. 

In reality, of course, the survival of the human species depends just as much on characteristically female activities like giving birth and nurturing the young. Nevertheless, evolutionary thinkers preferred to exalt the more typically male activities like hunting and fighting as most important for the progress of the species. 

Beasts at Heart

Other evolutionary thinkers likewise promoted theories of male supremacy. The most influential popularizer of Darwinism in America was the sociologist Herbert Spencer, who argued that survival of the fittest weeds out all but the most aggressive men: 

In the course of the struggles for existence among wild tribes, those tribes survived in which the men were not only powerful and courageous, but aggressive, unscrupulous, intensely egoistic. Necessarily, then, the men of the conquering races which gave origin to the civilized races were men in whom the brutal characteristics were dominant. 

How could women survive in relationships with such brutal men? Spencer’s answer was that women needed to develop the “ability to please.” It would help if they also acquired “the powers of disguising their feelings” in order to hide the sense of “antagonism produced in them by ill treatment.”

The lesson of evolution, apparently, was that men are brutal beasts and that women must appease and placate them, while learning to hide their resentment of “ill treatment.” 

Many leading scientists of the day agreed with Darwin that women were less evolved than men. Anthropologist James McGrigor Allan held that “physically, mentally and morally, woman is a kind of adult child.” Thomas H. Huxley, whose fierce defense of Darwinism earned him the moniker Darwin’s Bulldog, said even education could not lift women to intellectual equality with men. Since women’s inferior abilities were a product of natural selection, he argued, they were not “likely to be removed by even the most skillfully conducted educational selection.” There was no hope, apparently, for women to escape their inferior position. 

The new York library a brief architectural history.

David Berlinski unsettles science.

 Iterations of Immortality

David Berlinski

Editor’s note: We are delighted to welcome Science After Babel, the latest book from mathematician and philosopher David Berlinski. This article is adapted from Chapter 7. 

The calculus and the rich body of mathematical analysis to which it gave rise made modern science possible, but it was the algorithm that made possible the modern world. They are utterly different, these ideas. The calculus serves the imperial vision of mathematical physics. It is a vision in which the real elements of the world are revealed to be its elementary constituents: particles, forces, fields, or even a strange fused combination of space and time. Written in the language of mathematics, a single set of fearfully compressed laws describes their secret nature. The universe that emerges from this description is alien, indifferent to human desires.

The great era of mathematical physics is now over. The three-hundred-year effort to represent the material world in mathematical terms has exhausted itself. The understanding that it was to provide is infinitely closer than it was when Isaac Newton wrote in the late 17th century, but it is still infinitely far away. 

One man ages as another is born, and if time drives one idea from the field, it does so by welcoming another. The algorithm has come to occupy a central place in our imagination. It is the second great scientific idea of the West. There is no third.

An algorithm is an effective procedure — a recipe, a computer program — a way of getting something done in a finite number of discrete steps. Classical mathematics contains algorithms for virtually every elementary operation. Over the course of centuries, the complex (and counterintuitive) operations of addition, multiplication, subtraction, and division have been subordinated to fixed routines. Arithmetic algorithms now exist in mechanical form; what was once an intellectual artifice has become an instrumental artifact.

Old as the Hills, and Cunning

The world the algorithm makes possible is retrograde in its nature to the world of mathematical physics. Its fundamental theoretical objects are symbols, and not muons, gluons, quarks, or space and time fused into a pliant knot. Algorithms are human artifacts. They belong to the world of memory and meaning, desire and design. The idea of an algorithm is as old as the dry humped hills, but it is also cunning, disguising itself in a thousand protean forms. It was only in this century that the concept of an algorithm was coaxed completely into consciousness. The work was undertaken more than sixty years ago by a quartet of brilliant mathematical logicians: Kurt Gödel, Alonzo Church, Emil Post, and A. M. Turing, whose lost eyes seem to roam anxiously over the second half of the 20th century.

If it is beauty that governs the mathematician’s soul, it is truth and certainty that remind him of his duty. At the end of the 19th century, mathematicians anxious about the foundations of their subject asked themselves why mathematics was true and whether it was certain, and to their alarm discovered that they could not say and did not know. Caught between mathematical crises and their various correctives, logicians were forced to organize a new world to rival the abstract, cunning, and continuous world of the physical sciences, their work transforming the familiar and intuitive but hopelessly unclear concept of the algorithm into one both formal and precise.

Unlike Andrew Wiles, who spent years searching for a proof of Fermat’s last theorem, the logicians did not set out to find the concept that they found. They were simply sensitive enough to see what they spotted. We still do not know why mathematics is true and whether it is certain. But we know what we do not know in an immeasurably richer way than we did. And learning this has been a remarkable achievement, among the greatest and least known of the modern era. 

Serene in the Cloudless Sky

Dawn kisses the continents one after the other, and as it does a series of coded communications hustles itself along the surface of the earth, relayed from point to point by fiber-optic cables, or bouncing in a triangle from the earth to synchronous satellites, serene in the cloudless sky, and back to earth again, the great global network of computers moving chunks of data at the speed of light: stock-market indices, currency prices, gold and silver futures, news of cotton crops, rumors of war, strange tales of sexual scandal, images of men in starched white shirts stabbing at keyboards with stubby fingers or looking upward at luminescent monitors, beads of perspiration on their tensed lips. E-mail flashes from server to server, the circle of affection or adultery closing in an electronic braid; there is good news in Lisbon and bad news in Saigon. There is data everywhere and information on every conceivable topic: the way raisins are made in the Sudan, the history of the late Sung dynasty, telephone numbers of dominatrices in Los Angeles, and pictures too. A man may be whipped, scourged, and scoured without ever leaving cyberspace; he may satisfy his curiosity or his appetites, read widely in French literature, decline verbs in Sanskrit, or scan an interlinear translation of the Iliad, discovering the Greek for “greave” or “grieve”; he may search out remedies for obscure diseases, make contact with covens in South Carolina, or exchange messages with people in chat groups who believe that Princess Diana was murdered on instructions tendered by the House of Windsor, the dark demented devious old Queen herself sending the order that sealed her fate.

All of this is very interesting and very new — indeed, interesting because new — but however much we may feel that our senses are brimming with the debris of data, the causal nexus that has made the modern world extends in a simple line from the idea of an algorithm, as logicians conceived it in the 1930s, directly to the ever-present always-moving now; and not since the framers of the American Constitution took seriously the idea that all men are created equal has an idea so transformed the material conditions of life, the expectations of the race. 

It is the algorithm that rules the world itself, insinuating itself into every device and every discussion or diagnosis, offering advice and making decisions, maintaining its presence in every transaction, carrying out dizzying computations, arming and then aiming cruise missiles, bringing the dinosaurs back to life on film, and, like blind Tiresias, foretelling the extinction of the universe either in a cosmic crunch or in one of those flaccid affairs in which after a long time things just peter out.

