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Barriers to COVID-19 Testing and Treatment: Immigrants without Health Coverage in the United States

As millions of U.S. workers lose jobs and the health insurance associated with them, Medicaid and similar programs are increasingly important for people seeking COVID-19 testing and treatment. Yet many low-income uninsured noncitizens, including green-card holders, are excluded from such programs because of their immigration status, as this fact sheet explores.




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Reflections on Business, Leadership, and Branding: Shelly Lazarus ’70

Much has changed in the world of advertising from the picture painted by Mad Men. Shelly Lazarus ’70, Chairman Emeritus, Ogilvy & Mather, was one of the women helping pioneer these changes. Making the journey from ‘the only woman in the room’ to CEO and Chairman of Ogilvy gives Lazarus a lot to reflect on […]




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Thinking with AND: Insights from KIND’s story

“I’m a confused Mexican Jew.” So says Daniel Lubetzky, Founder and CEO of KIND Snack, in his very personal interview with Columbia faculty member David Rogers at BRITE ’16. Their discussion touched on the many ideas behind KIND Snacks, from the beginnings of the company, to the strategic thinking that forces Lubetzky to stay away […]




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Algorhythms for Marketing Transformation

We all understand that digital media, data, and analytics are driving transformations in society and business. Most marketers are now armed with case studies of what can be done differently, but many are still challenged with how to truly develop new ideas and execute new strategies to grow their business. Mitch Joel, President of Mirum […]




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Evaluating the Effect of U-500 Insulin Therapy on Glycemic Control in Veterans With Type 2 Diabetes

Joseph A. Granata
Jan 1, 2015; 33:14-19
Feature Articles




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Case Study: Potential Pitfalls of Using Hemoglobin A1c as the Sole Measure of Glycemic Control

Huy A. Tran
Jul 1, 2004; 22:141-143
Case Studies




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Diabetes and Periodontal Infection: Making the Connection

Janet H. Southerland
Oct 1, 2005; 23:171-178
Feature Articles




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Clarifying the Role of Insulin in Type 2 Diabetes Management

John R. White
Jan 1, 2003; 21:
Feature Articles




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Diapression: An Integrated Model for Understanding the Experience of Individuals With Co-Occurring Diabetes and Depression

Paul Ciechanowski
Apr 1, 2011; 29:43-49
Feature Articles




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Self-Monitoring of Blood Glucose: The Basics

Evan M. Benjamin
Jan 1, 2002; 20:
Practical Pointers




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Persistence of Continuous Glucose Monitoring Use in a Community Setting 1 Year After Purchase

James Chamberlain
Jul 1, 2013; 31:106-109
Feature Articles




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Opportunities and Challenges for Biosimilars: What's on the Horizon in the Global Insulin Market?

Lisa S. Rotenstein
Oct 1, 2012; 30:138-150
Features




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Health Care Transition in Adolescents and Young Adults With Diabetes

Michael E. Bowen
Jun 1, 2010; 28:99-106
Feature Articles




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Building Therapeutic Relationships: Choosing Words That Put People First

Jane K. Dickinson
Jan 1, 2017; 35:51-54
Commentary




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Application of Adult-Learning Principles to Patient Instructions: A Usability Study for an Exenatide Once-Weekly Injection Device

Gayle Lorenzi
Sep 1, 2010; 28:157-162
Bridges to Excellence




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Engaging Patients in Education for Self-Management in an Accountable Care Environment

Christine A. Beebe
Jul 1, 2011; 29:123-126
Practical Pointers




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Helping Patients Make and Sustain Healthy Changes: A Brief Introduction to Motivational Interviewing in Clinical Diabetes Care

Michele Heisler
Oct 1, 2008; 26:161-165
Practical Pointers




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Diabetes Self-Management in a Community Health Center: Improving Health Behaviors and Clinical Outcomes for Underserved Patients

Daren Anderson
Jan 1, 2008; 26:22-27
Bridges to Excellence




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Cardiac Manifestations of Congenital Generalized Lipodystrophy

Vani P. Sanon
Oct 1, 2016; 34:181-186
Feature Articles




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Perspectives in Gestational Diabetes Mellitus: A Review of Screening, Diagnosis, and Treatment

Jennifer M. Perkins
Apr 1, 2007; 25:57-62
Feature Articles




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What's So Tough About Taking Insulin? Addressing the Problem of Psychological Insulin Resistance in Type 2 Diabetes

William H. Polonsky
Jul 1, 2004; 22:147-150
Practical Pointers




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Improving Patient Adherence

Alan M. Delamater
Apr 1, 2006; 24:71-77
Feature Articles




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10 Examples of Heroism Arising From the COVID-19 Pandemic

By Scott T. Allison In any tragedy or crisis, you will see many people standing out and stepping up to save lives and make the world a better place. These heroic individuals can range from leaders of nations to ordinary citizens who rise to the occasion to help others in need. During this COVID-19 pandemic, … Continue reading 10 Examples of Heroism Arising From the COVID-19 Pandemic




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Baseball and Linguistic Uncertainty

In my youth I played an inordinate amount of baseball, collected baseball cards, and idolized baseball players. I've outgrown all that but when I'm in the States during baseball season I do enjoy watching a few innings on the TV.

So I was watching a baseball game recently and the commentator was talking about the art of pitching. Throwing a baseball, he said, is like shooting a shotgun. You get a spray. As a pitcher, you have to know your spray. You learn to control it, but you know that it is there. The ball won't always go where you want it. And furthermore, where you want the ball depends on the batter's style and strategy, which vary from pitch to pitch for every batter.

