Data Availability Quotes

There are periods of history when the visions of madmen and dope fiends are a better guide to reality than the common-sense interpretation of data available to the so-called normal mind. This is one such period, if you haven't noticed already.

Science has the answer to every question that can be asked. However, science reserves the right to change that answer should additional data become available.

There is scarcely a subject that cannot be mathematically treated and the effects calculated or the results determined beforehand from the available theoretical and practical data.

Discovering a cure for a disease is one thing, but making that cure available to everyone so it can actually be used to eradicate the problem is another thing.

People often think that the best way to predict the future is by collecting as much data as possible before making a decision. But this is like driving a car looking only at the rearview mirror—because data is only available about the past.

NASA are idiots. They want to send canned primates to Mars!" Manfred swallows a mouthful of beer, aggressively plonks his glass on the table: "Mars is just dumb mass at the bottom of a gravity well; there isn't even a biosphere there. They should be working on uploading and solving the nanoassembly conformational problem instead. Then we could turn all the available dumb matter into computronium and use it for processing our thoughts. Long-term, it's the only way to go. The solar system is a dead loss right now – dumb all over! Just measure the MIPS per milligram. If it isn't thinking, it isn't working. We need to start with the low-mass bodies, reconfigure them for our own use. Dismantle the moon! Dismantle Mars! Build masses of free-flying nanocomputing processor nodes exchanging data via laser link, each layer running off the waste heat of the next one in. Matrioshka brains, Russian doll Dyson spheres the size of solar systems. Teach dumb matter to do the Turing boogie!

Example: “Based on the available information and the data hitherto collected, my hypothesis is that the farther away I stay from love, the better off I will be.

The scientific study of suffering inevitably raises questions of causation, and with these, issues of blame and responsibility. Historically, doctors have highlighted predisposing vulnerability factors for developing PTSD, at the expense of recognizing the reality of their patients' experiences… This search for predisposing factors probably had its origins in the need to deny that all people can be stressed beyond endurance, rather than in solid scientific data; until recently such data were simply not available… When the issue of causation becomes a legitimate area of investigation, one is inevitably confronted with issues of man's inhumanity to man, with carelessness and callousness, with abrogation of responsibility, with manipulation and with failures to protect.

There’s data in the world available only to those who have reached a certain level of wretchedness. You dont know what’s down there if you havent been down there. Joy on the other hand hardly even teaches gratitude. A thoughtful silence.

Paradoxically, the sources available today (in the era of big data) are less precise than those that were available a century ago due to the internationalization of wealth, the proliferation of tax havens, and above all, lack of political will to enforce financial transparency, so it is quite possible that we are underestimating the level of wealth inequality in recent decades.

When you put together open medicine, open science, open access, open source, and open data—Open5—all sorts of new channels of research activity become available, and existing ones become exponentially more powerful.

It is amazing how much both happiness and efficiency can be increased by the cultivation of an orderly mind, which thinks about a matter adequately at the right time rather than inadequately at all times. When a difficult or worrying decision has to be reached, as soon as all the data are available, give the matter your best thought and make your decision; having made the decision, do not revise it unless some new fact comes to your knowledge. Nothing is so exhausting as indecision, and nothing is so futile.

You dont know what antipsychotics are and you dont know how they work. Or why. All we have finally is the spectacle of tardive dyskinetics feeling their way along the wall. Jerking and drooling and muttering. Of course for those trekking toward the void there are waystations where the news will very suddenly become altogether bleaker. Maybe a sudden chill. There’s data in the world available only to those who have reached a certain level of wretchedness. You dont know what’s down there if you havent been down there.

Availability protection ensures reliability and timely access to data and resources to authorized individuals.

There's data in the world available only to those who have reached a certain level of wretchedness. You dont know what's down there if you havent been down there.

Based on the available information and the data hitherto collected, my hypothesis is that the farther away I stay from love, the better off I will be

It’s very important that people take back their minds and that people analyse our dilemma in the context of the entire human story from the descent onto the grassland to our potential destiny as citizens of the galaxy and the universe. We are at a critical turning point and, as I say; the tools, the data that holds the potential for our salvation is now known, it is available: it is among us, but it is misrepresented, it is slandered, it is litigated against, and it’s up to each one of us to relate to this situation in a fashion that will allow us to answer the question that will surely be put to us at some point in the future, which is: What did you do to help save the world?

Electrons don’t care. Once data of any sort go into the net, time is frozen. All that is necessary is to remember that all the endless riches of the past are available any time you punch for them.

The avalanche of new data that has become available in the wake of the genome revolution has shown just how wrong the tree metaphor is for summarizing the relationship among modern human populations.

some forms of deception might become harder to practice thanks to increased availability of many kinds of data, including reputations and track records, or the promulgation of strong epistemic norms and rationality culture.

The Washington Post found press documentation of 258 black victims of fatal police shootings in 2015, most of whom were seriously attacking the officer. In 2014, the most recent year for which such data are available, there were 6,095 black homicide victims in the United States, which means that the police could eliminate all of their own fatal shootings without having a significant impact on the black homicide death rate. The killers of those black homicide victims are overwhelmingly other blacks—who are responsible for a death risk ten times that of whites in urban areas.

The value for which P=0.05, or 1 in 20, is 1.96 or nearly 2; it is convenient to take this point as a limit in judging whether a deviation ought to be considered significant or not. Deviations exceeding twice the standard deviation are thus formally regarded as significant. Using this criterion we should be led to follow up a false indication only once in 22 trials, even if the statistics were the only guide available. Small effects will still escape notice if the data are insufficiently numerous to bring them out, but no lowering of the standard of significance would meet this difficulty.

A citizen at his home in Rockford, Illinois, or Boulder, Colorado, could read a newspaper, listen to a radio, or watch the round-the-clock coverage on television, but he had no way of connecting with those who shared his views. Nor was there a quick, readily available tool for an ordinary citizen to gather information on his own. In 1960, communication was a one-way street, and information was fundamentally inaccessible. The whole idea of summoning up data or reaching thousands of individuals with the touch of a finger was a science-fiction fantasy.

The Internet’s abundant capacity has removed the old artificial constraints on publishing—including getting our content checked and verified. The new strategy of publishing everything we find out thus results in an immense cloud of data, free of theory, published before verified, and available to anyone with an Internet connection. And this is changing the role that facts have played as the foundation of knowledge.

Mug shot extortion sites turn this sort of thing into a business. Mug shots are public record, but they’re not readily available. Owners of mug shot sites acquire the photos in bulk and publish them online, where everybody can find them, then charge individuals to remove their photos from the sites.

When a difficult or worrying decision has to be reached, as soon as all the data are available give the matter your best thought and make your decision; having made the decision, do not revise it unless some new fact comes to your knowledge. Nothing is so exhausting as indecision, and nothing is so futile. A

The right of the Gabbitas and Kogan Page to be identified as the authors of this work has been asserted by them in accordance with the Copyright, Designs and Patents Act 1988. British Library Cataloguing in Publication Data A CIP record for this book is available from the British Library ISBN       978 0 7494 6747 0

Some readers are bound to want to take the techniques we’ve introduced here and try them on the problem of forecasting the future price of securities on the stock market (or currency exchange rates, and so on). Markets have very different statistical characteristics than natural phenomena such as weather patterns. Trying to use machine learning to beat markets, when you only have access to publicly available data, is a difficult endeavor, and you’re likely to waste your time and resources with nothing to show for it. Always remember that when it comes to markets, past performance is not a good predictor of future returns—looking in the rear-view mirror is a bad way to drive. Machine learning, on the other hand, is applicable to datasets where the past is a good predictor of the future.

Protecting data is not just about preventing unauthorized access. It also involves ensuring data integrity and availability.

Ron Rivest, one of the inventors of RSA, thinks that restricting cryptography would be foolhardy: It is poor policy to clamp down indiscriminately on a technology just because some criminals might be able to use it to their advantage. For example, any U.S. citizen can freely buy a pair of gloves, even though a burglar might use them to ransack a house without leaving fingerprints. Cryptography is a data-protection technology, just as gloves are a hand-protection technology. Cryptography protects data from hackers, corporate spies, and con artists, whereas gloves protect hands from cuts, scrapes, heat, cold, and infection. The former can frustrate FBI wiretapping, and the latter can thwart FBI fingerprint analysis. Cryptography and gloves are both dirt-cheap and widely available. In fact, you can download good cryptographic software from the Internet for less than the price of a good pair of gloves.

although largely Canaanite according to currently available cultural data, Israel expressed a distinct sense of origins and deity and possessed largely distinct geographical holdings in the hill country by the end of the Iron I period.