Our Fantastic and Artificial World

The algorithm has made the fantastic and artificial world that many of us now inhabit. It also seems to have made much of the natural world, at least that part of it that is alive. The fundamental act of biological creation, the most meaningful of moist mysteries among the great manifold of moist mysteries, is the construction of an organism from a single cell. Look at it backward so that things appear in reverse (I am giving you my own perspective): Viagra discarded, hair returned, skin tightened, that unfortunate marriage zipping backward, teeth uncapped, memories of a radiant young woman running through a field of lilacs, a bicycle with fat tires, skinned knees, Kool-Aid, and New Hampshire afternoons. But where memory fades in a glimpse of the noonday sun seen from a crib in winter, the biological drama only begins, for the rosy fat and cooing creature loitering at the beginning of the journey, whose existence I’m now inferring, the one improbably responding to kitchy kitchy coo, has come into the world as the result of a spectacular nine-month adventure, one beginning with a spot no larger than a pinhead and passing by means of repeated but controlled cellular divisions into an organism of rarified and intricately coordinated structures, these held together in systems, the systems in turn animated and controlled by a rich biochemical apparatus, the process of biological creation like no other seen anywhere in the universe, strange but disarmingly familiar, for when the details are stripped away, the revealed miracle seems cognate to miracles of a more familiar kind, as when something is read and understood.

Meaning in Molecules

Much of the schedule by which this spectacular nine-month construction is orchestrated lies resident in DNA — and “schedule” is the appropriate word, for while the outcome of the drama is a surprise, the offspring proving to resemble his maternal uncle and his great-aunt (red hair, prominent ears), the process itself proceeds inexorably from one state to the next, and processes of this sort, which are combinatorial (cells divide), finite (it comes to an end in the noble and lovely creature answering to my name), and discrete (cells are cells), would seem to be essentially algorithmic in nature, the algorithm now making and marking its advent within the very bowels of life itself.

DNA is a double helix — this everyone now knows, the image as familiar as Marilyn Monroe — two separate strands linked to one another by a succession of steps so that the molecule itself looks like an ordinary ladder seen under water, the strands themselves curved and waving. Information is stored on each strand by means of four bases — A, T, G, and C; these are by nature chemicals, but they function as symbols, the instruments by which a genetic message is conveyed.

A library is in place, one that stores information, and far away, where the organism itself carries on, one sees the purposes to which the information is put, an inaccessible algorithm ostensibly orchestrating the entire affair. Meaning is inscribed in molecules, and so there is something that reads and something that is read; but they are, those strings, richer by far than the richest of novels, for while Tolstoy’s Anna Karenina can only suggest the woman, her black hair swept into a chignon, the same message carrying the same meaning, when read by the right biochemical agencies, can bring the woman to vibrant and complaining life, reading now restored to its rightful place as a supreme act of creation.

The mechanism is simple, lucid, compelling, extraordinary. In transcription, the molecule faces outward to control the proteins. In replication, it is the internal structure of DNA that conveys secrets, not from one molecule to another but from the past into the future. At some point in the life of a cell, double-stranded DNA is cleaved, so that instead of a single ladder, two separate strands may be found waving gently, like seaweed, the bond between base pairs broken. As in the ancient stories in which human beings originally were hermaphroditic, each strand finds itself longingly incomplete, its bases unsatisfied because unbound. In time, bases attract chemical complements from the ambient broth in which they are floating, so that if a single strand of DNA contains first A and then C, chemical activity prompts a vagrant T to migrate to A, and ditto for G, which moves to C, so that ultimately the single strand acquires its full complementary base pairs. Where there was only one strand of DNA, there are now two. Naked but alive, the molecule carries on the work of humping and slithering its way into the future.

There, That Is What Intelligence Is

A general biological property, intelligence is exhibited in varying degrees by everything that lives, and it is intelligence that immerses living creatures in time, allowing the cat and the cockroach alike to peep into the future and remember the past. The lowly paramecium is intelligent, learning gradually to respond to electrical shocks, this quite without a brain let alone a nervous system. But like so many other psychological properties, intelligence remains elusive without an objective correlative, some public set of circumstances to which one can point with the intention of saying, There, that is what intelligence is or what intelligence is like.

The stony soil between mental and mathematical concepts is not usually thought efflorescent, but in the idea of an algorithm modern mathematics does offer an obliging witness to the very idea of intelligence. Like almost everything in mathematics, algorithms arise from an old wrinkled class of human artifacts, things so familiar in collective memory as to pass unnoticed. By now, the ideas elaborated by Gödel, Church, Turing, and Post have passed entirely into the body of mathematics, where themes and dreams and definitions are all immured, but the essential idea of an algorithm blazes forth from any digital computer, the unfolding of genius having passed inexorably from Gödel’s incompleteness theorem to Space Invaders VII rattling on an arcade Atari, a progression suggesting something both melancholy and exuberant about our culture.

The computer is a machine, and so belongs to the class of things in nature that do something; but the computer is also a device dividing itself into aspects, symbols set into software to the left, the hardware needed to read, store, and manipulate the software to the right. This division of labor is unique among man-made artifacts: it suggests the mind immersed within the brain, the soul within the body, the presence anywhere of spirit in matter. An algorithm is thus an ambidextrous artifact, residing at the heart of both artificial and human intelligence. Computer science and the computational theory of mind appeal to precisely the same garden of branching forks to explain what computers do or what men can do or what in the tide of time they have done.

A Combinatorial System

Molecular biology has revealed that whatever else it may be, a living creature is also a combinatorial system, its organization controlled by a strange, hidden, and obscure text, one written in a biochemical code. It is an algorithm that lies at the humming heart of life, ferrying information from one set of symbols (the nucleic acids) to another (the proteins).

The complexity of human artifacts, the things that human beings make, finds its explanation in human intelligence. The intelligence responsible for the construction of complex artifacts — watches, computers, military campaigns, federal budgets, this very essay — finds its explanation in biology. Yet however invigorating it is to see the algorithmic pattern appear and reappear, especially on the molecular biological level, it is important to remember, if only because it is so often forgotten, that in very large measure we have no idea how the pattern is amplified. Yet the explanation of complexity that biology affords is largely ceremonial. At the very heart of molecular biology, a great mystery is vividly in evidence, as those symbolic forms bring an organism into existence, control its morphology and development, and slip a copy of themselves into the future.

The transaction hides a process never seen among purely physical objects, one that is characteristic of the world where computers hum and human beings attend to one another. In that world intelligence is always relative to intelligence itself, systems of symbols gaining their point from having their point gained. This is not a paradox. It is simply the way things are. Two hundred years ago the French biologist Charles Bonnet asked for an account of the “mechanics which will preside over the formation of a brain, a heart, a lung, and so many other organs.” No account in terms of mechanics is yet available. Information passes from the genome to the organism. Something is given and something read; something ordered and something done. But just who is doing the reading and who is executing the orders, this remains unclear.

There is always another side to the story

What the science says about the case for Darwinism.

The tab has to be paid some at some point.

Fall of the three brains theory?