That's baseball talk, but it stuck in my mind. Baseball pitchers must manage uncertainty! And it is not enough to reduce it and hope for the best. Suppose you want to throw a strike. It's not a good strategy to aim directly at, say, the lower outside corner of the strike zone, because of the spray of the ball's path and because the batter's stance can shift. Especially if the spray is skewed down and out, you'll want to move up and in a bit.

This is all very similar to the ambiguity of human speech when we pitch words at each other. Words don't have precise meanings; meanings spread out like the pitcher's spray. If we want to communicate precisely we need to be aware of this uncertainty, and manage it, taking account of the listener's propensities.

Take the word "liberal" as it is used in political discussion.

For many decades, "liberals" have tended to support high taxes to provide generous welfare, public medical insurance, and low-cost housing. They advocate liberal (meaning magnanimous or abundant) government involvement for the citizens' benefit.

A "liberal" might also be someone who is open-minded and tolerant, who is not strict in applying rules to other people, or even to him or herself. Such a person might be called "liberal" (meaning advocating individual rights) for opposing extensive government involvement in private decisions. For instance, liberals (in this second sense) might oppose high taxes since they reduce individuals' ability to make independent choices. As another example, John Stuart Mill opposed laws which restricted the rights of women to work (at night, for instance), even though these laws were intended to promote the welfare of women. Women, insisted Mill, are intelligent adults and can judge for themselves what is good for them.

Returning to the first meaning of "liberal" mentioned above, people of that strain may support restrictions of trade to countries which ignore the health and safety of workers. The other type of "liberal" might tend to support unrestricted trade.

Sending out words and pitching baseballs are both like shooting a shotgun: meanings (and baseballs) spray out. You must know what meaning you wish to convey, and what other meanings the word can have. The choice of the word, and the crafting of its context, must manage the uncertainty of where the word will land in the listener's mind.


Let's go back to baseball again.

If there were no uncertainty in the pitcher's pitch and the batter's swing, then baseball would be a dreadfully boring game. If the batter knows exactly where and when the ball will arrive, and can completely control the bat, then every swing will be a homer. Or conversely, if the pitcher always knows exactly how the batter will swing, and if each throw is perfectly controlled, then every batter will strike out. But which is it? Whose certainty dominates? The batter's or the pitcher's? It can't be both. There is some deep philosophical problem here. Clearly there cannot be complete certainty in a world which has some element of free will, or surprise, or discovery. This is not just a tautology, a necessary result of what we mean by "uncertainty" and "surprise". It is an implication of limited human knowledge. Uncertainty - which makes baseball and life interesting - is inevitable in the human world.

How does this carry over to human speech?

It is said of the Wright brothers that they thought so synergistically that one brother could finish an idea or sentence begun by the other. If there is no uncertainty in what I am going to say, then you will be bored with my conversation, or at least, you won't learn anything from me. It is because you don't know what I mean by, for instance, "robustness", that my speech on this topic is enlightening (and maybe interesting). And it is because you disagree with me about what robustness means (and you tell me so), that I can perhaps extend my own understanding.

So, uncertainty is inevitable in a world that is rich enough to have surprise or free will. Furthermore, this uncertainty leads to a process - through speech - of discovery and new understanding. Uncertainty, and the use of language, leads to discovery.

Isn't baseball an interesting game?




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Robustness and Locke's Wingless Gentleman

Our ancestors have made decisions under uncertainty ever since they had to stand and fight or run away, eat this root or that berry, sleep in this cave or under that bush. Our species is distinguished by the extent of deliberate thought preceding decision. Nonetheless, the ability to decide in the face of the unknown was born from primal necessity. Betting is one of the oldest ways of deciding under uncertainty. But you bet you that 'bet' is a subtler concept than one might think.

We all know what it means to make a bet, but just to make sure let's quote the Oxford English Dictionary: "To stake or wager (a sum of money, etc.) in support of an affirmation or on the issue of a forecast." The word has been around for quite a while. Shakespeare used the verb in 1600: "Iohn a Gaunt loued him well, and betted much money on his head." (Henry IV, Pt. 2 iii. ii. 44). Drayton used the noun in 1627 (and he wasn't the first): "For a long while it was an euen bet ... Whether proud Warwick, or the Queene should win."

An even bet is a 50-50 chance, an equal probability of each outcome. But betting is not always a matter of chance. Sometimes the meaning is just the opposite. According to the OED 'You bet' or 'You bet you' are slang expressions meaning 'be assured, certainly'. For instance: "'Can you handle this outfit?' 'You bet,' said the scout." (D.L.Sayers, Lord Peter Views Body, iv. 68). Mark Twain wrote "'I'll get you there on time' - and you bet you he did, too." (Roughing It, xx. 152).

So 'bet' is one of those words whose meaning stretches from one idea all the way to its opposite. Drayton's "even bet" between Warwick and the Queen means that he has no idea who will win. In contrast, Twain's "you bet you" is a statement of certainty. In Twain's or Sayers' usage, it's as though uncertainty combines with moral conviction to produce a definite resolution. This is a dialectic in which doubt and determination form decisiveness.

John Locke may have had something like this in mind when he wrote:

"If we will disbelieve everything, because we cannot certainly know all things; we shall do muchwhat as wisely as he, who would not use his legs, but sit still and perish, because he had no wings to fly." (An Essay Concerning Human Understanding, 1706, I.i.5)

The absurdity of Locke's wingless gentleman starving in his chair leads us to believe, and to act, despite our doubts. The moral imperative of survival sweeps aside the paralysis of uncertainty. The consequence of unabated doubt - paralysis - induces doubt's opposite: decisiveness.