People often think that the best way to predict the future is by collecting as much data as possible before making a decision. But this…is like driving a car looking only at the rearview mirror-because data is only available about the past.

By then all the available data had been coordinated into what Americans really seem to mean when they say they want “the news”—and what they really mean is “Tell me a story” and make sure it has a beginning, a middle, and some kind of ending.

the income from traditional capital is even more unevenly shared out across society than the income from salaries and wages. This fact is true ‘without exception’, notes Thomas Piketty, in all countries and at all times for which data is available.

It is often thought that the life of the hunter-gatherer was one of feast and famine. But most available data suggest that they were surprisingly healthy and had a fairly stable diet and lifestyle. Not so the primitive farmers. In years when the crops failed, in settlements where the population density was high and where disease weakened the ability to cope even further, life would have been very hard indeed. The settled population could not migrate to follow the food supply as could hunter-gatherers. They were trapped.

note that, where comparative data are available “people in [WEIRD] societies consistently occupy the extreme end of the … distribution [making them] one of the worst subpopulations one could study for generalizing about Homo sapiens” (Henrich et al. 2010: 63, 65, 79).

Pretty soon all the information in the world – every tiny scrap of knowledge that humans possess, every little thought we’ve ever had that’s been considered worth preserving over thousands of years – all of it will be available digitally. Every road on earth has been mapped. Every building photographed. Everywhere we humans go, whatever we buy, whatever websites we look at, we leave a digital trail as clear as slug-slime. And this data can be read, searched and analysed by computers and value extracted from it in ways we cannot even begin to conceive.

Thankfully, most supplements are usually not harmful, at least not in the short term. As Tod Cooperman, the president of a supplement testing company called ConsumerLab.com, put it to me, “In the vast majority of cases, people are just throwing their money out the window or hurting themselves over a long period of time.” But as the last part of his comment suggests, there are still reasons for concern over what’s in some of these products—especially given that in the most recent data available from the Centers for Disease Control and Prevention, more than 50 percent of American adults reported using some sort of dietary supplement.

Needless to say, the anointed much prefer to quote family and household statistics on income, claiming “economic stagnation,” the “disappearance of the middle class,” and miscellaneous other rhetorical catastrophes. “For all but the top 20 percent,” an op-ed column in the New York Times said, “income has stagnated.” Moreover, this alleged fact was “widely acknowledged” by “politicians, economists and sociologists.”72 That so many such people echoed the same refrain—without bothering to check readily available census data to the contrary—says more about them than about income. Moreover, not all such use of household or family income data can be attributed to statistical naivete.

Then, after many weeks, Citra had an epiphany. If everything uploaded to the Thunderhead was stored in the backbrain, then not just public records were there, but personal as well. She couldn’t access other people’s private records, but anything she uploaded would be available to her. Which meant she could seed the search with data of her own.…

This is not to say that everybody with ADHD suffers from poor work performance; many are quite consistent and productive workers, and some are truly outstanding employees. Available data simply indicate that the executive function impairments of ADHD significantly increase the risk that affected adults will have significant problems with employment.

The End of Nature was the first book for a general audience about global warming; it came out in 1989 and soon appeared in more than twenty languages. At the time, the available data on climate change still fit on the top of my desk. What’s astonishing is that twenty years later most of the predictions scientists were then making have proved too conservative.

The importance of experimental proof, on the other hand, does not mean that without new experimental data we cannot make advances. It is often said that science takes steps forward only when there is new experimental data. If this were true, we would have little hope of finding the theory of quantum gravity before measuring something new, but this is patently not the case. Which new data were available to Copernicus? None. He had the same data as Ptolemy. Which new data did Newton have? Almost none. His real ingredients were Kepler's laws and Galileo's results. What new data did Einstein have to discover general relativity? None. His ingredients were special relativity and Newton's theory. It simply isn't true that physics only advances when it is afforded new data.

Despite all technical change in the advanced countries, to this day India, with a much smaller cultivated area than the US, produces annually a larger total tonnage of cereals, root crops, oil crops, sugar crops, fruits and vegetables. The precise figures are 858 million tonnes in India and 676 million tonnes in the US in 2007, the latest year for which the data from the United Nations Food and Agriculture Organisation is available. As for China, its even more intensive cultivation, developed over centuries, and consequent high land productivity were legendary; Britain’s agricultural yields at that time, properly measured over the same production period, were pathetic in comparison. By 2007 China produced 1,308 million tonnes from an area substantially less than that of India and of the US.

As philosopher Brian Keeley has pointed out, by weaving every niggling anomaly into a grand unifying theory, conspiracy theories can look stronger than the official stories by sheer virtue of completeness. Conspiracy theories “always explain more than competing theories, because by invoking a conspiracy, they can explain both the data of the received account and the errant data that the received theory fails to explain.” But this apparent virtue, Keeley argues, is an illusion. You can find anomalies everywhere if you look hard enough. Our understanding of complex events will always contain errors, contradictions, and gaps. History is messy, people are fallible. “Given the imperfect nature of our human understanding of the world, we should expect that even the best possible theory would not explain all the available data,” Keeley concludes.

The results of decades of neurotransmitter-depletion studies point to one inescapable conclusion: low levels or serotonin, norepinephrine or dopamine do not cause depression. here is how the authors of the most complete meta-analysis of serotonin-depletion studies summarized the data: "Although previously the monoamine systems were considered to be responsible for the development of major depressive disorder (MDD), the available evidence to date does not support a direct causal relationship with MDD. There is no simple direct correlation of serotonin or norepinephrine levels in the brain and mood.' In other words, after a half-century of research, the chemical-imbalance hypothesis as promulgated by the drug companies that manufacture SSRIs and other antidepressants is not only with clear and consistent support, but has been disproved by experimental evidence.

Eventually, the performance of a classifier, computational power as well as predictive power, depends heavily on the underlying data that are available for learning. The five main steps that are involved in training a machine learning algorithm can be summarized as follows: Selection of features. Choosing a performance metric. Choosing a classifier and optimization algorithm. Evaluating the performance of the model. Tuning the algorithm.

High-quality and transparent data, clearly documented, timely rendered, and publicly available are the sine qua non of competent public health management. During a pandemic, reliable and comprehensive data are critical for determining the behavior of the pathogen, identifying vulnerable populations, rapidly measuring the effectiveness of interventions, mobilizing the medical community around cutting-edge disease management, and inspiring cooperation from the public. The shockingly low quality of virtually all relevant data pertinent to COVID-19, and the quackery, the obfuscation, the cherrypicking and blatant perversion would have scandalized, offended, and humiliated every prior generation of American public health officials. Too often, Dr. Fauci was at the center of these systemic deceptions. The “mistakes” were always in the same direction—inflating the risks of coronavirus and the safety and efficacy of vaccines in

Like the railroads that bankrupted a previous generation of visionary entrepreneurs and built the foundations of an industrial nation, fiber-optic webs, storewidth breakthroughs, data centers, and wireless systems installed over the last five years will enable and endow the next generation of entrepreneurial wealth. As Mead states, "the hardest thing I ever had to do in my life was to get a company going during the bubble". Now, Mead says, "there's space available; you can get fab runs; you can get vendors to answer the phone. You can make deals with people; you can sit down and they don't spend their whole time telling you how they're a hundred times smarter than you. It's absolutely amazing. You can actually get work done now, which means what's happening now is that the entrepreneurs, the technologists, are building the next generation technology that isn't visible yet but upon which will be built the biggest expansion of productivity the world has ever seen.

The process of decision making and projecting a future in which one future among many can be selected depends less and less on human will. We may call it the paradox of the decider: as the circulation of information becomes faster and more complex, the time available for the elaboration of relevant information becomes shorter. The more space taken by the available information, the less time there is for understanding and conscious choice. This is why the interdependence between data and decisions is more and more embedded in infomachinery, in technolinguistic interfaces. This is why the execution of the program is entrusted to automated procedures that human operators can neither change nor ignore. The machine pretends to be neutral, purely mathematical, but we know that its procedures are only the technical reification of social interests: profit, accumulation, competition—these are the criteria underlying the automatic procedures embedded in the machine. Human volition is reduced to a procedural pretense.