 Reptilian Brain Myth Is Still Alive and Kicking

Denyse o' Leary 

Do we have a three-part brain — reptilian, mammalian, and human? Curiously, psychology textbooks teach us that we do and neuroscience studies teach us that we don’t. Who to believe? And how did that happen anyway?

In the 1960s, Yale University physiologist and psychiatrist Paul D. MacLean (1913–2007) offered the triune brain theory. On that view, the reptilian brain (brain stem) controls things like movement and breathing; the mammalian brain controls emotion (limbic system); and the human cerebral cortex controls language and reasoning (neocortex). That might have been just another theory except that it was widely promoted by celebrity astronomer Carl Sagan (1934–1996) in his book The Dragons of Eden (Random House, 1977). Praised in The Atlantic as “a rational, elegant, and witty book,” Dragons won a Pulitzer Prize in 1978, for “a distinguished book of non-fiction by an American author that is not eligible for consideration in any other category.”

Chiming Beautifully

The theory chimed beautifully with materialist thought of the day. The cool people already assumed a long slow process of evolution from mud to mind, with stops along the way for reptile, mammal, and ape. And, as we were constantly reminded, many of us may have got stuck along the way.

But, as neuroscience advanced over the years, unwelcome facts began to surface. The human brain is just not organized as if the story happened in that way. As University of Oslo psychology professor Christian Krog Tamnes puts the matter in an interview at Science Norway, “Those of us who research brain development and brain evolution have known for quite some time that this isn’t true”:

Instead, the cells that are similar to each other were found scattered throughout the brains of both species.

Emotions, such as fear and sadness, are not made in one specific place in the brain. In fact, several parts of the brain are always involved.

Which parts of the brain are active vary from time to time, and from person to person.

For example, Tamnes points to a paper on the topic last year: Despite 320 million years of separate evolution, lizards and mice share a core set of neuron types that are found all over the brain, “including in the cerebral cortex, challenging the notion that certain brain regions are more ancient than others.”

Northeastern University neuroscientist Lisa Feldman Barrett offers, “So if we absolutely need to have a metaphor, it’s much better to think of the brain as an orchestra. Even playing a simple song requires a lot of pieces to talk together effectively and in a coordinated way.”

So we can still have lots of problems but our Inner Lizard is not one of them.

What Psychology Students Are Learning

Psychology lecture rooms and textbooks have been curiously slow to let go of the reptilian brain myth, however. Is that perhaps because it is socially reassuring to think that everyone who questions our sincerely held beliefs is, neurologically maybe, a rat or reptile throwback? In 2020, Joseph Cesario and colleagues reported on a study of what psychology students are told about such matters:

This belief, although widely shared and stated as fact in psychology textbooks, lacks any foundation in evolutionary biology.

“Our experience suggests that it may surprise many readers to learn that these ideas have long been discredited among people studying nervous-system evolution. Indeed, some variant of the above story is seen throughout introductory discussions of psychology and some subareas within the discipline… 

“To investigate the scope of the problem, we sampled 20 introductory psychology textbooks published between 2009 and 2017. Of the 14 that mention brain evolution, 86% contained at least one inaccuracy along the lines described above. Said differently, only 2 of the field’s current introductory textbooks describe brain evolution in a way that represents the consensus shared among comparative neurobiologists.”

CESARIO, J., JOHNSON, D. J., & EISTHEN, H. L. (2020). YOUR BRAIN IS NOT AN ONION WITH A TINY REPTILE INSIDE. CURRENT DIRECTIONS IN PSYCHOLOGICAL SCIENCE, 29(3), 255–260.

More information on the textbooks is offered here.

Puzzled by Sagan’s Role

Science writer and editor Ross Pomeroy seems genuinely puzzled by the role Sagan played in helping to popularize triune brain theory: “Carl Sagan was, and to this day is, generally regarded as an honest and skeptical broker of scientific information. That he presented such a disputed theory essentially as fact to the lay public is a bit surprising. What’s more, Carl Sagan continued to push the theory three years later in his far more widely read book, Cosmos.”

It’s not really so surprising if we look at the big picture. First, Sagan was a one-way skeptic. There were many things he was not skeptical about at all because they suited the popular worldview he shared and helped shape. 

For example, as Justin Gregg recounted in 2013, in 1961, he joined a semi-secret society called the Order of the Dolphin, which sought a way to communicate with intelligent extraterrestrials. He bought into the idea that dolphins had a sort of super-intelligence and a language like ours. The theory was that if we could decipher that language, we could decipher any extraterrestrial one. The Order was certainly dedicated. Gregg recounts, “As the Princeton historian D. Graham Burnett has noted, members wore insignia shaped like bottlenose dolphins and sent each other coded messages to hone their dolphinese and alien-language-decoding skills.”

Were They Nuts?

It might seem so at this distance. But club members back then included evolutionary biologist J. B. S. Haldane (1892–1964) and chemistry Nobelist Melvin Calvin — alongside SETI founder Frank Drake (1930–2022).

The lesson here is that science functions better when we follow the evidence, as the neuroscientists are doing, than when we form fan clubs for cozy ideas championed by science celebs, as the psychologists appear to be doing — at least in this area.

The extraterrestrials at home?

The porn/sex-trafficking axis.

Accurate timekeeping is always by design?

 Compasses, Clocks — Intelligent Design in Time

David Coppedge 

One can look at a piece of art or engineering and use the design filter to rule out chance or natural law. How much more is the design inference valid when seeing a sequence of events that work together for a purpose? If a sculpture appears designed, how much more a pendulum clock, or a symphony? Life is filled with dynamically changing, yet carefully regulated processes.

Hippos and Hedgehogs

Take the protein Sonic Hedgehog (SHH), whimsically named after a Japanese videogame character able to run at supersonic speeds, curl into a ball and attack enemies. Well known for its role in regulating embryonic development, SHH doesn’t just sit in the cell; it signals other proteins with the precision of a conductor. Patterns in the embryo, such as left-right symmetry and dorsal-ventral axis, are regulated by this important protein, coded for by the sonic hedgehog gene. Kim and Blackshaw, writing in Science, tell about a new function for this dynamic regulator that carries on throughout life.

Virtually all mammalian physiological functions fall under the control of an internal circadian rhythm, or body clock. This circadian rhythm is governed by master neural networks in the hypothalamus that synchronize the activity of peripheral clocks in cells throughout the body. Environmental perturbations that are a regular part of modern life, such as artificial light and international travel, can disrupt circadian rhythms, leading to adverse consequences for mental and physical health. On page 972 of this issue, Tu et al. report that primary cilia–mediated Sonic Hedgehog (SHH) signaling allows cells in the master circadian clock to maintain synchronization and control circadian rhythmicity in mice, identifying an unexpected functional role for this developmental regulator.

How can a tiny protein within a cell have dramatic effects on the hypothalamus, and by extension on the entire body? 