But rational creatures must have some method for reasoning around their uncertainties. Locke does not intend for us to simply ignore our ignorance. But if we have no way to place bets - if the odds simply are unknown - then what are we to do? We cannot "sit still and perish".

This is where the strategy of robustness comes in.

'Robust' means 'Strong and hardy; sturdy; healthy'. By implication, something that is robust is 'not easily damaged or broken, resilient'. A statistical test is robust if it yields 'approximately correct results despite the falsity of certain of the assumptions underlying it' or despite errors in the data. (OED)

A decision is robust if its outcome is satisfactory despite error in the information and understanding which justified or motivated the decision. A robust decision is resilient to surprise, immune to ignorance.

It is no coincidence that the colloquial use of the word 'bet' includes concepts of both chance and certainty. A good bet can tolerate large deviation from certainty, large error of information. A good bet is robust to surprise. 'You bet you' does not mean that the world is certain. It means that the outcome is certain to be acceptable, regardless of how the world turns out. The scout will handle the outfit even if there is a rogue in the ranks; Twain will get there on time despite snags and surprises. A good bet is robust to the unknown. You bet you!


An extended and more formal discussion of these issues can be found elsewhere.




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Beware the Rareness Illusion When Exploring the Unknown

Here's a great vacation idea. Spend the summer roaming the world in search of the 10 lost tribes of Israel, exiled from Samaria by the Assyrians 2700 years ago (2 Kings 17:6). Or perhaps you'd like to search for Prester John, the virtuous ruler of a kingdom lost in the Orient? Or would you rather trace the gold-laden kingdom of Ophir (1 Kings 9:28)? Or do you prefer the excitement of tracking the Amazons, that nation of female warriors? Or perhaps the naval power mentioned by Plato, operating from the island of Atlantis? Or how about unicorns, or the fountain of eternal youth? The Unknown is so vast that the possibilities are endless.

Maybe you don't believe in unicorns. But Plato evidently "knew" about the island of Atlantis. The conquest of Israel is known from Assyrian archeology and from the Bible. That you've never seen a Reubenite or a Naphtalite (or a unicorn) means that they don't exist?

It is true that when something really does not exist, one might spend a long time futilely looking for it. Many people have spent enormous energy searching for lost tribes, lost gold, and lost kingdoms. Why is it so difficult to decide that what you're looking for really isn't there? The answer, ironically, is that the world has endless possibilities for discovery and surprise.

Let's skip vacation plans and consider some real-life searches. How long should you (or the Libyans) look for Muammar Qaddafi? If he's not in the town of Surt, maybe he's Bani Walid, or Algeria, or Timbuktu? How do you decide he cannot be found? Maybe he was pulverized by a NATO bomb. It's urgent to find the suicide bomber in the crowded bus station before it's too late - if he's really there. You'd like to discover a cure for AIDS, or a method to halt the rising global temperature, or a golden investment opportunity in an emerging market, or a proof of the parallel postulate of Euclidean geometry.

Let's focus our question. Suppose you are looking for something, and so far you have only "negative" evidence: it's not here, it's not there, it's not anywhere you've looked. Why is it so difficult to decide, conclusively and confidently, that it simply does not exist?

This question is linked to a different question: how to make the decision that "it" (whatever it is) does not exist. We will focus on the "why" question, and leave the "how" question to students of decision theories such as statistics, fuzzy logic, possibility theory, Dempster-Shafer theory and info-gap theory. (If you're interested in an info-gap application to statistics, here is an example.)

Answers to the "why" question can be found in several domains.

Psychology provides some answers. People can be very goal oriented, stubborn, and persistent. Marco Polo didn't get to China on a 10-hour plane flight. The round trip took him 24 years, and he didn't travel business class.

Ideology is a very strong motivator. When people believe something strongly, it is easy for them to ignore evidence to the contrary. Furthermore, for some people, the search itself is valued more than the putative goal.

The answer to the "why" question that I will focus on is found by contemplating The Endless Unknown. It is so vast, so unstructured, so, well ..., unknown, that we cannot calibrate our negative evidence to decide that whatever we're looking for just ain't there.

I'll tell a true story.

I was born in the US and my wife was born in Israel, but our life-paths crossed, so to speak, before we were born. She had a friend whose father was from Europe and lived for a while - before the friend was born - with a cousin of his in my home town. This cousin was - years later - my 3rd grade teacher. My school teacher was my future wife's friend's father's cousin.

Amazing coincidence. This convoluted sequence of events is certainly rare. How many of you can tell the very same story? But wait a minute. This convoluted string of events could have evolved in many many different ways, each of which would have been an equally amazing coincidence. The number of similar possible paths is namelessly enormous, uncountably humongous. In other words, potential "rare" events are very numerous. Now that sounds like a contradiction (we're getting close to some of Zeno's paradoxes, and Aristotle thought Zeno was crazy). It is not a contradiction; it is only a "rareness illusion" (something like an optical illusion). The specific event sequence in my story is unique, which is the ultimate rarity. We view this sequence as an amazing coincidence because we cannot assess the number of similar sequences. Surprising strings of events occur not infrequently because the number of possible surprising strings is so unimaginably vast. The rareness illusion is the impression of rareness arising from our necessary ignorance of the vast unknown. "Necessary" because, by definition, we cannot know what is unknown. "Vast" because the world is so rich in possibilities.