If we had enough data then this statistical approach would undoubtedly sort out these things, and a lot of problems are arising precisely because we haven't got enough documents for the statistical approach to be wholly valid. I know you can calculate levels of probability and so forth, but to establish this really clearly we want a lot more information than we have actually got available. This is surely our major problem that we are still at the very limits at which you can use a technique of this sort. - John Chadwick

Modern scientific culture has evolved from its roots in the ancient world and has become a complex web of many highly specialized disciplines. Gone are the days when one man, such as the seventeeth-century Robert Hooke, could be a groundbreaking inventor, microscopist, physicist, surveyor, astronomer, biologist and even artist. Today the sheer enormity of available information has led to highly defined specialisms, and academics are expected to keep to their field - despite the truism that science has no experts. [...] The gains from modern science are beyond counting. But the loss, arguably, is the synthesis of information generated by the many gentleman scholars that once existed, before becoming extinct somewhere around hte late nineteenth century. So few scholars now have a chance to view the bigger picture - to seek out patterns that might unexpectedly exist when apparently unrelated data is brought together. It has to be remembered that the difference between a major breakthrough and nothing at all can be just the angle of view rather than anything else.

In fact, as these companies offered more and more (simply because they could), they found that demand actually followed supply. The act of vastly increasing choice seemed to unlock demand for that choice. Whether it was latent demand for niche goods that was already there or a creation of new demand, we don't yet know. But what we do know is that the companies for which we have the most complete data - netflix, Amazon, Rhapsody - sales of products not offered by their bricks-and-mortar competitors amounted to between a quarter and nearly half of total revenues - and that percentage is rising each year. in other words, the fastest-growing part of their businesses is sales of products that aren't available in traditional, physical retail stores at all. These infinite-shelf-space businesses have effectively learned a lesson in new math: A very, very big number (the products in the Tail) multiplied by a relatives small number (the sales of each) is still equal to a very, very big number. And, again, that very, very big number is only getting bigger. What's more, these millions of fringe sales are an efficient, cost-effective business. With no shelf space to pay for - and in the case of purely digital services like iTunes, no manufacturing costs and hardly any distribution fees - a niche product sold is just another sale, with the same (or better) margins as a hit. For the first time in history, hits and niches are on equal economic footing, both just entries in a database called up on demand, both equally worthy of being carried. Suddenly, popularity no longer has a monopoly on profitability.

In its broadest sense, the question to be considered is, "How to Investigate a Problem." In doing this the first step is to get together all available information regarding the problem, including books, experimental data and results of experience, and to consider and digest this material. Personal investigations and inquiry, further experimental research, correspondence, travel, etc., may then be necessary. This will be based, however, in general, upon a study of books, and with this part of the subject we are here particularly concerned.

In the Negev in Israel, Israeli authorities have refused to legally recognize 35 Palestinian Bedouin communities, making it impossible for their 90,000 or so residents to live lawfully in the communities they have lived in for decades. Instead, authorities have sought to concentrate Bedouin communities in larger recognized townships in order, as expressed in governmental plans and statements by officials, to maximize the land available for Jewish communities. Israeli law considers all buildings in these unrecognized villages to be illegal, and authorities have refused to connect most to the national electricity or water grids or to provide even basic infrastructure such as paved roads or sewage systems. The communities do not appear on official maps, most have no educational facilities, and residents live under constant threat of having their homes demolished. Israeli authorities demolished more than 10,000 Bedouin homes in the Negev between 2013 and 2019, according to government data. They razed one unrecognized village that challenged the expropriation of its lands, al-Araqib, 185 times.

The JFK assassination itself has been dissected to pieces by obsessed researchers like me. Suffice to say that a few days of intense study of the available record will convince any honest person, beyond any reasonable doubt, that Lee Harvey Oswald was not responsible for the crime. The coverup was so clear and obvious in nature, and so shabbily constructed, that the conclusion is inescapable that the conspirators who killed him wanted the kind of controversy that soon exploded, shortly after the first wave of private citizens began to look at the data.

Roy Jastram has produced a systematic study of the purchasing power of gold over the longest consistent datasets available.6 Observing English data from 1560 to 1976 to analyze the change in gold's purchasing power in terms of commodities, Jastram finds gold dropping in purchasing power during the first 140 years, but then remaining relatively stable from 1700 to 1914, when Britain went off the gold standard. For more than two centuries during which Britain primarily used gold as money, its purchasing power remained relatively constant, as did the price of wholesale commodities.

The first duty of the command and control system is to survive,” Baran argued, proposing a distributed network with hundreds or thousands of separate nodes connected through multiple paths. Messages would be broken into smaller “blocks,” sent along the first available path, and reassembled at their final destination. If nodes were out of service or destroyed, the network would automatically adapt and send the data along a route that was still intact. Baran’s work later provided the conceptual basis for the top secret communications networks at the Pentagon, as well as their civilian offshoot, the Internet.

In 2004, a panel of respected scientists—none of whom had worked with vaccines—was convened by the Institute of Medicine of the National Academy of Sciences to review all of the available data. They concluded that there was no evidence that vaccines were associated with the development of autism.23 Since that time, the evidence has become even more robust that there is no link between measles vaccines or thimerosal-containing vaccines and autism. The continuing public “controversy” in the face of the scientific evidence is now considered to be misinformation. And what pervasive misinformation it has been and continues to be.

I try to be rational (or at least my imaginary facsimile of what rationality is supposed to be). I try to look at the available data objectively (fully aware that this is impossible). I try to extrapolate what may be happening now into what will be happening later. And this, of course, is where naïve realism punches me in the throat. There's simply no way around the limited ceiling of my own mind. It's flat-out impossible to speculate on the future without (a) consciously focusing on the most obvious aspects of what we already know and (b) unconsciously excluding all the things we don't have the intellectual potential to grasp.

Ernestine Warner was working with the same rough information available to traders like Eisman. This was insane: The arbiter of the value of the bonds lacked access to relevant information about the bonds. "When we asked her why", said Vinny, she said "The issuers won't give it to us". That's when i lost it. "You need to demand to get it!" She looked at us like, We can't do that. We were like, "Who is in charge here? You're the grown-up. You're the cop! Tell them the fucking give it to you!!!" Eisman concluded that "S&P was worried that if they demanded the data from Wall Street, Wall Street would just go to Moody's for their ratings.

Prediabetes is easily identified through clinical measurements such as insulin resistance, fasting glucose levels, and glycated hemoglobin (HbA1c, often abbreviated to A1c). Unfortunately, we act on these measurements far less frequently than we should. Early interventions are far easier and far more effective than the more complex and generally ineffective therapies available to treat advanced diabetes. In most cases, all it takes to reverse prediabetes are some straightforward lifestyle choices, including a decrease in dietary sugar and an increase in exercise. These changes require some discipline but are generally simple and even pleasurable.

Trusting our instincts is not limited to sports. In every walk of life, regardless of how well trained our instincts are, we will usually do our best by trusting them. Recent brain-scanning technology has shown that the brain unconsciously makes rational decisions, quickly analyzing the data it gets, and reaches a decision sometimes seconds before our conscious minds “think up” that same decision. Actions that feel like random choices or instinctive responses are often logical thought processes using available information carried out in the unconscious mind. Many successful businesspeople say their best decisions are the ones they make using “gut feelings” or instinct.

These findings stand in sharp contrast to the belief in “American exceptionalism” that once dominated US sociology, according to which social mobility in the United States was exceptionally high compared with the class-bound societies of Europe. No doubt the settler society of the early nineteenth century was more mobile. As I have shown, moreover, inherited wealth played a smaller role in the United States than in Europe, and US wealth was for a long time less concentrated, at least up to World War I. Throughout most of the twentieth century, however, and still today, the available data suggest that social mobility has been and remains lower in the United States than in Europe.

It’s All about Scaling Most of the current learning algorithms were discovered more than twenty-five years ago, so why did it take so long for them to have an impact on the real world? With the computers and labeled data that were available to researchers in the 1980s, it was only possible to demonstrate proof of principle on toy problems. Despite some promising results, we did not know how well network learning and performance would scale as the number of units and connections increased to match the complexity of real-world problems. Most algorithms in AI scale badly and never went beyond solving toy problems. We now know that neural network learning scales well and that performance continues to increase with the size of the network and the number of layers. Backprop, in particular, scales extremely well. Should we be surprised? The cerebral cortex is a mammalian invention that mushroomed in primates and especially in humans. And as it expanded, more capacity became available and more layers were added in association areas for higher-order representations. There are few complex systems that scale this well. The Internet is one of the few engineered systems whose size has also been scaled up by a million times. The Internet evolved once the protocols were established for communicating packets, much like the genetic code for DNA made it possible for cells to evolve. Training many deep learning networks with the same set of data results in a large number of different networks that have roughly the same average level of performance.