The master circadian pacemaker responsible for regulating our daily rhythms is located in the suprachiasmatic nucleus (SCN) in the anterior hypothalamus. The cells that make up this pacemaker maintain intercellular coupling of molecular circadian rhythms, ensuring synchrony of SCN neurons. Robust clocks keep time using redundant mechanisms, and the SCN is no exception. Signals that promote cellular synchrony include paracrine signaling by fast neurotransmitters and multiple neuropeptides as well as gap junction–dependent electrical coupling. This cellular synchrony ensures the robust output of the central clock and renders it resistant to signals that reset peripheral clocks.

At this point in the story, one of the superheroes of irreducible complexity enters: the cilium, described by Michael Behe in his books. Neurons in the SCN synchronize their clocks via SHH signals sent and received through their primary cilia. Those non-motile cilia then transmit the timing signals inside via the molecular trucks inside the cilia: the intraflagellar transport (IFT) trains. 

The master circadian pacemaker in the suprachiasmatic nucleus (SCN) contains neuromedin S–expressing (NMS+) neurons that have primary cilia. The number and length of these cilia change throughout the day, which alters Sonic Hedgehog (SHH) signaling through Smoothened (SMO) co-receptors expressed on the cilia. When this signaling is disrupted, the cellular oscillators in the SCN become uncoupled, which affects circadian rhythmicity in mice. 

Kim and Blackshaw call the discovery “surprising” for a protein that had been almost exclusively studied for its role in development. The new study by Tu et al. shows that adult organisms rely on SHH every day to keep the body clock running on time. That’s why they call it a “Super sonic circadian synchronizer.” 

SHH is essential for the development and specification of many brain structures during embryogenesis, including the SCN, and it also regulates axonal targeting, dendrite formation, and synaptogenesis. An ongoing role for SHH signaling in the adult SCN raises several important questions. It is unclear what cells are the relevant source of SHH or how its synthesis and release are regulated. Primary cilia regulate many other classes of extracellular signaling—such as Notch, Wnt, Hippo, and mammalian target of rapamycin (mTOR) pathways—often through receptor-independent mechanisms. Thus, it is unclear whether other extrinsic factors might contribute to controlling SCN function. 

The Hippo pathway, which regulates body size, also transmits its signals about body size through the cilium. Look at this diagram to get a taste of the dynamic signals going on in the cell for that symphony of signals. The cilium looks more irreducibly complex than ever!

Encompassing a Body Compass

Understanding how SHH interacts with day-night cycles can help solve the problem of jet lag. It takes a while to resynchronize our body clock to the time of day in another location when we zoom off to another time zone and find the sun angle at odds with expectations. Time for a reset!

Just as the body clock can be reset by external cues, our internal compass can be reset by an external cue: namely, head direction. Results of experiments at McGill University, also done on mice, shows how whole-body actions interact with signals inside of cells.

This ability to accurately decode the animal’s internal head direction allowed the researchers to explore how the Head-Direction cells, which make up the brain’s internal compass, support the brain’s ability to re-orient itself in changing surroundings. Specifically, the research team identified a phenomenon they term ‘network gain’ that allowed the brain’s internal compass to reorient after the mice were disoriented. “It’s as if the brain has a mechanism to implement a ‘reset button’ allowing for rapid reorientation of its internal compass in confusing situations,” says Ajabi.

Fast Clocks, Slow Clocks

Speaking of development, we know that different animals have different gestation times: humans take nine months, mice around 20 days. Yet all of us live under the same day-night cycle. How do these “heterochronies” regulate themselves? It comes down to the dynamic activities going on inside cells as well, says a Focus article in Science Advances. The author’s one mention of evolution contributes nothing to the science:

In evolutionary developmental biology, differences in genetically controlled temporal programs are well recognized and referred to as heterochronies. These include differences in the time of initiation, duration, or rate of a process in comparison with an organisms’ ancestors or other species. Whereas shifts in the time of initiation or duration have been linked to genetic variation of regulatory sequences or differential expression dynamics, other heterochronies that emerge from changes in the rate of a process are distinct and usually involve the same genetic program operating at different speeds. This has been termed allochrony and does not seem to be explained by variations in regulatory sequences (Fig. 1, A to C). However, less is known about the mechanisms driving allochronies.

Nothing in Figure 1 owes anything to Darwinian evolution. Audiences know intuitively that any delicate dance is the work of a choreographer.

Developmental processes need to operate in harmony to synchronize cells, tissues, organs, and the whole organism. It is increasingly clear that a central element of this delicate dance is achieved by each cell using its own clock…. Cells offer the most basic model to expose timing control processes and to investigate the intrinsic genetic mechanisms that control timing.

Teresa Rayon’s article goes on to discuss the harmony between biochemical reactions, motor neurons, mitochondrial activity, metabolic rate and epigenetic mechanisms. The differences in scale between these players working toward a common goal—homeostasis—is astonishing.

Clocks that Must Not Reset

The body adjusts for day and night cycles, but some body clocks dare not change outside of tight limits: heart rate and breathing. We have a “resting heart rate” during sleep that was thought to be under the sole control of the parasympathetic nervous system, the nerve network that relaxes us. Scientists at Manchester University found, however, that the “fight-or-flight” sympathetic nervous system (SNS) works in concert with it to keep the heart ticking within its acceptable range. Listen to this orchestra play:

Importantly, transcription factors in the sinus node lost rhythmicity following the sustained β-adrenergic blockade. Thus, the team proposed that day-night rhythms in the sinus node are orchestrated by rhythmic β-adrenergic input from the SNS to regulate ion channel gene expression. “It’s a way of thinking about the involvement of the autonomic nervous system, not as commonly accepted, which is these very short range, immediate acute modulations of ion channel function, but through long range modulation by affecting gene expression in the heart or in the sinus node,” said D’Souza.

Here again is a case of tight coordination between cell signals and a body composed of trillions of cells. Talk about the tail wagging the dog: the goings on in specific ion channels in a cell membrane can influence the brain and the heart that are orders of magnitude larger. Sleep tight; your body knows what parts have to slow down and what parts must keep going.

No Real Hope for Evolution

One study on biological clocks attempted to “Darwinize” them, but only for the very simplest case: the KaiA/B/C oscillator in cyanobacteria (see this video for a quick presentation of this clock). “The central role of circadian rhythms in many biological processes, controlled by the day and night cycle on Earth, makes their evolution a fascinating topic,” say eight evolutionists in an open-access paper in Nature. They attempt to show a stepwise evolution “From primordial clocks to circadian oscillators.” Good luck.

Circadian rhythms play an essential part in many biological processes, and only three prokaryotic proteins are required to constitute a true post-translational circadian oscillator. The evolutionary history of the three Kai proteins indicates that KaiC is the oldest member and a central component of the clock. Subsequent additionsof KaiB and KaiA regulate the phosphorylation state of KaiC for time synchronization. The canonical KaiABC system in cyanobacteria is well understood, but little is known about more ancient systems that only possess KaiBC…. Here we investigate the primordial circadian clock in Rhodobacter sphaeroides, which contains only KaiBC, to elucidate its inner workings despite missing KaiA. Using a combination of X-ray crystallography and cryogenic electron microscopy, we find a new dodecameric fold for KaiC, in which two hexamers are held together by a coiled-coil bundle of 12 helices. This interaction is formed by the carboxy-terminal extension of KaiC and serves as an ancient regulatory moiety that is later superseded by KaiA. A coiled-coil register shift between daytime and night-time conformations is connected to phosphorylation sites through a long-range allosteric network that spans over 140 Å. Our kinetic data identify the difference in the ATP-to-ADP ratio between day and night as the environmental cue that drives the clock. They also unravel mechanistic details that shed light on the evolution of self-sustained oscillators.