The rareness illusion is a false impression, a mistake. For instance, it leads people to wrongly goggle at strings of events - rare in themselves - even though "rare events" are numerous and "amazing coincidences" occur all the time. An appreciation of the richness and boundlessness of the Unknown is an antidote for the rareness illusion.

Recognition of the rareness illusion is the key to understanding why it is so difficult to confidently decide, based on negative evidence, that what you're looking for simply does not exist.

One might be inclined to reason as follows. If you're looking for something, then look very thoroughly, and if you don't find it, then it's not there. That is usually sound and sensible advice, and often "looking thoroughly" will lead to discovery.

However, the number of ways that we could overlook something that really is there is enormous. It is thus very difficult to confidently conclude that the search was thorough and that the object cannot be found. Take the case of your missing house keys. They dropped from your pocket in the car, or on the sidewalk and somebody picked them up, or you left them in the lock when you left the house, or or or .... Familiarity with the rareness illusion makes it very difficult to decide that you have searched thoroughly. If you think that the only contingencies not yet explored are too exotic to be relevant (a raven snatched them while you were daydreaming about that enchanting new employee), then think again, because you've been blinded by a rareness illusion. The number of such possibilities is so vastly unfathomable that you cannot confidently say that all of them are collectively negligible. Recognition of the rareness illusion prevents you from confidently concluding that what you are seeking simply does not exist.

Many quantitative tools grapple with the rareness illusion. We mentioned some decision theories earlier. But because the rareness illusion derives from our necessary ignorance of the vast unknown, one must always beware.

Looking for an exciting vacation? The Endless Unknown is the place to go. 




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The Language of Science and the Tower of Babel


And God said: Behold one people with one language for them all ... and now nothing that they venture will be kept from them. ... [And] there God mixed up the language of all the land. (Genesis, 11:6-9)

"Philosophy is written in this grand book the universe, which stands continually open to our gaze. But the book cannot be understood unless one first learns to comprehend the language and to read the alphabet in which it is composed. It is written in the language of mathematics." Galileo Galilei

Language is power over the unknown. 

Mathematics is the language of science, and computation is the modern voice in which this language is spoken. Scientists and engineers explore the book of nature with computer simulations of swirling galaxies and colliding atoms, crashing cars and wind-swept buildings. The wonders of nature and the powers of technological innovation are displayed on computer screens, "continually open to our gaze." The language of science empowers us to dispel confusion and uncertainty, but only with great effort do we change the babble of sounds and symbols into useful, meaningful and reliable communication. How we do that depends on the type of uncertainty against which the language struggles.

Mathematical equations encode our understanding of nature, and Galileo exhorts us to learn this code. One challenge here is that a single equation represents an infinity of situations. For instance, the equation describing a flowing liquid captures water gushing from a pipe, blood coursing in our veins, and a droplet splashing from a puddle. Gazing at the equation is not at all like gazing at the droplet. Understanding grows by exposure to pictures and examples. Computations provide numerical examples of equations that can be realized as pictures. Computations can simulate nature, allowing us to explore at our leisure.

Two questions face the user of computations: Are we calculating the correct equations? Are we calculating the equations correctly? The first question expresses the scientist's ignorance - or at least uncertainty - about how the world works. The second question reflects the programmer's ignorance or uncertainty about the faithfulness of the computer program to the equations. Both questions deal with the fidelity between two entities. However, the entities involved are very different and the uncertainties are very different as well.

The scientist's uncertainty is reduced by the ingenuity of the experimenter. Equations make predictions that can be tested by experiment. For instance, Galileo predicted that small and large balls will fall at the same rate, as he is reported to have tested from the tower of Pisa. Equations are rejected or modified when their predictions don't match the experimenter's observation. The scientist's uncertainty and ignorance are whittled away by testing equations against observation of the real world. Experiments may be extraordinarily subtle or difficult or costly because nature's unknown is so endlessly rich in possibilities. Nonetheless, observation of nature remorselessly cuts false equations from the body of scientific doctrine. God speaks through nature, as it were, and "the Eternal of Israel does not deceive or console." (1 Samuel, 15:29). When this observational cutting and chopping is (temporarily) halted, the remaining equations are said to be "validated" (but they remain on the chopping block for further testing).

The programmer's life is, in one sense, more difficult than the experimenter's. Imagine a huge computer program containing millions of lines of code, the accumulated fruit of thousands of hours of effort by many people. How do we verify that this computation faithfully reflects the equations that have ostensibly been programmed? Of course they've been checked again and again for typos or logical faults or syntactic errors. Very clever methods are available for code verification. Nonetheless, programmers are only human, and some infidelity may slip through. What remorseless knife does the programmer have with which to verify that the equations are correctly calculated? Testing computation against observation does not allow us to distinguish between errors in the equations, errors in the program, and compensatory errors in both.

The experimenter compares an equation's prediction against an observation of nature. Like the experimenter, the programmer compares the computation against something. However, for the programmer, the sharp knife of nature is not available. In special cases the programmer can compare against a known answer. More frequently the programmer must compare against other computations which have already been verified (by some earlier comparison). The verification of a computation - as distinct from the validation of an equation - can only use other high-level human-made results. The programmer's comparisons can only be traced back to other comparisons. It is true that the experimenter's tests are intermediated by human artifacts like calipers or cyclotrons. Nonetheless, bedrock for the experimenter is the "reality out there". The experimenter's tests can be traced back to observations of elementary real events. The programmer does not have that recourse. One might say that God speaks to the experimenter through nature, but the programmer has no such Voice upon which to rely.

