A 'Gaydar' machine?

Heather Murphy describes the kerfuffle that has ensued after Stanford researchers published a preprint of their work that will soon appear in The Journal of Personality and Social Psychlogy. To teach a machine (a widely used facial analysis program employing a pattern identifying neural network) to detect sexuality, authors Kosinski and Wang copied more than 75,000 dating profiles of men and women seeking same or different sex partners. The software extracted information from thousands of facial data points to generate average composite heterosexual and gay male and female faces (pictures are in the Murphy article). They found that their model did much better than humans at identifying sexual orientation. When the computer was given five photos for each person instead of just one, accuracy rose to 83% for women and 91% for men.

The negative Tweet storms and blog posts criticized the study as being a technology-fueled revival of the long discredited notion that physiognomy, measuring the size and shape of a person's eyes, nose and face, can predict personality traits. Highly inaccurate science, racism by algorithm, etc.

And, even if the machine works as stated, William T.L. Cox, a psychologist who studies stereotypes at the University of Wisconsin-Madison, notes:

Let’s say 5 percent of the population is gay, or 50 of every 1,000 people. A facial scan that is 91 percent accurate would misidentify 9 percent of straight people as gay; in the example above, that’s 85 people (0.91 x 950).

The software would also mistake 9 percent of gay people as straight people. The result: Of 130 people the facial scan identified as gay, 85 actually would be straight.

When an algorithm with 91 percent accuracy operates in the real world, almost two-thirds of the times it says someone is gay, it would be wrong.

Brain and body imaging of the emotional power of poetry.

By now a body of work has grown on how peak musical experiences engage the reward systems of our brains, with concomitant changes such as tingling and goosebumps triggered by our autonomic nervous systems. A colleague pointed me to this discussion by Delistraty of recent work in the journal Social Cognitive and Affective Neuroscience by Wassiliwizky et al. that extends this sort of analysis to the appreciation of poetry. I suggest you read the discussion. Here is the abstract of the work:

It is a common experience—and well established experimentally—that music can engage us emotionally in a compelling manner. The mechanisms underlying these experiences are receiving increasing scrutiny. However, the extent to which other domains of aesthetic experience can similarly elicit strong emotions is unknown. Using psychophysiology, neuroimaging and behavioral responses, we show that recited poetry can act as a powerful stimulus for eliciting peak emotional responses, including chills and objectively measurable goosebumps that engage the primary reward circuitry. Importantly, while these responses to poetry are largely analogous to those found for music, their neural underpinnings show important differences, specifically with regard to the crucial role of the nucleus accumbens. We also go beyond replicating previous music-related studies by showing that peak aesthetic pleasure can co-occur with physiological markers of negative affect. Finally, the distribution of chills across the trajectory of poems provides insight into compositional principles of poetry.

MindBlog has moved to Austin Texas.

A personal note.  Len and I have just moved back into the family house in Austin Texas where I grew up, through high school. My son and his family recently moved from this house into a larger home, where my Steinway B now resides in a much larger living room. The annual snowbird commute will now be between Madison WI and Austin Texas, rather than Madison and Fort Lauderdale. The picture shows an Essex upright (Steinway sub-brand) that just arrived at the smaller family house to serve as a practice piano.

Price modulates the effectiveness of your pain medication!

Fascinating observations from Tinnermann et al. A Science magazine summary, followed by the article abstract:

Price modulates early pain processing

Patients in randomized clinical trials frequently stop taking their drug, complaining of side effects. However, it turns out that some of these subjects are part of the placebo group and thus never received any active medication. This is a case of the nocebo effect seriously interfering with medical treatment. Tinnermann et al. investigated whether value information such as the price of a medication can further modulate behavioral nocebo effects and the underlying neural network dynamics (see the Perspective by Colloca). They used brain imaging to characterize the circuits involved in nocebo hyperalgesia within the descending pain pathway from the prefrontal cortex to the spinal cord. Their findings revealed how value information increased the nocebo effect.

Abstract

Value information about a drug, such as the price tag, can strongly affect its therapeutic effect. We discovered that value information influences adverse treatment outcomes in humans even in the absence of an active substance. Labeling an inert treatment as expensive medication led to stronger nocebo hyperalgesia than labeling it as cheap medication. This effect was mediated by neural interactions between cortex, brainstem, and spinal cord. In particular, activity in the prefrontal cortex mediated the effect of value on nocebo hyperalgesia. Value furthermore modulated coupling between prefrontal areas, brainstem, and spinal cord, which might represent a flexible mechanism through which higher-cognitive representations, such as value, can modulate early pain processing.

Transcending tribalism - crafting a new vision for America?

I want to point to, and comment on, two recent pieces by David Brooks. In the first, he argues that “the main enemy is not aliens; it’s division — between rich and poor, white and black, educated and less educated, right and left. Where there is division there are fences. Mobility is retarded and the frontier is destroyed. Trumpist populists want to widen the divisions and rearrange the fences. They want to turn us into an old, settled and fearful nation.” The second article deals with the gun control issue having “become an epiphenomenon of a much larger conflict over values and identity.” Both describe a reactionary core of Americans who contract into a vision of a lost past rather than opening up to feel comfortable in a more multicultural society. The first piece suggests the possibility of finding unity in a shared quest for new frontiers, with the same psychological force as the geographical western frontiers of the 1800’s, but instead in communication, the arts, science, and new social structures and media.