Premenstrual syndrome (PMS) is a collection of symptoms that can include among other things: mood swings, anxiety, breast tenderness, bloating, acne, headaches, stomach pain and sleep problems. PMS affects 90% of women, but is chronically under-studied: one research round-up found five times as many studies on erectile dysfunction than on PMS.88 And yet while a range of medication exists to treat erectile dysfunction89 there is very little available for women, to the extent that over 40% of women who have PMS don’t respond to treatments currently available. Sufferers are still sometimes treated with hysterectomies; in extreme cases, women have tried to kill themselves.90 But researchers are still being turned down for research grants on the basis that ‘PMS does not actually exist’.91

When experimentation is complete, researchers are expected to document and share their data and methodology so they are available for careful scrutiny by other scientists. This allows other researchers the chance to verify results by attempting to reproduce them and allows statistical measures of the reliability of these data to be established. This is called “full disclosure” and is an area that the paranormal field is lacking in. Currently there is no repository of paranormal data or body of evidence that researchers can turn to for comparing data. Television shows and websites that document paranormal activity are really our only outlet. The drawback to not having a database is that researchers cannot identify patterns of activity and therefore can’t derive theories or explanations of the paranormal.

I always find it extraordinary that so many studies are made of price and volume behavior, the stuff of chartists. Can you imagine buying an entire business simply because the price of the business had been marked up substantially last week and the week before? Of course, the reason a lot of studies are made of these price and volume variables is that now, in the age of computers, there are almost endless data available about them. It isn’t necessarily because such studies have any utility; it’s simply that the data are there and academicians have worked hard to learn the mathematical skills needed to manipulate them. Once these skills are acquired, it seems sinful not to use them, even if the usage has no utility or negative utility. As a friend said, to a man with a hammer, everything looks like a nail.

Has ‘Western civilization’ really made life better for everyone? This ultimately comes down to the question of how to measure human happiness, which is a notoriously difficult thing to do. About the only dependable way anyone has ever discovered to determine whether one way of living is really more satisfying, fulfilling, happy or otherwise preferable to any other is to allow people to fully experience both, give them a choice, then watch what they actually do. For instance, if Pinker is correct, then any sane person who had to choose between (a) the violent chaos and abject poverty of the ‘tribal’ stage in human development and (b) the relative security and prosperity of Western civilization would not hesitate to leap for safety.25 But empirical data is available here, and it suggests something is very wrong with Pinker’s conclusions.

The view that many well-established theoretical positions in psychology cannot be as widely generalized as their authors assume was given a boost by a carefully argued paper published in 2010. Joe Henrich and colleagues challenged the very foundations of the discipline in arguing that psychologists fail to account for the influence of culture or nurture on human behavior. From a large-scale survey they determined that the vast majority of research in psychology is carried out with citizens – especially college students – of Western, Educated, Industrialized, Rich, Democracies (WEIRD). They note that, where comparative data are available “people in [WEIRD] societies consistently occupy the extreme end of the … distribution [making them] one of the worst subpopulations one could study for generalizing about Homo sapiens” (Henrich et al. 2010: 63, 65, 79).

TRUST IN ONE’S ORGANISM A second characteristic of the persons who emerge from therapy is difficult to describe. It seems that the person increasingly discovers that his own organism is trustworthy, that it is a suitable instrument for discovering the most satisfying behavior in each immediate situation. If this seems strange, let me try to state it more fully. Perhaps it will help to understand my description if you think of the individual as faced with some existential choice: “Shall I go home to my family during vacation, or strike out on my own?” “Shall I drink this third cocktail which is being offered?” “Is this the person whom I would like to have as my partner in love and in life?” Thinking of such situations, what seems to be true of the person who emerges from the therapeutic process? To the extent that this person is open to all of his experience, he has access to all of the available data in the situation, on which to base his behavior. He has knowledge of his own feelings and impulses, which are often complex and contradictory. He is freely able to sense the social demands, from the relatively rigid social “laws” to the desires of friends and family. He has access to his memories of similar situations, and the consequences of different behaviors in those situations. He has a relatively accurate perception of this external situation in all of its complexity. He is better able to permit his total organism, his conscious thought participating, to consider, weigh and balance each stimulus, need, and demand, and its relative weight and intensity. Out of this complex weighing and balancing he is able to discover that course of action which seems to come closest to satisfying all his needs in the situation, long-range as well as immediate needs.

It is a remarkable fact that in modern Europe and America institutional religion has declined while belief in God and the supernatural has remained strong and in some settings has even increased. Recent surveys, for example, show that while a declining group of Americans regularly go to church or synagogue (20–30 percent), overwhelming majorities of Americans report believing in a God who responds to prayer (80–90 percent), in angels and demons who actively interact with the living (70 percent), or in a heavenly afterlife that welcomes the souls of the departed (70–85 percent). An astonishing 30 percent of Americans report that they have been “in touch” with someone who has died.1 Similar data are also available for European nations, which report even lower levels of religious affiliation but an explosion of self-identified “spiritual but not religious” people. There are many reasons for the distaste for institutional religion,

Generally, it is clear that things that make life less boring are a priority for the poor. This may be a television, or a little bit of something special to eat—or just a cup of sugary tea. Even Pak Solhin had a television, although it was not working when we visited him. Festivals may be seen in this light as well. Where televisions or radios are not available, it is easy to see why the poor often seek out the distraction of a special family celebration of some kind, a religious observance, or a daughter’s wedding. In our eighteen-country data set, it is clear that the poor spend more on festivals when they are less likely to have a radio or a television. In Udaipur, India, where almost no one has a television, the extremely poor spend 14 percent of their budget on festivals (which includes both lay and religious occasions). By contrast, in Nicaragua, where 58 percent of rural poor households have a radio and 11 percent own a television, very few households report spending anything on festivals.33

Imagine you're sitting having dinner in a restaurant. At some point during the meal, your companion leans over and whispers that they've spotted Lady Gaga eating at the table opposite. Before having a look for yourself, you'll no doubt have some sense of how much you believe your friends theory. You'll take into account all of your prior knowledge: perhaps the quality of the establishment, the distance you are from Gaga's home in Malibu, your friend's eyesight. That sort of thing. If pushed, it's a belief that you could put a number on. A probability of sorts. As you turn to look at the woman, you'll automatically use each piece of evidence in front of you to update your belief in your friend's hypothesis Perhaps the platinum-blonde hair is consistent with what you would expect from Gaga, so your belief goes up. But the fact that she's sitting on her own with no bodyguards isn't, so your belief goes down. The point is, each new observations adds to your overall assessment. This is all Bayes' theorem does: offers a systematic way to update your belief in a hypothesis on the basis of the evidence. It accepts that you can't ever be completely certain about the theory you are considering, but allows you to make a best guess from the information available. So, once you realize the woman at the table opposite is wearing a dress made of meat -- a fashion choice that you're unlikely to chance up on in the non-Gaga population -- that might be enough to tip your belief over the threshold and lead you to conclude that it is indeed Lady Gaga in the restaurant. But Bayes' theorem isn't just an equation for the way humans already make decisions. It's much more important that that. To quote Sharon Bertsch McGrayne, author of The Theory That Would Not Die: 'Bayes runs counter to the deeply held conviction that modern science requires objectivity and precision. By providing a mechanism to measure your belief in something, Bayes allows you to draw sensible conclusions from sketchy observations, from messy, incomplete and approximate data -- even from ignorance.

Throughout most of the twentieth century, however, and still today, the available data suggest that social mobility has been and remains lower in the United States than in Europe. One possible explanation for this is the fact that access to the most elite US universities requires the payment of extremely high tuition fees. Furthermore, these fees rose sharply in the period 1990–2010, following fairly closely the increase in top US incomes, which suggests that the reduced social mobility observed in the United States in the past will decline even more in the future.29 The issue of unequal access to higher education is increasingly a subject of debate in the United States. Research has shown that the proportion of college degrees earned by children whose parents belong to the bottom two quartiles of the income hierarchy stagnated at 10–20 percent in 1970–2010, while it rose from 40 to 80 percent for children with parents in the top quartile.30 In other words, parents’ income has become an almost perfect predictor of university access.