The tower built of old would have reached the heavens because of the power of language. That tower was never completed because God turned talk into babble and dispersed the people across the land. Scholars have argued whether the story prescribes a moral norm, or simply describes the way things are, but the power of language has never been disputed.

The tower was never completed, just as science, it seems, has a long way to go. Genius, said Edison, is 1 percent inspiration and 99 percent perspiration. A good part of the sweat comes from getting the language right, whether mathematical equations or computer programs.

Part of the challenge is finding order in nature's bubbling variety. Each equation captures a glimpse of that order, adding one block to the structure of science. Furthermore, equations must be validated, which is only a stop-gap. All blocks crumble eventually, and all equations are fallible and likely to be falsified.

Another challenge in science and engineering is grasping the myriad implications that are distilled into an equation. An equation compresses and summarizes, while computer simulations go the other way, restoring detail and specificity. The fidelity of a simulation to the equation is usually verified by comparing against other simulations. This is like the dictionary paradox: using words to define words.

It is by inventing and exploiting symbols that humans have constructed an orderly world out of the confusing tumult of experience. With symbols, like with blocks in the tower, the sky is the limit.




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Picking a Theory is Like Building a Boat at Sea


"We are like sailors who on the open sea must reconstruct their ship
 but are never able to start afresh from the bottom." 
Otto Neurath's analogy in the words of Willard V. Quine

Engineers, economists, social planners, security strategists, and others base their plans and decisions on theories. They often argue long and hard over which theory to use. Is it ever right to use a theory that we know is empirically wrong, especially if a true (or truer) theory is available? Why is it so difficult to pick a theory?

Let's consider two introductory examples.

You are an engineer designing a robot. You must calculate the forces needed to achieve specified motions of the robotic arms. You can base these calculations on either of two theories. One theory assumes that an object comes to rest unless a force acts upon it. Let's call this axiom A. The other theory assumes that an object moves at constant speed unless a force acts upon it. Let's call this axiom G. Axiom A agrees with observation: Nothing moves continuously without the exertion of force; an object will come to rest unless you keep pushing it. Axiom G contradicts all observation; no experiment illustrates the perpetual motion postulated by the axiom. If all else is the same, which theory should you choose?

Axiom A is Aristotle's law of inertia, which contributed little to the development of mechanical dynamics. Axiom G is Galileo's law of inertia: one of the most fruitful scientific ideas of all time. Why is an undemonstrable assertion - axiom G - a good starting point for a theory?

Consider another example.

You are an economist designing a market-based policy to induce firms to reduce pollution. You will use an economic theory to choose between policies. One theory assumes that firms face pure competition, meaning that no single firm can influence market prices. Another theory provides agent-based game-theoretic characterization of how firms interact (without colluding) by observing and responding to price behavior of other firms and of consumers.

Pure competition is a stylized idealization (like axiom G). Game theory is much more realistic (like axiom A), but may obscure essential patterns in its massive detail. Which theory should you use?

We will not address the question of how to choose a theory upon which to base a decision. We will focus on the question: why is theory selection so difficult? We will discuss four trade offs.

"Thanks to the negation sign, there are as many truths as falsehoods;
we just can't always be sure which are which." Willard V. Quine

The tension between right and right. The number of possible theories is infinite, and sometimes it's hard to separate the wheat from the chaff, as suggested by the quote from Quine. As an example, I have a book called A Modern Guide to Macroeconomics: An Introduction to Competing Schools of Thought by Snowdon, Vane and Wynarczyk. It's a wonderful overview of about a dozen theories developed by leading economic scholars, many of them Nobel Prize Laureates. The theories are all fundamentally different. They use different axioms and concepts and they compete for adoption by economists. These theories have been studied and tested upside down and backwards. However, economic processes are very complex and variable, and the various theories succeed in different ways or in different situations, so the jury is still out. The choice of a theory is no simple matter because many different theories can all seem right in one way or another.

"The fox knows many things, but the hedgehog knows one big thing." Archilochus

The fox-hedgehog tension. This aphorism by Archilochus metaphorically describes two types of theories (and two types of people). Fox-like theories are comprehensive and include all relevant aspects of the problem. Hedgehog-like theories, in contrast, skip the details and focus on essentials. Axiom A is fox-like because the complications of friction are acknowledged from the start. Axiom G is hedgehog-like because inertial resistance to change is acknowledged but the complications of friction are left for later. It is difficult to choose between these types of theories because it is difficult to balance comprehensiveness against essentialism. On the one hand, all relevant aspects of the problem should be considered. On the other hand, don't get bogged down in endless details. This fox-hedgehog tension can be managed by weighing the context, goals and implications of the decision. We won't expand on this idea since we're not considering how to choose a theory; we're only examining why it's a difficult choice. However, the idea of resolving this tension by goal-directed choice motivates the third tension.

"Beyond this island of meanings which in their own nature are true or false
lies the ocean of meanings to which truth and falsity are irrelevant." John Dewey

The truth-meaning tension. Theories are collections of statements like axioms A and G in our first example. Statements carry meaning, and statements can be either true or false. Truth and meaning are different. For instance, "Archilochus was a Japanese belly dancer" has meaning, but is not true. The quote from Dewey expresses the idea that "meaning" is a broader description of statements than "truth". All true statements mean something, but not all meaningful statements are true. That does not imply, however, that all untrue meaningful statements are false, as we will see.