The authors build phylogenetic trees to argue that KaiC is more ancient than KaiA and KaiB. While admittedly rigorous, their work does not explain the origin of KaiBC itself, the gene that codes it, or its functional connection to diurnal cycle. KaiC, as shown in the video, is the largest and most complex protein in the clock with 518 amino acids arranged in a geometrically-elegant pair of hexamers that can undergo conformational changes essential for its operation. Its function is intimately tied to specific serine and threonine residues at precise locations.

At best, their evolutionary hypothesis shows a division of labor when KaiA is present. Oddly, the authors say that the KaiBC clock in R. sphaeroides “can perform both autophosphorylation and nucleotide exchange on its own and does so faster than its more recently evolved counterparts.” The paper leaves many unasked and unanswered questions. They offer no stepwise evolution from the simple prokaryotic clock to the “complex and highly sophisticated” circadian clocks in eukaryotes. There is no mention of mutations or natural selection. And a chicken-and-egg conundrum arises when asking which came first: the gene or the protein. Why would a gene sequence 518 aa long emerge by mistake without a function being known for it? That’s too improbable. If the protein came first and ticked like a clock, how did the code for it become embedded in the genome, which has a different alphabet? In the concluding discussion, the authors give an essentially magical explanation, calling the simplest of clocks “an example of convergent evolution.” If one did not already believe in the creative power of natural selection, this paper would prove little and make less sense.

In the arts, design is evident in both static and dynamic works. If paintings and sculptures evince design, much more do finely crafted instruments performing in harmony in real time. That’s ID in the 4th dimension.

The fall of the selfish gene?

 Cognitive Cells? A Newer Challenge to Neo-Darwinism

Denyse O Leary

In September 1957, Nobel Prize-winning biophysicist Francis Crick (1916–2004) announced the “Central Dogma” in biology, at a symposium at Oxford University. The dogma is currently given in the Biology Dictionary thus: “genetic information flows primarily from nucleic acids in the form of DNA and RNA to functional proteins during the process of gene expression.” This view that genes rule underpins mainstream assumptions about how traits are inherited; from there, it governs accepted assumptions about evolution. So the ground on which Darwin’s modern defenders stand, propounding the only true history of life, is narrow but it is firm.

Sir Francis Crick is perhaps better known to laypeople for his 1994 book, The Astonishing Hypothesis: The Scientific Search for Soul, which he opened by announcing

The Astonishing Hypothesis is that “You”, your joys and your sorrows, your memories and your ambitions, your sense of identity and free will, are in fact no more than the behaviour of a vast assembly of nerve cells and their associated molecules. As Lewis Carroll’s Alice might have phrased it: “You’re nothing but a pack of neurons.”

And the pack of mindless neurons that you think is you was created by those genes.

An Interesting New Paper

But what about the evidence that neurons self-organize? An interesting new paper in Progress in Biophysics and Molecular Biology calls for a different Central Dogma, recognizing forces other than genes:

Accumulating scientific discoveries support the need for a revised Central Dogma to buttress evolutionary biology’s still-fledgling migration from a Neodarwinian canon. A reformulated Central Dogma to meet contemporary biology is proposed: all biology is cognitive information processing.

The word “cognitive” is worth examining. According to Merriam–Webster, it means

of, relating to, being, or involving conscious intellectual activity (such as thinking, reasoning, or remembering)

or

based on or capable of being reduced to empirical factual knowledge.

Which definition do the authors, William B. Miller Jr. (UCLA), František Baluška (University of Bonn), and Arthur S. Reber (University of British Columbia), mean when they tell us that “As the internal measurement by cells of information is self-referential by definition, self-reference is biological self-organization, underpinning 21st century Cognition-Based Biology.” Do they mean that cells, in some sense, think?

Thoughtful Cells

They don’t quite say but the hints are intriguing. Darwin-shaped biology lags behind the times, they say, despite the accumulating contrary evidence that “non-random genetic mutations are common, linked to structural factors, epigenetic impacts, and biased DNA repair mechanisms,” among other things.

More directly, they write: “The crux of that difference separating Crick’s Central Dogma from a modern idiom is the contemporary recognition that cellular cognition governs the flow of biological information.”

So cells are smarter than we thought… ? They offer a brief look at the many bewilderingly complex feedback loops in typical cells. In their view, how should biology change? Here are some snippets from their Conclusion:

When biology is framed as an informational interactome, all forms of biological expression interact productively in a continuous, seamless feedback loop. In that reciprocating living cycle, there is no privileged level of causation since all aspects of the cell as an organized whole participate in cellular problem-solving

So the cell acts on itself (self-organization) instead of merely being acted upon by the neo-Darwinian genes. But also, they write,

The origin of self-referential cognition is unknown. Indeed, it can now be declared biology’s most profound enigma. Yet, that instantiation can be properly accredited as equating with the origin of life.

“Self-Referential Cognition”

In short, we have no idea how cells, which have been around for billions of years, could become so complex that they can be compared to intelligent beings (“self-referential cognition”) without any design in nature at all. Well, maybe they couldn’t have. Maybe the main thing to take away here, whether the authors intend it or not, is this: If biologists don’t want intelligent design, they will surely need to come up with something more convincing than Crick’s materialism.

Two other things are worth noting: Dogmas in science often do not age well because challenges are mounted by brilliant investigators but the dogma is defended by tenured mediocrities and — in the case of any type of Darwinism — pop science writers and education pressure groups. Even when the dogma is mouldy and rotten, it can be hard to overturn once it is embedded in the institutional culture on which their careers all depend.

Second, conundrums like this help us understand why panpsychism (all life forms/cells are conscious) is beginning to replace materialism in science.

Here’s the Problem

In a nutshell: The only really satisfactory form of materialism is eliminative materialism, meaning that minds are merely what brains do and human consciousness is simply an evolved illusion. You are indeed nothing but a pack of neurons. But if so, that very theory is an illusion like all the others.

In a world of awe-inspiringly complex life forms, it probably makes more sense for the materialist to adopt panpsychism. Thus words like “cognitive” and “self-referential” can be attached to cells without risk. I am not claiming that the authors are panpsychists, of course. My point is that their approach should be welcome to panpsychists.