The policy debate about sanctions has been repeated almost every decade since the [League of Nations] was created in the wake of World War I. At its core has been the perennial question: do economic sanctions work? While the success rate differs depending on the objective, the historical record is relatively clear: most economic sanctions have not worked. In the twentieth century, only one in three uses of sanctions was “at least partially successful.” More modest goals have better chances of success. But from the available data it is clear that the history of sanctions is largely a history of disappointment. What is striking is that this limited utility has not affected frequency of use. To the contrary: sanctions use doubled in the 1990s and 2000s compared to the period from 1950 to 1985; by the 2010s it had doubled again. Yet while in the 1985–1995 period, at a moment of great relative Western power, the chances of sanctions success were still around 35–40 percent, by 2016 this had fallen below 20 percent. In other words, while the use of sanctions has surged, their odds of success have plummeted.

The only path McAuliffe saw to hard-money parity ran through cycles of prospecting new donors, in the mail and online. To accomplish that on the scale he believed crucial, Democrats needed the list of 100 million new names, sortable by party registration or voting behavior, that would fill a national voter file. McAuliffe proposed a deal to the state chairs, that the DNC would effectively borrow their files, help clean them up, add new data like donor information and commercially available phone numbers, and then return them for the state party’s use. At the same time, McAuliffe went to Vinod Gupta, a major Democratic fund-raiser and Clinton friend who was the founder and CEO of InfoUSA, one of the country’s large commercial data vendors. Like many of his rivals, Gupta had been trying for years to find customers in the political world, and offered McAuliffe a good deal for his product. McAuliffe agreed, and as the state files came in, the DNC would send them out to InfoUSA’s Omaha servers, where hundreds of pieces of new information were added to each voter’s profile. A new interface was built to navigate it all. It was called Demzilla.

What we need,” I said, “are statistics on the amount of sugar cane standing in the field before the hurricanes came through Puerto Rico.” There was a stunned silence, as if they were afraid I had stumbled onto something that could turn out to be embarrassing for the Labor Department. “Well, it’s not that easy,” one of the Labor Department economists said. “We don’t have those statistics.” “I’ll bet the Department of Agriculture has them,” I said. “That’s still not the same as if we had them in the Department of Labor,” I was told. “Why can’t we get them from the Department of Agriculture?” I asked. “That’s easier said than done. First of all, we would have to make a request, going all the way up through channels to the Secretary of Labor. Then he would have to seek approval from the Secretary of Agriculture, who would then have to forward the request down the chain of command in the Department of Agriculture, to see if the data are available and can be released.” “Well,” I said, “John F. Kennedy says that a journey of a thousand miles must begin with a single step. Let me file the request.” That was 1960. I have yet to receive an official reply to my request.

Cohn assembled every piece of economic data available to show that American workers did not aspire to work in assembly factories. Each month Cohn brought Trump the latest Job Openings and Labor Turnover Survey, called JOLTS, conducted y the Bureau of Labor Statistics. He realized he was being an asshole by rubbing it in because each month was basically the same, but he didn't care. "Mr. President, can I show this to you?" Cohn fanned out the pages of data in front of the president. "See, the biggest leavers of jobs--people leaving voluntarily--was from manufacturing." "I don't get it," Trump said. Cohn tried to explain: "I can sit in a nice office with air conditioning and a desk, or stand on my feet eight hours a day. Which one would you do for the same pay?" Cohn added, "People don't want to stand in front of a 2,000 degree blast furnace. People don't want to go into coal mines and get black lung. For the same dollars or equal ollars, they're going to choose something else." Trump wasn't buying it. Severl times Cohn just asked the president, "Why do you have these views?" "I just do," Trump replied. "I've had these views for 30 years." "That doesn't mean they're right," Cohn said. "I had the view for 15 years I could play professional football. It doesn't mean I was right.

Despite the advancements of systematic experimental pipelines, literature-curated protein-interaction data continue to be the primary data for investigation of focused biological mechanisms. Notwithstanding the variable quality of curated interactions available in public databases, the impact of inspection bias on the ability of literature maps to provide insightful information remains equivocal. The problems posed by inspection bias extend beyond mapping of protein interactions to the development of pharmacological agents and other aspects of modern biomedicine. Essentially the same 10% of the proteome is being investigated today as was being investigated before the announcement of completion of the reference genome sequence. One way forward, at least with regard to interactome mapping, is to continue the transition toward systematic and relatively unbiased experimental interactome mapping. With continued advancement of systematic protein-interaction mapping efforts, the expectation is that interactome 'deserts', the zones of the interactome space where biomedical knowledge researchers simply do not look for interactions owing to the lack of prior knowledge, might eventually become more populated. Efforts at mapping protein interactions will continue to be instrumental for furthering biomedical research.

Base your understanding of the world on data, rather than journalism. Journalism is a highly non random sample of the worst things that have happened in any given period. It is an availability machine, in the sense of Tversky and Kahneman's availability heuristic; namely - our sense of risk, danger and prevalence is driven by anecdotes, images and narratives that are available in memory. A lot of good things are either things that "don't happen" (like a country at peace, or a city that has not been attacked by terrorists, which almost by definition are not news), or things that build up incrementally, a few percentage points a year, and then compound (like the decline of extreme poverty). We can be unaware, out to lunch about what's happening in the world if we base our view on the news. If instead we base our view on data, then not only do we see that many (although not all) things have gone better (not linearly, not without setbacks and reversals, but in general a lot better... and that paradoxically, as I've cheekily put it, progressives hate progress), but also that the best possible case for progress - that is, for striving for more progress in the future, for being a true progressive - is not to have some kind of foolish hope, but to look at the fact that progress has taken place in the past; and that means: why should it stop now?

I will show that this spectacular increase in inequality largely reflects an unprecedented explosion of very elevated incomes from labor, a veritable separation of the top managers of large firms from the rest of the population. One possible explanation of this is that the skills and productivity of these top managers rose suddenly in relation to those of other workers. Another explanation, which to me seems more plausible and turns out to be much more consistent with the evidence, is that these top managers by and large have the power to set their own remuneration, in some cases without limit and in many cases without any clear relation to their individual productivity, which in any case is very difficult to estimate in a large organization. This phenomenon is seen mainly in the United States and to a lesser degree in Britain, and it may be possible to explain it in terms of the history of social and fiscal norms in those two countries over the past century. The tendency is less marked in other wealthy countries (such as Japan, Germany, France, and other continental European states), but the trend is in the same direction. To expect that the phenomenon will attain the same proportions elsewhere as it has done in the United States would be risky until we have subjected it to a full analysis—which unfortunately is not that simple, given the limits of the available data.

The “pale blue dot” image and Carl’s prose meditation on it have been beloved the world over ever since. It exemplifies just the kind of breakthrough that I think of as a fulfillment of Einstein’s hope for science. We have gotten clever enough to dispatch a spacecraft four billion miles away and command it to send us back an image of Earth. Seeing our world as a single pixel in the immense darkness is in itself a statement about our true circumstances in the cosmos, and one that every single human can grasp instantly. No advanced degree required. In that photo, the inner meaning of four centuries of astronomical research is suddenly available to all of us at a glance. It is scientific data and art equally, because it has the power to reach into our souls and alter our consciousness. It is like a great book or movie, or any major work of art. It can pierce our denial and allow us to feel something of reality—even a reality that some of us have long resisted. A world that tiny cannot possibly be the center of a cosmos of all that is, let alone the sole focus of its creator. The pale blue dot is a silent rebuke to the fundamentalist, the nationalist, the militarist, the polluter—to anyone who does not put above all other things the protection of our little planet and the life that it sustains in the vast cold darkness. There is no running away from the inner meaning of this scientific achievement.

Gone are those days when media platforms were available to few individuals like politicians, movie stars, artists,sports sensations, civil right activists, and religious scholars. =Today social media gives people an easy way to almost everything =It is very easy to learn from others who are experts and professionals,Regardless of your location and education background you can educate yourself, without paying for it. =It even reveals good and Mabošaedi of the most respected people who are role models to others = You can share your issues with the community and get help within an hour . = The main advantage of the social media is that you update yourself from the latest happenings around in the world. = you can promote your business to the largest audience and even employ people But it can also damage your life for good = Since anyone can create a fake account and do anything without being traced, it has become quite easy for people to frustrate others and do a damage to their names or life. = Personal data and privacy can easily be hacked and shared on the Internet. Which can make financial losses and loss to personal life. Similarly, identity theft is another issue that can give financial losses to anyone by hacking their personal accounts. This is one of the dangerous disadvantages of the social media and it even made people kill them selfs. = Addiction destroyed many families and employments.