We know the meanings of words and sentences from experience with language and life. A child learns the meanings of words - chair, mom, love, good, bad - by experience. Meanings are learned by pointing - this is a chair - and also by experiencing what it means to love or to be good or bad.

Truth is a different concept. John Dewey wrote that

"truths are but one class of meanings, namely, those in which a claim to verifiability by their consequences is an intrinsic part of their meaning. Beyond this island of meanings which in their own nature are true or false lies the ocean of meanings to which truth and falsity are irrelevant. We do not inquire whether Greek civilization was true or false, but we are immensely concerned to penetrate its meaning."

A true statement, in Dewey's sense, is one that can be confirmed by experience. Many statements are meaningful, even important and useful, but neither true nor false in this experimental sense. Axiom G is an example.

Our quest is to understand why the selection of a theory is difficult. Part of the challenge derives from the tension between meaning and truth. We select a theory for use in formulating and evaluating a plan or decision. The decision has implications: what would it mean to do this rather than that? Hence it is important that the meaning of the theory fit the context of the decision. Indeed, hedgehogs would say that getting the meaning and implication right is the essence of good decision making.

But what if a relevantly meaningful theory is unprovable or even false? Should we use a theory that is meaningful but not verifiable by experience? Should we use a meaningful theory that is even wrong? This quandary is related to the fox-hedgehog tension because the fox's theory is so full of true statements that its meaning may be obscured, while the hedgehog's bare-bones theory has clear relevance to the decision to be made, but may be either false or too idealized to be tested.

Galileo's axiom of inertia is an idealization that is unsupported by experience because friction can never be avoided. Axiom G assumes conditions that cannot be realized so the axiom can never be tested. Likewise, pure competition is an idealization that is rarely if ever encountered in practice. But these theories capture the essence of many situations. In practical terms, what it means to get the robotic arm from here to there is to apply net forces that overcome Galilean inertia. But actually designing a robot requires considering details of dissipative forces like friction. What it means to be a small business is that the market price of your product is beyond your control. But actually running a business requires following and reacting to prices in the store next door.

It is difficult to choose between a relevantly meaningful but unverifiable theory, and a true theory that is perhaps not quite what we mean.

The knowledge-ignorance tension. Recall that we are discussing theories in the service of decision-making by engineers, social scientists and others. A theory should facilitate the use of our knowledge and understanding. However, in some situations our ignorance is vast and our knowledge will grow. Hence a theory should also account for ignorance and be able to accommodate new knowledge.

Let's take an example from theories of decision. The independence axiom is fundamental in various decision theories, for instance in von Neumann-Morgenstern expected utility theory. It says that one's choices should be independent of irrelevant alternatives. Suppose you are offered the dinner choice between chicken and fish, and you choose chicken. The server returns a few minutes later saying that beef is also available. If you switch your choice from chicken to fish you are violating the independence axiom. You prefer beef less than both chicken and fish, so the beef option shouldn't alter the fish-chicken preference.

But let's suppose that when the server returned and mentioned beef, your physician advised you to reduce your cholesterol intake (so your preference for beef is lowest) which prompted your wife to say that you should eat fish at least twice a week because of vitamins in the oil. So you switch from chicken to fish. Beef is not chosen, but new information that resulted from introducing the irrelevant alternative has altered the chicken-fish preference.

One could argue for the independence axiom by saying that it applies only when all relevant information (like considerations of cholesterol and fish oil) are taken into account. On the other hand, one can argue against the independence axiom by saying that new relevant information quite often surfaces unexpectedly. The difficulty is to judge the extent to which ignorance and the emergence of new knowledge should be central in a decision theory.

Wrapping up. Theories express our knowledge and understanding about the unknown and confusing world. Knowledge begets knowledge. We use knowledge and understanding - that is, theory - in choosing a theory. The process is difficult because it's like building a boat on the open sea as Otto Neurath once said. 




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Genesis for Engineers

Technology has come a long way since Australopithecus first bruised their fingers chipping flint to make knives and scrapers. We are blessed to fruitfully multiply, to fill the world and to master it (Genesis 1:28). And indeed the trend of technological history is towards increasing mastery over our world. Inventors deliberately invent, but many inventions are useless or even harmful. Why is there progress and how certain is the process? Part of the answer is that good ideas catch on and bad ones get weeded out. Reality, however, is more complicated: what is 'good' or 'bad' is not always clear; unintended consequences cannot be predicted; and some ideas get lost while others get entrenched. Mastering the darkness and chaos of creation is a huge engineering challenge. But more than that, progress is painful and uncertain and the challenge is not only technological.

An example of the weeding-out process, by which our mastery improves, comes to us in Hammurabi's code of law from 38 centuries ago:

"If a builder build a house for some one, and does not construct it properly, and the house which he built fall in and kill its owner, then that builder shall be put to death. If it kill the son of the owner the son of that builder shall be put to death." (Articles 229-230)

Builders who use inferior techniques, or who act irresponsibly, will be ruthlessly removed. Hammurabi's law doesn't say what techniques to use; it is a mechanism for selecting among techniques. As the level of competence rises and the rate of building collapse decreases, the law remains the same, implicitly demanding better performance after each improvement.

Hammurabi's law establishes negative incentives that weed out faulty technologies. In contrast, positive incentives can induce beneficial invention. John Harrison (1693-1776) worked for years developing a clock for accurate navigation at sea, motivated by the Royal Society's 20,000 pound prize.