Anyway, there is a definite nudge in that direction. University of Chicago biochemist James Shapiro titled a 2021 journal paper “All living cells are cognitive.” The same year, prominent neuroscientist Antonio Damasio, said in a book excerpt at The Scientist, that we cannot deny viruses “some fraction” of intelligence, based on the way their strategies resemble those of insects. Scientific American has run a number of pieces sympathetic to panpsychism over the years. New Scientist also offered a sympathetic long form discussion last year.

From a panpsychist perspective, human consciousness is not a mere illusion generated by a pack of neurons. It is the most highly developed known form of consciousness among life forms, all of which are conscious to some extent. That is, it is real in the same way that cell cognition and self-organization are real. So humans can learn about cells and propound theories about them that are not necessarily illusions but rather a meta level of consciousness.

Of course, panpsychism doesn’t do much to resolve the “profound enigma” of how such a world of life could come to exist without any intelligent intention or design. But that’s not what the materialist most needs right now anyway. He most needs to believe that his own findings are not just a user illusion. He can admit the profound enigma and leave the matter there.

More Rudyard Kipling style Just so stories from Darwinist.

 How Did Birds Get Their Wings? Bacteria May Provide a Clue to the Genomic Basis of Evolutionary Innovation, Say Evolutionists

Cornelius G Hunter 

That evolution occurred is known to be a fact but how evolution occurred is not known. In particular we are ignorant of how evolutionary innovations arose. Of course biological novelties and innovations arose from a series of random chance events, but it is less than reassuring that we cannot provide more detail. How exactly did the most complex designs spontaneously arise? What mechanisms overcame, over and over, the astronomical entropy barriers, by sheer luck of the draw? As Craig MacLean’s and Andreas Wagner’s, and coworker’s, new PLOS Genetics paper begins, “Novel traits play a key role in evolution, but their origins remain poorly understood.” Could it be that evolution is not actually a fact? No, not according to evolutionists. And this new paper claims to provide the basis for how the seemingly impossible became the mundane.

The paper begins by summarizing the many proposed genetic mechanisms for the evolution of biological innovations:

An evolutionary innovation is a new trait that allows organisms to exploit new ecological opportunities. Some popular examples of innovations include flight, flowers or tetrapod limbs [1,2]. Innovation has been proposed to arise through a wide variety of genetic mechanisms, including: domain shuffling [3], changes in regulation of gene expression [4], gene duplication and subsequent neofunctionalization [5,6], horizontal gene transfer [7,8] or gene fusion [9]. Although innovation is usually phenotypically conspicuous, the underlying genetic basis of innovation is often difficult to discern, because the genetic signature of evolutionary innovation erodes as populations and species diverge through time.

1. Mayr E. Animal Species and Evolution. Cambridge: MA: Harvard University Press; 1963.

2. Pigliucci M. What, if anything, is an evolutionary novelty? Philos Sci. 2008;75: 887–898. Available:http://philpapers.org/rec/PIGWIA

3. Patthy L. Genome evolution and the evolution of exon-shuffling—a review. Gene. 1999;238: 103–14. Available: http://www.ncbi.nlm.nih.gov/pubmed/10570989 pmid:10570989

4. True JR, Carroll SB. Gene co-option in physiological and morphological evolution. Annu Rev Cell Dev Biol. 2002;18: 53–80. doi: 10.1146/annurev.cellbio.18.020402.140619. pmid:12142278

5. Zhang J. Evolution by gene duplication: An update. Trends Ecol Evol. 2003;18: 292–298. doi: 10.1016/S0169-5347(03)00033-8.

6. Bergthorsson U, Andersson DI, Roth JR. Ohno’s dilemma: evolution of new genes under continuous selection. Proc Natl Acad Sci U S A. 2007;104: 17004–9. doi: 10.1073/pnas.0707158104. pmid:17942681

7. Boucher Y, Douady CJ, Papke RT, Walsh DA, Boudreau MER, Nesbø CL, et al. Lateral gene transfer and the origins of prokaryotic groups. Annu Rev Genet. 2003;37: 283–328. doi: 10.1146/annurev.genet.37.050503.084247. pmid:14616063

8. Wiedenbeck J, Cohan FM. Origins of bacterial diversity through horizontal genetic transfer and adaptation to new ecological niches. FEMS Microbiol Rev. 2011;35: 957–976. doi: 10.1111/j.1574-6976.2011.00292.x. pmid:21711367

9. Thomson TM, Lozano JJ, Loukili N, Carrió R, Serras F, Cormand B, et al. Fusion of the human gene for the polyubiquitination coeffector UEV1 with Kua, a newly identified gene. Genome Res. 2000;10: 1743–56. pmid:11076860 doi: 10.1101/gr.gr-1405r 

The unspoken problem here is, as usual, serendipity. The various proposed genetic mechanisms for the evolution of biological innovations all suggest an amazing bit of fortuitous luck. For random chance events just happened to create these various complicated structures and mechanisms (such as horizontal gene transfer and protein domains their shuffling) which then produced new evolutionary breakthroughs.

Evolution didn’t know what was coming. Evolution did not plan this out, it did not realize that horizontal gene transfer would lead the way to new biological worlds. The evolution of horizontal gene transfer would require a long sequence of random mutations, many of which would not provide any fitness advantage. And when the construction project was completed, and the first horizontal gene transfer capability was possible, there would be no immediate advantage.

This is because there would have been no genes to transfer. The mechanism works only when it is present in more than one, neighboring, cells. One cell gives, and another cells receives. By definition the mechanism involves multiple cells.

But it doesn’t stop there. Even if the first horizontal gene transfer capability was able to spread across a population, and even if it did provide a fitness advantage to the fortunate citizens, there would not be even a hint of the enormous world of biological innovations that had just been opened.

In other words, what this evolutionary narrative entails is monumental serendipity. Biological structures and mechanisms (horizontal gene transfer in this case, but it is the same story with the other hypotheses listed above) are supposed to have evolved as a consequence of a local, proximate, fitness advantage: a bacteria could now have a gene it didn’t have before.

But it just so happened that the new structures and mechanisms would also, as a free bonus, be just what was needed to produce all manner of biological innovations, far beyond assisting a lowly bacteria increase its fecundity.

This is monumental serendipity.

Undaunted, the new paper finds that one of the other mechanisms, gene duplication and subsequent neofunctionalization, is a key enabler and pathway to biological innovations.

That conclusion resulted from what otherwise was a fine piece of research work. The experimenters exposed different populations of Pseudomonas aeruginosa, a dangerous infectious bacteria, to 95 new sources of its favorite food: carbon.

The bacteria had to adjust to the new flavors of carbon and they did so with various genetic modifications, including various genetic mutations. In the most challenging cases (where the new carbon sources were most difficult for the bacteria to adjust to), the bacteria often produced mutations in genes involved in transcription and metabolism. And these mutations often occurred in genes where there were multiple copies, so the mutations occurred in one copy while the other copy could continue in its normal duties.

The problem is, these genetic duplicates were preexisting in the P. aeruginosa genome. This is yet another instance of serendipity.

Why? Because preexisting duplicates are not common. Only about 10% of the genes have duplicates lying around, and fortunately, the genes needed for adaptation (involving transcription and metabolism) just happened to have such duplicates.