[THE DAILY BREATH] Blaise Pascal, the famous mathematician, once said: "To those who wish to see, God gives them sufficient light. To those who doesn't wish to see, God gives them sufficient darkness." Seeing the Truth is a choice. Listening to my words is a choice. Healing is a choice. If want scientific evidence about the existence of God, there is a wealth of data to support it. Dr. Jeffrey Long, M.D. used the best scientific techniques available today to study more than 4,000 people who had near-death experiences and found themselves face to face with our Heavenly Father. Read the book "God and the Afterlife" and you will find it. If you want scientific evidence about Jesus being the Son of God, Lee Strobel, an atheist investigative journalist discovered it. Read the book "The Case for Christ" and you will find it. If you want scientific evidence about Jesus still healing today, study the ministries of Dr. Charles Ndifon, T.L. Osborn, Kathryn Kuhlman among others, and you will find it. But most importantly, if you want to fill the emptiness within you, and experience the perfect love, mercy and forgiveness, if you want to live in the peace of our Heavenly Father, give your body, your mind and your heart to Christ. Give your life to Jesus. The empty place you feel in your heart is reserved only for the spirit of Christ and nothing from this world will fill it. Look up to heaven, behold Jesus and Live.

Hunter-gatherers who survive childhood typically live to be old: their most common age of death is between sixty-eight and seventy-two, and most become grandparents or even great-grandparents.70 They most likely die from gastrointestinal or respiratory infections, diseases such as malaria or tuberculosis, or from violence and accidents.71 Health surveys also indicate that most of the noninfectious diseases that kill or disable older people in developed nations are rare or unknown among middle-aged and elderly hunter-gatherers.72 These admittedly limited studies have found that hunter-gatherers rarely if ever get type 2 diabetes, coronary heart disease, hypertension, osteoporosis, breast cancer, asthma, and liver disease. They also don’t appear to suffer much from gout, myopia, cavities, hearing loss, collapsed arches, and other common ailments. To be sure, hunter-gatherers don’t live in perpetually perfect health, especially since tobacco and alcohol have become increasingly available to them, but the evidence suggests that they are healthy compared to many older Americans today despite never having received any medical care. In short, if you were to compare contemporary health data from people around the world with equivalent data from hunter-gatherers, you would not conclude that rising rates of common mismatch diseases such as heart disease and type 2 diabetes are straightforward, inevitable by-products of economic progress and increased longevity. Moreover,

Then came the so-called flash crash. At 2:45 on May 6, 2010, for no obvious reason, the market fell six hundred points in a few minutes. A few minutes later, like a drunk trying to pretend he hadn’t just knocked over the fishbowl and killed the pet goldfish, it bounced right back up to where it was before. If you weren’t watching closely you could have missed the entire event—unless, of course, you had placed orders in the market to buy or sell certain stocks. Shares of Procter & Gamble, for instance, traded as low as a penny and as high as $100,000. Twenty thousand different trades happened at stock prices more than 60 percent removed from the prices of those stocks just moments before. Five months later, the SEC published a report blaming the entire fiasco on a single large sell order, of stock market futures contracts, mistakenly placed on an exchange in Chicago by an obscure Kansas City mutual fund. That explanation could only be true by accident, because the stock market regulators did not possess the information they needed to understand the stock markets. The unit of trading was now the microsecond, but the records kept by the exchanges were by the second. There were one million microseconds in a second. It was as if, back in the 1920s, the only stock market data available was a crude aggregation of all trades made during the decade. You could see that at some point in that era there had been a stock market crash. You could see nothing about the events on and around October 29, 1929.

Ultimately, the World Top Incomes Database (WTID), which is based on the joint work of some thirty researchers around the world, is the largest historical database available concerning the evolution of income inequality; it is the primary source of data for this book.24 The book’s second most important source of data, on which I will actually draw first, concerns wealth, including both the distribution of wealth and its relation to income. Wealth also generates income and is therefore important on the income study side of things as well. Indeed, income consists of two components: income from labor (wages, salaries, bonuses, earnings from nonwage labor, and other remuneration statutorily classified as labor related) and income from capital (rent, dividends, interest, profits, capital gains, royalties, and other income derived from the mere fact of owning capital in the form of land, real estate, financial instruments, industrial equipment, etc., again regardless of its precise legal classification). The WTID contains a great deal of information about the evolution of income from capital over the course of the twentieth century. It is nevertheless essential to complete this information by looking at sources directly concerned with wealth. Here I rely on three distinct types of historical data and methodology, each of which is complementary to the others.25 In the first place, just as income tax returns allow us to study changes in income inequality, estate tax returns enable us to study changes in the inequality of wealth.26 This

Changing what we think is always a sticky process, especially when it comes to religion. When new information becomes available, we cringe under an orthodox mindset, particularly when we challenge ideas and beliefs that have been “set in stone” for decades. Thomas Kuhn coined the term paradigm shift to represent this often-painful transition to a new way of thinking in science. He argued that “normal science” represented a consensus of thought among scientists when certain precepts were taken as truths during a given period. He believed that when new information emerges, old ideas clash with new ones, causing a crisis. Once the basic truths are challenged, the crisis ends in either revolution (where the information provides new understanding) or dismissal (where the information is rejected as unsound). The information age that we live in today has likely surprised all of us as members of the LDS Church at one time or another as we encounter new ideas that revise or even contradict our previous understanding of various aspects of Church history and teachings. This experience is similar to that of the Copernican Revolution, which Kuhn uses as one of his primary examples to illustrate how a paradigm shift works. Using similar instruments and comparable celestial data as those before them, Copernicus and others revolutionized the heavens by describing the earth as orbiting the sun (heliocentric) rather than the sun as orbiting the earth (geocentric). Because the geocentric model was so ingrained in the popular (and scientific!) understanding, the new, heliocentric idea was almost impossible to grasp. Paradigm shifts also occur in religion and particularly within Mormonism. One major difference between Kuhn’s theory of paradigm shift and the changes that occur within Mormonism lies in the fact that Mormonism privileges personal revelation, which is something that cannot be institutionally implemented or decreed (unlike a scientific law). Regular members have varying degrees of religious experience, knowledge, and understanding dependent upon many factors (but, importantly, not “faithfulness” or “worthiness,” or so forth). When members are faced with new information, the experience of processing that information may occur only privately. As such, different members can have distinct experiences with and reactions to the new information they receive. This short preface uses the example of seer stones to examine the idea of how new information enters into the lives of average Mormons. We have all seen or know of friends or family who experience a crisis of faith upon learning new information about the Church, its members, and our history. Perhaps there are those reading who have undergone this difficult and unsettling experience. Anyone who has felt overwhelmed at the continual emergence of new information understands the gravity of these massive paradigm shifts and the potentially significant impact they can have on our lives. By looking at just one example, this preface will provide a helpful way to think about new information and how to deal with it when it arrives.

To understand why it is no longer an option for geneticists to lock arms with anthropologists and imply that any differences among human populations are so modest that they can be ignored, go no further than the “genome bloggers.” Since the genome revolution began, the Internet has been alive with discussion of the papers written about human variation, and some genome bloggers have even become skilled analysts of publicly available data. Compared to most academics, the politics of genome bloggers tend to the right—Razib Khan17 and Dienekes Pontikos18 post on findings of average differences across populations in traits including physical appearance and athletic ability. The Eurogenes blog spills over with sometimes as many as one thousand comments in response to postings on the charged topic of which ancient peoples spread Indo-European languages,19 a highly sensitive issue since as discussed in part II, narratives about the expansion of Indo-European speakers have been used as a basis for building national myths,20 and sometimes have been abused as happened in Nazi Germany.21 The genome bloggers’ political beliefs are fueled partly by the view that when it comes to discussion about biological differences across populations, the academics are not honoring the spirit of scientific truth-seeking. The genome bloggers take pleasure in pointing out contradictions between the politically correct messages academics often give about the indis​tingu​ishab​ility of traits across populations and their papers showing that this is not the way the science is heading.