Organizations, mores, laws and other institutions explain a major part of how good ideas catch on and how bad ones are abandoned. But good ideas can get lost as well. Jared Diamond relates that bow and arrow technologies emerged and then disappeared from pre-historic Australian cultures. Aboriginal mastery of the environment went up and then down. The mechanisms or institutions for selecting better tools do not always exist or operate.

Valuable technologies can be "side-lined" as well, despite apparent advantages. The CANDU nuclear reactor technology, for instance, uses natural Uranium. No isotope enrichment is needed, so its fuel cycle is disconnected from Uranium enrichment for military applications (atom bombs use highly enriched Uranium or Plutonium). CANDU's two main technological competitors - pressurized and boiling water reactors - use isotope-enriched fuel. Nuclear experts argue long (and loud) about the merits of various technologies, but no "major" or "serious" accidents (INES levels 6 or 7) have occurred with CANDU reactors but have with PWRs or BWRs. Nonetheless, the CANDU is a minor contributor to world nuclear power.

The long-run improvement of technology depends on incentives created by attitudes, organizations and institutions, like the Royal Society and the law. Technology modifies those attitudes and institutions, creating an interactive process whereby society influences technological development, and technology alters society. The main uncertainty in technological progress arises from unintended impacts of technology on mores, values and society as a whole. An example will make the point.

Early mechanical clocks summoned the faithful to prayer in medieval monasteries. But technological innovations may be used for generations without anyone realizing their full implications, and so it was with the clock. The long-range influence of the mechanical clock on western civilization was the idea of "time discipline as opposed to time obedience. One can ... use public clocks to summon people for one purpose or another; but that is not punctuality. Punctuality comes from within, not from without. It is the mechanical clock that made possible, for better or for worse, a civilization attentive to the passage of time, hence to productivity and performance." (Landes, p.7)

Unintended consequences of technology - what economists called "externalities" - can be beneficial or harmful. The unintended internalization of punctuality is beneficial (maybe). The clock example illustrates how our values gradually and unexpectedly change as a result of technological innovation. Environmental pollution and adverse climate change are harmful, even when they result from manufacturing beneficial consumer goods. Attitudes towards technological progress are beginning to change in response to perceptions of technologically-induced climate change. Pollution and climate change may someday seriously disrupt the technology-using societies that produced them. This disruption may occur either by altering social values, or by adverse material impacts, or both.

Progress occurs in historical and institutional context. Hammurabi's Code created incentives for technological change; monastic life created needs for technological solutions. Progress is uncertain because we cannot know what will be invented, and whether it will be beneficial or harmful. Moreover, inventions will change our attitudes and institutions, and thus change the process of invention itself, in ways that we cannot anticipate. The scientific engineer must dispel the "darkness over the deep" (Genesis 1:2) because mastery comes from enlightenment. But in doing so we change both the world and ourselves. The unknown is not only over "the waters" but also in ourselves.




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We're Just Getting Started: A Glimpse at the History of Uncertainty


We've had our cerebral cortex for several tens of thousands of years. We've lived in more or less sedentary settlements and produced excess food for 7 or 8 thousand years. We've written down our thoughts for roughly 5 thousand years. And Science? The ancient Greeks had some, but science and its systematic application are overwhelmingly a European invention of the past 500 years. We can be proud of our accomplishments (quantum theory, polio vaccine, powered machines), and we should worry about our destructive capabilities (atomic, biological and chemical weapons). But it is quite plausible, as Koestler suggests, that we've only just begun to discover our cerebral capabilities. It is more than just plausible that the mysteries of the universe are still largely hidden from us. As evidence, consider the fact that the main theories of physics - general relativity, quantum mechanics, statistical mechanics, thermodynamics - are still not unified. And it goes without say that the consilient unity of science is still far from us.

What holds for science in general, holds also for the study of uncertainty. The ancient Greeks invented the axiomatic method and used it in the study of mathematics. Some medieval thinkers explored the mathematics of uncertainty, but it wasn't until around 1600 that serious thought was directed to the systematic study of uncertainty, and statistics as a separate and mature discipline emerged only in the 19th century. The 20th century saw a florescence of uncertainty models. Lukaczewicz discovered 3-valued logic in 1917, and in 1965 Zadeh introduced his work on fuzzy logic. In between, Wald formulated a modern version of min-max in 1945. A plethora of other theories, including P-boxes, lower previsions, Dempster-Shafer theory, generalized information theory and info-gap theory all suggest that the study of uncertainty will continue to grow and diversify.

In short, we have learned many facts and begun to understand our world and its uncertainties, but the disputes and open questions are still rampant and the yet-unformulated questions are endless. This means that innovations, discoveries, inventions, surprises, errors, and misunderstandings are to be expected in the study or management of uncertainty. We are just getting started. 








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New JHBS: Mind-Body Medicine Before Freud, Psychology and Biography, Jung and Einstein

The Spring 2020 issue of the Journal of the History of the Behavioral Sciences is now online. Full details about contributions to this issue follow below. “Practicing mind-body medicine before Freud: John G. Gehring, the “Wizard of the Androscoggin”” by. Ben Harris and Courtney J. Stevens. Abstract: This article describes the psychotherapy practice of physician … Continue reading New JHBS: Mind-Body Medicine Before Freud, Psychology and Biography, Jung and Einstein




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Review Article – Within a single lifetime: Recent writings on autism

AHP readers will be interested in a review article now available online from History of the Human Sciences “Within a single lifetime: Recent writings on autism.” Written by Gregory Hollin the piece reviews five recent books on autism.