Now there were a few instances of de novo gene duplication. That is, once the experiment began, and after the P. aeruginosa populations were exposed to the challenging diets, a total of six genes underwent duplication events. But in each and every case, the duplication events occurred repeatedly and independently, in different populations (for each of the 95 different carbon sources, the experimenters ran four parallel trials with independent populations).

This result indicates directed gene duplication. This is because it is highly unlikely that random, chance, gene duplication events just happened hit on the same gene in different populations. Here is an example calculation.

Let’s assume that in the course of the experiment, which ran for 30 days and about 140 generations of P. aeruginosa, some genes may undergo duplication events by chance. Next assume there is a particular gene that needs to be duplicated and modified in order to for P. aeruginosa to adapt to the new food source. (Note that there may be several such genes, but as we shall see that will not affect the conclusion). Given that there are four separate, independent trials, what is the probability that the gene will be duplicated in two or more of those trials?

Let P_dup be the probability that any gene is duplicated in the course of the experiment. For our gene of interest, it may be duplicated in 0, 1, 2, 3, or all 4 of the trials. The binomial distribution describes the probability, P, of each of these outcomes. To answer our question (i.e., What is the probability that the gene will be duplicated in two or more of those trials?) we sum the binomial distribution’s value for N = 2, 3 and 4. In other words, we calculate P(2) + P(3) + P(4).

This will give us the probability of observing what was observed in the experiment (i.e., the duplication events occurred repeatedly and independently, in different populations, in all 6 cases where duplication events were observed).

Well for a reasonable value of P_dup, the probability that any gene is duplicated in the course of the experiment, such as 0.0001, the probability of observing multiple duplications events for any given food source (i.e., P(2) + P(3) + P(4)) is about 60 in one billion, or 6 times 10^-8. Even worse, the probability of observing this in all 6 cases where duplication events were observed is about 5 times 10^-44.

It isn’t going to happen.

Exceptionally high rates of gene duplication, in particular genomic regions of Salmonella typhimurium, in a high growth rate medium, were observed to be about 0.001 and even slightly above 0.01 in rare cases.

If we go all out and set P_dup to an unrealistically high 0.1, our results are still unlikely. The P(2) + P(3) + P(4)) is .05, and the probability of observing this in all 6 cases where duplication events were observed is about 2 times 10^-8.

In order to raise these probabilities to reasonable levels, such that what was observed in the experiment is actually likely to have occurred, we need to raise P_dup to much higher values. For example, for a P_dup of .67 (two-thirds probability), P(2) + P(3) + P(4)) is .89, and the probability of observing this in all 6 cases where duplication events were observed is about .5.

But even this doesn’t work. For if we were to imagine unrealistically high P_dup values of 0.1 or higher, then massive numbers of duplication events would have been observed in the experiments.

But they weren’t.

Once again, the science contradicts the theory. Our a priori assumption that evolution is a fact, and that the P. aeruginosa adaptations to the new food sources were driven by random mutations, did not work. The theory led to astronomically low probabilities of the observed results.

What the observed gene duplications are consistent with is directed gene duplications. Just as mutations have been found to be directed in cases of environmental challenges, it appears that gene duplications may also be directed.

The paper’s premise, that biological innovations such as flowers and wings are analogous to bacteria adapting to new nutrient sources, is fallacious. But setting that aside, the experimental results do not make sense on evolution’s mechanism of random mutations and natural selection. Instead, the results indicate directed adaptation.

Isaiah chapter 44 Legacy Standard Bible

 

Isaiah 44

“But now hear, O Jacob, My servant,

And Israel, whom I have chosen:

2 

Thus says Yahweh who made you

And formed you from the womb, who will help you,

‘Do not fear, O Jacob My servant,

And you Jeshurun whom I have chosen.

3 

For I will pour out water on the thirsty ground

And streams on the dry land;

I will pour out My Spirit on your seed

And My blessing on your offspring;

4 

And they will spring up among the grass

Like poplars by streams of water.’

5 

This one will say, ‘I am Yahweh’s’;

And this one will call on the name of Jacob;

And this one will write on his hand, ‘Belonging to Yahweh,’

And will name Israel’s name with honor.

6 

“Thus says Yahweh, the King of Israel and his Redeemer, Yahweh of hosts:

‘I am the first, and I am the last,

And there is no God besides Me.

7 

Who is like Me? Let him call out and declare it;

And let him tell it to Me in order,

From the time that I established the ancient people.

And let them declare to them the things that are to come

And the events that are going to take place.

8 

Do not be in dread and do not be afraid;

Have I not long since caused it to be heard to you and declared it?

And you are My witnesses.

Is there any God besides Me,

Or is there any other Rock?

I know of none.’”

9 

Those who form a graven image are all of them futile, and their desirable things are of no profit; even their own witnesses fail to see or know, so that they will be put to shame.

10 

Who has formed a god or cast a graven image to no profit?

11 

Behold, all his companions will be put to shame. The craftsmen themselves are mere men. Let them all assemble themselves, let them stand up, let them be in dread, let them together be put to shame.

12 

The man crafts iron into a cutting tool and does his work over the coals, forming it with hammers and working it with his powerful arm. He also gets hungry and has no power; he drinks no water and becomes weary.

13 

Another crafts wood, he extends a measuring line; he outlines it with a stylus. He makes it with planes and outlines it with a compass and makes it like the form of a man, like the glory of man, so that it may sit in a house.

14 

In order to cut cedars for himself, he takes a cypress or an oak and raises it for himself among the trees of the forest. He plants a fir, and the rain makes it grow.

15 

Then it becomes something for a man to burn, so he takes one of them and warms himself; he also kindles a fire to bake bread. He also works to produce a god and worships it; he makes it a graven image and falls down before it.

16 

Half of it he burns in the fire; over this half he eats meat as he roasts a roast and is satisfied. He also warms himself and says, “Aha! I am warm; I have seen the fire.”

17 

But the rest of it he makes into a god, his graven image. He falls down before it and worships; he also prays to it and says, “Deliver me, for you are my god.”

18 

They do not know, nor do they understand, for He has smeared over their eyes so that they cannot see and their hearts so that they will have no insight.

19 

No one causes this to return to his heart, nor is there knowledge or understanding to say, “I have burned half of it in the fire and also have baked bread over its coals. I roast meat and eat it. Then I make the rest of it into an abomination; I fall down before a block of wood!”

20 

He feeds on ashes; a deceived heart has turned him aside. And he cannot deliver his soul, and he cannot say, “Is there not a lie in my right hand?”

YAHWEH FORGIVES AND REDEEMS

21 

“Remember these things, O Jacob,

And Israel, for you are My servant;

I have formed you, you are My servant;

O Israel, you will not be forgotten by Me.

22 

I have wiped out your transgressions like a thick cloud

And your sins like a cloud.

Return to Me, for I have redeemed you.”

23 

Shout for joy, O heavens, for Yahweh has done it!