The largest and most rigorous study that is currently available in this area is the third one commissioned by the British Home Office (Kelly, Lovett, & Regan, 2005). The analysis was based on the 2,643 sexual assault cases (where the outcome was known) that were reported to British police over a 15-year period of time. Of these, 8% were classified by the police department as false reports. Yet the researchers noted that some of these classifications were based simply on the personal judgments of the police investigators, based on the victim’s mental illness, inconsistent statements, drinking or drug use. These classifications were thus made in violation of the explicit policies of their own police agencies. There searchers therefore supplemented the information contained in the police files by collecting many different types of additional data, including: reports from forensic examiners, questionnaires completed by police investigators, interviews with victims and victim service providers, and content analyses of the statements made by victims and witnesses. They then proceeded to evaluate each case using the official criteria for establishing a false allegation, which was that there must be either “a clear and credible admission by the complainant” or “strong evidential grounds” (Kelly, Lovett, & Regan,2005). On the basis of this analysis, the percentage of false reports dropped to 2.5%." Lonsway, Kimberly A., Joanne Archambault, and David Lisak. "False reports: Moving beyond the issue to successfully investigate and prosecute non-stranger sexual assault." The Voice 3.1 (2009): 1-11.

In 2000, for instance, two statisticians were hired by the YMCA—one of the nation’s largest nonprofit organizations—to use the powers of data-driven fortune-telling to make the world a healthier place. The YMCA has more than 2,600 branches in the United States, most of them gyms and community centers. About a decade ago, the organization’s leaders began worrying about how to stay competitive. They asked a social scientist and a mathematician—Bill Lazarus and Dean Abbott—for help. The two men gathered data from more than 150,000 YMCA member satisfaction surveys that had been collected over the years and started looking for patterns. At that point, the accepted wisdom among YMCA executives was that people wanted fancy exercise equipment and sparkling, modern facilities. The YMCA had spent millions of dollars building weight rooms and yoga studios. When the surveys were analyzed, however, it turned out that while a facility’s attractiveness and the availability of workout machines might have caused people to join in the first place, what got them to stay was something else. Retention, the data said, was driven by emotional factors, such as whether employees knew members’ names or said hello when they walked in. People, it turns out, often go to the gym looking for a human connection, not a treadmill. If a member made a friend at the YMCA, they were much more likely to show up for workout sessions. In other words, people who join the YMCA have certain social habits. If the YMCA satisfied them, members were happy. So if the YMCA wanted to encourage people to exercise, it needed to take advantage of patterns that already existed, and teach employees to remember visitors’ names.

All airplanes must carry two black boxes, one of which records instructions sent to all on-board electronic systems. The other is a cockpit voice recorder, enabling investigators to get into the minds of the pilots in the moments leading up to an accident. Instead of concealing failure, or skirting around it, aviation has a system where failure is data rich. In the event of an accident, investigators, who are independent of the airlines, the pilots’ union, and the regulators, are given full rein to explore the wreckage and to interrogate all other evidence. Mistakes are not stigmatized, but regarded as learning opportunities. The interested parties are given every reason to cooperate, since the evidence compiled by the accident investigation branch is inadmissible in court proceedings. This increases the likelihood of full disclosure. In the aftermath of the investigation the report is made available to everyone. Airlines have a legal responsibility to implement the recommendations. Every pilot in the world has free access to the data. This practice enables everyone—rather than just a single crew, or a single airline, or a single nation—to learn from the mistake. This turbocharges the power of learning. As Eleanor Roosevelt put it: “Learn from the mistakes of others. You can’t live long enough to make them all yourself.” And it is not just accidents that drive learning; so, too, do “small” errors. When pilots experience a near miss with another aircraft, or have been flying at the wrong altitude, they file a report. Providing that it is submitted within ten days, pilots enjoy immunity. Many planes are also fitted with data systems that automatically send reports when parameters have been exceeded. Once again, these reports are de-identified by the time they proceed through the report sequence.*

In the introduction, I wrote that COVID had started a war, and nobody won. Let me amend that. Technology won, specifically, the makers of disruptive new technologies and all those who benefit from them. Before the pandemic, American politicians were shaking their fists at the country’s leading tech companies. Republicans insisted that new media was as hopelessly biased against them as traditional media, and they demanded action. Democrats warned that tech giants like Amazon, Facebook, Apple, Alphabet, and Netflix had amassed too much market (and therefore political) power, that citizens had lost control of how these companies use the data they generate, and that the companies should therefore be broken into smaller, less dangerous pieces. European governments led a so-called techlash against the American tech powerhouses, which they accused of violating their customers’ privacy. COVID didn’t put an end to any of these criticisms, but it reminded policymakers and citizens alike just how indispensable digital technologies have become. Companies survived the pandemic only by allowing wired workers to log in from home. Consumers avoided possible infection by shopping online. Specially made drones helped deliver lifesaving medicine in rich and poor countries alike. Advances in telemedicine helped scientists and doctors understand and fight the virus. Artificial intelligence helped hospitals predict how many beds and ventilators they would need at any one time. A spike in Google searches using phrases that included specific symptoms helped health officials detect outbreaks in places where doctors and hospitals are few and far between. AI played a crucial role in vaccine development by absorbing all available medical literature to identify links between the genetic properties of the virus and the chemical composition and effects of existing drugs.

There are two parts to growing as a person—well, no, there aren’t, there’s more, but you can simplify it down—the first is pinpointing problematic areas, the toxic parts, as you said, and cutting them out. You are immensely good at this,” he said, and it sounded a quite genuine compliment, “but it is only one half of the equation. The other part, once you have hollowed out all the offensive parts, is to replace them with healthy, constructive parts. New behaviours; new patterns of thought. Something to nurture those empty spaces back to whole. Because otherwise those holes stay open, and they beg to be filled, and they will collapse on themselves and cause even bigger problems than the things that once lived inside of them. And you, Ronoah? You are singularly lacking in imagination in this respect. You take half the bricks out of a veritable castle of behavioural instinct and you expect it to hold—you never put new ones back in. And I shall tell you why. “There is a difference between action and character. One you change on purpose, but the other, it changes clandestine, without your noticing, until one day you have to run to catch up with where it’s got to. There is a difference between making a mistake, and being a mistake,” he said, tapping Ronoah’s shoulder with one, and then two fingers. “Your problem, Ronoah, quite possibly one of the only problems I can offer that you have not already thought of, is that you are constantly conflating the two. To the everyday eye, character is immovable, immutable—how do you solve a problem when the problem is you? You cannot improve a broken system when the only tool you have with which to do the fixing-up is the system itself. You need new parts, better data—and it just so happens you are discarding a rather sizeable portion of the available data on yourself while you’re at it, which makes your calculations even more erroneous. Because, and get ready for this, it might come as a bit of a shock—because you are not actually broken.

By collecting data from the vast network of doctors across the globe, they added dozens of new compounds to the arsenal—all proven effective against COVID-19. Dr. Kory told me that he was deeply troubled that the extremely successful efforts by scores of front-line doctors to develop repurposed medicines to treat COVID received no support from any government in the entire world—only hostility—much of it orchestrated by Dr. Fauci and the US health agencies. The large universities that rely on hundreds of millions in annual funding from NIH were also antagonistic. “We didn’t have a single academic institution come up with a single protocol,” said Dr. McCullough. “They didn’t even try. Harvard, Johns Hopkins, Duke, you name it. Not a single medical center set up even a tent to try to treat patients and prevent hospitalization and death. There wasn’t an ounce of original research coming out of America available to fight COVID—other than vaccines.” All of these universities are deeply dependent on billions of dollars that they receive from NIH. As we shall see, these institutions live in terror of offending Anthony Fauci, and that fear paralyzed them in the midst of the pandemic. “Dr. Fauci refused to promote any of these interventions,” says Kory. “It’s not just that he made no effort to find effective off-the-shelf cures—he aggressively suppressed them.” Instead of supporting McCullough’s work, NIH and the other federal regulators began actively censoring information on this range of effective remedies. Doctors who attempted merely to open discussion about the potential benefits of early treatments for COVID found themselves heavily and inexplicably censored. Dr. Fauci worked with Facebook’s Mark Zuckerberg and other social media sites to muzzle discussion of any remedies. FDA sent a letter of warning that N-acetyle-L-cysteine (NAC) cannot be lawfully marketed as a dietary supplement, after decades of free access on health food shelves, and suppressed IV vitamin C, which the Chinese were using with extreme effectiveness.