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Forthcoming in JHBS: Quêtelet on Deviance, McClelland on Leadership, Psychological Warfare, and More

A number of articles now in press at the Journal of the History of the Behavioral Sciences will be of interest to AHP readers. Full details below. “Uncovering the metaphysics of psychological warfare: The social science behind the Psychological Strategy Board’s operations planning, 1951–1953,” Gabrielle Kemmis. Abstract: In April 1951 president Harry S. Truman established … Continue reading Forthcoming in JHBS: Quêtelet on Deviance, McClelland on Leadership, Psychological Warfare, and More




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Forthcoming HOPOS Special Issue on Descriptive Psychology and Völkerpsychologie

Two pieces forthcoming in a special issue of HOPOS, the official journal of the International Society for the History of Philosophy of Science, will be of interest to AHP readers. The special issue, “Descriptive Psychology and Völkerpsychologie—in the Contexts of Historicism, Relativism, and Naturalism,” is guest-edited by Christian Damböck, Uljana Feest, and Martin Kusch. Full details … Continue reading Forthcoming HOPOS Special Issue on Descriptive Psychology and Völkerpsychologie




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CfP: Shaping the ‘Socialist Self’? The Role of Psy-Sciences in Communist States of the Eastern Bloc (1948–1989)

CALL FOR PAPERSINTERNATIONAL WORKSHOP Shaping the ‘Socialist Self’? The Role of Psy-Sciences in Communist States of the Eastern Bloc (1948–1989) Date: 6 November 2020 Venue: Prague, Czech Republic Deadline for applications: 30 June 2020 Organizing institutions: CEFRES (French Research Center in Humanities and Social Sciences in Prague) Institute of Contemporary History of the Czech Academy of Sciences Collegium Carolinum … Continue reading CfP: Shaping the ‘Socialist Self’? The Role of Psy-Sciences in Communist States of the Eastern Bloc (1948–1989)




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May HoP, including a Special Section: Who Was Little Albert? The Historical Controversy

Photographs of John Watson (left) and Rosalie Rayner (right) via Ben Harris. The May 2020 issue of History of Psychology is now online. The issue includes a special section on “Who Was Little Albert? The Historical Controversy.” Full details follow below. Special Section: Who Was Little Albert? The Historical Controversy“Journals, referees, and gatekeepers in the … Continue reading May HoP, including a Special Section: Who Was Little Albert? The Historical Controversy




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Forthcoming in HHS: Homosexual Aversion Therapy, Comte on Organism-Environment Relationships

Two forthcoming pieces in History of the Human Sciences may be of interest to AHP readers. Full details below. “Cold War Pavlov: Homosexual aversion therapy in the 1960s,” by Kate Davison. Abstract: Homosexual aversion therapy enjoyed two brief but intense periods of clinical experimentation: between 1950 and 1962 in Czechoslovakia, and between 1962 and 1975 … Continue reading Forthcoming in HHS: Homosexual Aversion Therapy, Comte on Organism-Environment Relationships




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The Music That Boosts Learning By 18% (M)

Three classical pieces that boost memory retention.

Support PsyBlog for just $5 per month. Enables access to articles marked (M) and removes ads.

→ Explore PsyBlog's ebooks, all written by Dr Jeremy Dean:




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Cuddling: The Amazing Effect On Your Brain

For the study, 10 couples spent 45 minutes inside a brain scanner together in close physical contact.

Support PsyBlog for just $5 per month. Enables access to articles marked (M) and removes ads.

→ Explore PsyBlog's ebooks, all written by Dr Jeremy Dean:




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How Technology Is Improving Safety On the Roads and Reducing Driving Anxiety

Technology has changed a number of aspects of our everyday lives and has led to increased efficiency. But when it comes to driving, has it helped or hindered the process? In this article, we will be looking into some of the ways that technology has improved safety on our roads in the last 10 years. […]




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How to Mentally Prepare for a Synchro Swimming Competition

Some people have the misguided belief that synchronized swimming is just an easy sport performed in beautiful swim team suits. That it’s merely dancing in the water that you can tune in to watch during the Olympic Games. But that is far from true; there is much more to the sport.  Synchro is a dominant […]




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Examining the Pros and Cons of Phone Therapy

Telephone therapy has taken on greater significance in the mental health industry in wake of the covid-19 pandemic. While some individuals may have avoided telephone therapy in the past, the temporary closure of mental health offices and the necessity of social distancing have resulted in an increasing number of people asking for more information on […]




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How Phone Counseling May Help Save Lives During the Covid-19 Lockdown

With the covid-19 pandemic now affecting virtually every country on earth, it is understandable that much of the world’s focus has been on protecting people’s physical health. Hand washing and social distancing is important in the fight against the coronavirus. However, it is important to remember that mental health issues may lead to loss of […]




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A devious little marketing nudge

Courtesy of computer security provider Lavasoft (spotted by a sharp behavioral graduate student at Booth). Yes, you can click the grayed-out button on the left and “update” to the free software.  




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Where is behavioral economics headed in the world of marketing?

The Nudge blog sat down (electronically) with John Kenny, Senior Vice President of Strategic Planning in Draftfcb’s Chicago office, to explore whether behavioral economics is just a fad in marketing or a legitimate tool to help the industry perform better. Starting with the Institute of Decision Making, Draftfcb has been one of the leaders in [...]




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Here’s how Washington State’s nudge for state park donations works via its web site

A couple years ago, Washington State switched the default rule on state park fees that drivers pay (or don’t pay) when they renew their licenses. Reader Steve Loeb nicely captures what this switch looks like on the Washington State Department of Licensing site.