Make a loud shout, you lower parts of the earth;

Break forth into a shout of joy, you mountains,

O forest, and every tree in it;

For Yahweh has redeemed Jacob

And in Israel He shows forth His beautiful glory.

24 

Thus says Yahweh, your Redeemer, and the one who formed you from the womb,

“I, Yahweh, am the maker of all things,

Stretching out the heavens by Myself

And spreading out the earth all alone,

25 

Causing the omens of boasters to be annulled,

And making fools out of diviners,

Causing wise men to turn back,

And making foolishness out of their knowledge,

26 

Confirming the word of His servant⁠—

And the counsel of His messengers He will complete⁠—

And being the One who says of Jerusalem, ‘She shall be inhabited!’

And of the cities of Judah, ‘They shall be built.’

And I will raise up her waste places again.

27 

It is I who says to the depth of the sea, ‘Be dried up!’

And I will make your rivers dry.

28 

It is I who says of Cyrus, ‘He is My shepherd!

And all My good pleasure he will complete.’

And saying of Jerusalem, ‘She will be built,’

And of the temple, ‘Your foundation will be laid.’”

The highest tech of all

 Listen: Carbon Valley Trumps Silicon Valley

Evolution News

Got a smartphone? As complicated a machine as it is, it doesn’t compare to the incredible sophistication found in biology. On a classic episode of ID the Future, we hear from two contributors to the Crossway Anthology, Theistic Evolution: A Scientific, Philosophical, and Theological Critique, molecular biologist Douglas Axe and philosopher of science Stephen Meyer. They explain how Carbon Valley trumps Silicon Valley, and shouts intelligent design. They compare some of today’s technological marvels to living technology, and show how even “simple cells” far exceed the best that Silicon Valley has to offer. As Meyer says: “Nobody doubts that natural selection and random mutation is a genuine biological process. What we do doubt is that those mechanisms have the power to generate fundamentally new forms of life.” Download the podcast or listen to it Here

Hired guns?

An architectural tour of the new Rome.

When the science is untrustworthy?

 Fossil Friday: The Gupta Scandal

Gunta Bechly 

This Fossil Friday features conodont microfossils from the Triassic of the Himalaya region in India (Goel 1977) to illustrate a veritable crime story. You may have heard of cases of fraud in paleontology such as the famous hoaxes of Piltdown Man and Archaeoraptor, but the greatest scientific fraud of the century is not so well known outside of professional paleontologist circles. It was Indian scientist Vishwa Jit Gupta, professor of geology at Panjab University, who played the “star role” in this biggest case of fraud in paleontology and maybe all of science ever (Lewin 1989).

A Dubious Accident

Gupta was India’s most celebrated paleontologist, with 455 scientific publications (including two Nature papers and five books), when the scandal started to come to light in 1989 (Talent 1989, Lewin 1989, Anderson 1991, Nature 1993), but it took nine years for the total truth and magnitude of the scandal to be revealed (Ruffell et al. 2012, Webster 2016). It turned out that over 30 years of research with 126 gullible co-authors, Gupta had falsified data, stolen fossils from colleagues and collections around the world, and then claimed to have found them in the Himalayas, often in made-up localities and layers. Gupta’s “fraudulent practices have involved most invertebrate phyla as well as the vertebrates and include fossils of Cambrian to Cenozoic age” (Webster et al. 1993). Gupta did not only commit scientific fraud on an unprecedented scale, but he even issued death threats with head money to whistleblowers including Australian geologist John Talent, one of whom one was actually killed in a dubious accident (Carleton 2005, Ruffell et al. 2012). After a final report in 1994 found Gupta guilty of all charges, “an article in the Indian weekly The World called for Gupta to be stripped of his PhD and DSc degrees, both of which had been demonstrated to be based upon fraudulent work. Strangely, though, when the Academic Senate of the Panjab University met to decide Gupta’s fate, only five out of the 55 senators voted for his dismissal. Gupta was allowed to keep his position within the university, to supervise research students and to retain his degrees” (Fossil Industry 2022).

Good to Remember

Gupta retired normally in 2002, with super-annuation benefits (Patnaik 2015), and none of his fraudulent publications has been retracted. Nor was he ever held legally accountable for his unbelievable misconduct. In 2013 a book was finally published in India about the case (Shah 2013). Nowadays, such a scandal would likely never have been uncovered at all, because political correctness would hardly allow anyone to accuse a scientist from a non-Western country of such outrageous behavior or even find that “India is also a leading nation in fraudulent scientific research” (Patnaik 2015). An obvious question that is also not allowed to be asked concerns the desolate state of a whole scientific discipline, where such a massive fraud could happen in the first place and stay unnoticed for decades. Good to remember when somebody tells you to just trust in science and to stop asking inconvenient questions.

References

Anderson I 1991. Himalayan scandal rocks Indian science. NewScientist Febr. 9, 1991. https://www.newscientist.com/article/mg12917551-600-himalayan-scandal-rocks-indian-science/

Carleton S 2005. What happens to the Whistleblowers? ABC The Science Show Sept. 3, 2005. http://web.archive.org/web/20050911052826/http://www.abc.net.au/rn/science/ss/stories/s1451250.htm

Fossil Industry 2022. A famous case of Indian fossil fraud and theft. Fossil Hunters Dec. 21, 2022. https://www.fossilhunters.xyz/fossil-industry/a-famous-case-of-indian-fossil-fraud-and-theft.html

Goel RK 1977. Triassic Conodonts from Spiti (Himachal Pradesh), India. Journal of Paleontology 51(6), 1085–1101. https://www.jstor.org/stable/1303823

Lewin R 1989. The Case of “Misplaced” Fossils. Science 244(4902), 277–279. DOI: https://doi.org/10.1126/science.244.4902.277

Nature 1993. Palaeontology under a Himalayan shadow. Nature 366(6456), 616. DOI: https://doi.org/10.1038/366616a0

Patnaik PR 2015. Scientific Misconduct in India: Causes and Perpetuation. Science and Engineering Ethics 22(4), 1245–1249. DOI: https://doi.org/10.1007/s11948-015-9677-6

Ruffell A, Majury N & Brooks WE 2012. Geological fakes and frauds. Earth-Science Reviews 111(1-2), 224–231. DOI: https://doi.org/10.1016/j.earscirev.2011.12.001

Shah SK 2013. Himalayan Fossil Fraud – A View from the Galleries. Palaeontological Society of India Special Publication 4, University of Lucknow, 141 pp.

Talent JA 1989. The case of peripatetic fossils. Nature 338(6217), 613–615. DOI: https://doi.org/10.1038/338613a0

Webster GD 2016. An evaluation of the V. J. Gupta echinoderm papers, 1971–1989. Journal of Paleontology 65(6), 1006–1008. DOI: https://doi.org/10.1017/S002233600003331X

Webster GD, Rexroad CB & Talent JA 1993. An Evaluation of the V. J. Gupta Conodont Papers. Journal of Paleontology 67(3), 486–493. https://www.jstor.org/stable