As Graedon scrutinized the FDA’s standards for bioequivalence and the data that companies had to submit, he found that generics were much less equivalent than commonly assumed. The FDA’s statistical formula that defined bioequivalence as a range—a generic drug’s concentration in the blood could not fall below 80 percent or rise above 125 percent of the brand name’s concentration, using a 90 percent confidence interval—still allowed for a potential outside range of 45 percent among generics labeled as being the same. Patients getting switched from one generic to another might be on the low end one day, the high end the next. The FDA allowed drug companies to use different additional ingredients, known as excipients, that could be of lower quality. Those differences could affect a drug’s bioavailability, the amount of drug potentially absorbed into the bloodstream. But there was another problem that really drew Graedon’s attention. Generic drug companies submitted the results of patients’ blood tests in the form of bioequivalence curves. The graphs consisted of a vertical axis called Cmax, which mapped the maximum concentration of drug in the blood, and a horizontal axis called Tmax, the time to maximum concentration. The resulting curve looked like an upside-down U. The FDA was using the highest point on that curve, peak drug concentration, to assess the rate of absorption into the blood. But peak drug concentration, the point at which the blood had absorbed the largest amount of drug, was a single number at one point in time. The FDA was using that point as a stand-in for “rate of absorption.” So long as the generic hit a similar peak of drug concentration in the blood as the brand name, it could be deemed bioequivalent, even if the two curves reflecting the time to that peak looked totally different. Two different curves indicated two entirely different experiences in the body, Graedon realized. The measurement of time to maximum concentration, the horizontal axis, was crucial for time-release drugs, which had not been widely available when the FDA first created its bioequivalence standard in 1992. That standard had not been meaningfully updated since then. “The time to Tmax can vary all over the place and they don’t give a damn,” Graedon emailed a reporter. That “seems pretty bizarre to us.” Though the FDA asserted that it wouldn’t approve generics with “clinically significant” differences in release rates, the agency didn’t disclose data filed by the companies, so it was impossible to know how dramatic the differences were.

The textbooks of history prepared for the public schools are marked by a rather naive parochialism and chauvinism. There is no need to dwell on such futilities. But it must be admitted that even for the most conscientious historian abstention from judgments of value may offer certain difficulties. As a man and as a citizen the historian takes sides in many feuds and controversies of his age. It is not easy to combine scientific aloofness in historical studies with partisanship in mundane interests. But that can and has been achieved by outstanding historians. The historian's world view may color his work. His representation of events may be interlarded with remarks that betray his feelings and wishes and divulge his party affiliation. However, the postulate of scientific history's abstention from value judgments is not infringed by occasional remarks expressing the preferences of the historian if the general purport of the study is not affected. If the writer, speaking of an inept commander of the forces of his own nation or party, says "unfortunately" the general was not equal to his task, he has not failed in his duty as a historian. The historian is free to lament the destruction of the masterpieces of Greek art provided his regret does not influence his report of the events that brought about this destruction. The problem of Wertfreíheit must also be clearly distinguished from that of the choice of theories resorted to for the interpretation of facts. In dealing with the data available, the historian needs ali the knowledge provided by the other disciplines, by logic, mathematics, praxeology, and the natural sciences. If what these disciplines teach is insufficient or if the historian chooses an erroneous theory out of several conflicting theories held by the specialists, his effort is misled and his performance is abortive. It may be that he chose an untenable theory because he was biased and this theory best suited his party spirit. But the acceptance of a faulty doctrine may often be merely the outcome of ignorance or of the fact that it enjoys greater popularity than more correct doctrines. The main source of dissent among historians is divergence in regard to the teachings of ali the other branches of knowledge upon which they base their presentation. To a historian of earlier days who believed in witchcraft, magic, and the devil's interference with human affairs, things hàd a different aspect than they have for an agnostic historian. The neomercantilist doctrines of the balance of payments and of the dollar shortage give an image of presentday world conditions very different from that provided by an examination of the situation from the point of view of modern subjectivist economics.

What is scarce? Surely time is scarce? This is true in the sense that we get only one life, but yet again there are ways in which competition and how we use our time can make us feel an artificial sense of time scarcity. Each time we are able to build on the work of others with confidence, each time we use the elements of life pulled from our commonwealth of agricultural knowledge, we bundle time, and so get the benefit of having multiple lifetimes. Each time nature uses genetic code that has been developed over millions of years, millions of years of development are collapsed into something that works in our lifetimes. Each time we add to that collection, we are putting our lifetimes' work into a useful form for the benefit of future generations. At the same time, yes, we each have only our own single lives in which to pursue happiness. The goal is to spend as much of that time in a framework of sharing abundance rather than having it squeezed into a life of scarcity and competition. In contrast, we need not look far to find lots of frustrating examples in which our time is treated as abundant when we would rather have it be valued as scarce. It happens each time we must stand in line at the DMV, fill out redundant forms at the hospital, reproduce others' efforts by spending time searching for knowledge or data that already exists somewhere, create a report that no one reads. In those cases, we are creating and living in artificial and unnecessary time scarcity. Time is indeed one of the most curious elements of life, especially since our lifetimes and those of plants and animals all move at different rates. We know, for example, that the urgency to address climate change is really on our human scale, not geologic scale. The Earth has been through greater upheavals and mass extinctions and will likely go through them again, but for the narrowest of narrow bands of human history on Earth, we require very specific conditions for us to continue to thrive as a species. To keep our planet within a habitable and abundant balance, we have, as Howard Buffet noted, only 'forty seasons' to learn and adjust. That is why building on one another's work is so important. One farmer can have the benefit of forty seasons and pass some of that experience down, but if 1,000 farmers do the same, there is the collective benefit of 1,000 years in a single year. If a million people participate, then a million years of collective experience are available. If we are then able to compound knowledge across generations and deepen our understanding of human and natural history, we add even greater richness. It is in this way of bundling our experiences for continual improvement, with compound interest, that time shifts from a scarce resource to being far less of a constraint, if not truly abundant. However, for time to be compounded, knowledge must be shared, and real resources, energy, and infrastructure must exist and function to support and grow our commonwealth of knowledge.

Henry, there’s something I would like to tell you, for what it’s worth, something I wish I had been told years ago. You’ve been a consultant for a long time, and you’ve dealt a great deal with top secret information. But you’re about to receive a whole slew of special clearances, maybe fifteen or twenty of them, that are higher than top secret. I’ve had a number of these myself, and I’ve known other people who have just acquired them, and I have a pretty good sense of what the effects of receiving these clearances are on a person who didn’t previously know they even existed. And the effects of reading the information that they will make available to you. First, you’ll be exhilarated by some of this new information, and by having it all—so much! incredible!—suddenly available to you. But second, almost as fast, you will feel like a fool for having studied, written, talked about these subjects, criticized and analyzed decisions made by presidents for years without having known of the existence of all this information, which presidents and others had and you didn’t, and which must have influenced their decisions in ways you couldn’t even guess. In particular, you’ll feel foolish for having literally rubbed shoulders for over a decade with some officials and consultants who did have access to all this information you didn’t know about and didn’t know they had, and you’ll be stunned that they kept that secret from you so well. You will feel like a fool, and that will last for about two weeks. Then, after you’ve started reading all this daily intelligence input and become used to using what amounts to whole libraries of hidden information, which is much more closely held than mere top secret data, you will forget there ever was a time when you didn’t have it, and you’ll be aware only of the fact that you have it now and most others don’t … and that all those other people are fools. Over a longer period of time—not too long, but a matter of two or three years—you’ll eventually become aware of the limitations of this information. There is a great deal that it doesn’t tell you, it’s often inaccurate, and it can lead you astray just as much as the New York Times can. But that takes a while to learn. In the meantime it will have become very hard for you to learn from anybody who doesn’t have these clearances. Because you’ll be thinking as you listen to them: “What would this man be telling me if he knew what I know? Would he be giving me the same advice, or would it totally change his predictions and recommendations?” And that mental exercise is so torturous that after a while you give it up and just stop listening. I’ve seen this with my superiors, my colleagues … and with myself. You will deal with a person who doesn’t have those clearances only from the point of view of what you want him to believe and what impression you want him to go away with, since you’ll have to lie carefully to him about what you know. In effect, you will have to manipulate him. You’ll give up trying to assess what he has to say. The danger is, you’ll become something like a moron. You’ll become incapable of learning from most people in the world, no matter how much experience they may have in their particular areas that may be much greater than yours.