My comment would be that we do not face such a new world with a blank slate, but rather an evolved psychology that permits individuals to have stable relationship with only ~150 other people (see Robin Dunbar), in a larger tribe that has clear rules and expectation of its members, and that organize itself to complete successfully with other groups. In the basements of our minds there is a paleolithic psychology trying to cope with an utterly altered world. Having at age 75 just moved back into the childhood home I grew up in, in Austin Texas, I have very strong recall of my immersion in, and comfort with, the social rites of fellow Texans of the 1940’s and 1950’s.

I can not imagine, for myself or others, feeling analogous emotional bonding to an national or international multicultural meritocracy with a ruling elite, permissive of its components having conflicting moralities and rules. An ‘us’ and (or versus) ‘them’ is mentally much less taxing. Brooks faces an uphill battle with his hopeful vision: “The core American idea is not the fortress, it’s the frontier…It may be dormant, but this striving American dream is still lurking in every heart. It’s waiting for somebody who has the guts to say no to tribe, yes to universal nation, no to fences, yes to the frontier, no to closed, and yes to the open future, no to the fear-driven homogeneity of the old continent and yes to the diverse hopefulness of the new one.”

It would take a very charismatic new leader to pull all this together. Sigh… we thought we had that at one point, with Barack Obama.

MindBlog's book abstracts.

I’ve been working on abstracting a book I’ve mentioned recently, Sapolsky’s “Behave - The Biology of Humans at Our Best and Worst,” hoping to present the basic message of its chapters in a series of MindBlog posts. This is taking longer than I expected. It is a more sprawling and messy affair (just like human behavior) than some of the other book extracts I have offered this way (Gilbert - Stumbling on Happiness, 8 posts; Metzinger - The Ego Tunnel, 5 posts, Grazanio - Consciousness and the Social Brain, post). I’m actually doing this brief post to point you to those previous abstracts, which are worth a look, because I suspect few current readers are aware of them.

Curtailing proactive policing can reduce major crime.

Weisburd points to work by Sullivan and O’Keeffe, yielding counter-intuitive results, that "took advantage of a natural experiment in New York City that resulted from the strangling death of Eric Garner in Staten Island. Subsequent political events led to the New York City Police Department (NYPD) engaging in a ‘slowdown’ characterized by dramatic reductions in arrests and summonses. One would have expected crime to go up in this period if this type of proactivity was effective. Instead, analyzing several years of data obtained from the NYPD, they find that civilian complaints of major crimes decreased. Accordingly, they conclude that prior proactivity did not reduce crime, but led to increases in crime." Here is the Sullivan and O'Keeffe abstract:

Governments employ police to prevent criminal acts. But it remains in dispute whether high rates of police stops, criminal summonses and aggressive low-level arrests reduce serious crime1,2,3,4,5,6,7. Police officers target their efforts at areas where crime is anticipated and/or where they expect enforcement will be most effective. Simultaneously, citizens decide to comply with the law or commit crime partly on the basis of police deployment and enforcement strategies. In other words, policing and crime are endogenous to unobservable strategic interaction, which frustrates causal analysis. Here, we resolve these challenges and present evidence that proactive policing—which involves systematic and aggressive enforcement of low-level violations—is positively related to reports of major crime. We examine a political shock that caused the New York Police Department (NYPD) to effectively halt proactive policing in late 2014 and early 2015. Analysing several years of unique data obtained from the NYPD, we find that civilian complaints of major crimes (such as burglary, felony assault and grand larceny) decreased during and shortly after sharp reductions in proactive policing. The results challenge prevailing scholarship as well as conventional wisdom on authority and legal compliance, as they imply that aggressively enforcing minor legal statutes incites more severe criminal acts.

Brain circuits that modulate sociability.

The social bonding neuropeptide oxytocin can be traced over 500 million years, with analogous peptides found in birds, reptiles, fish, amphibians, and some invertebrates. Hung et al. have found that release of oxytocin in the ventral tegmental area of the brain increases prosocial behaviors in mice. Optogenetic manipulation of oxytocin release influences sociability in a context-dependent manner. Oxytocin increases activity in dopamine cells that project to the nucleus accumbens, another key node of reward circuitry in the brain. Here is their abstract, followed by a nice graphic of the relevant systems in the human brain.

The reward generated by social interactions is critical for promoting prosocial behaviors. Here we present evidence that oxytocin (OXT) release in the ventral tegmental area (VTA), a key node of the brain’s reward circuitry, is necessary to elicit social reward. During social interactions, activity in paraventricular nucleus (PVN) OXT neurons increased. Direct activation of these neurons in the PVN or their terminals in the VTA enhanced prosocial behaviors. Conversely, inhibition of PVN OXT axon terminals in the VTA decreased social interactions. OXT increased excitatory drive onto reward-specific VTA dopamine (DA) neurons. These results demonstrate that OXT promotes prosocial behavior through direct effects on VTA DA neurons, thus providing mechanistic insight into how social interactions can generate rewarding experiences.

You want younger or older?

Interesting piece from Mona Chalabi:

(According to the Census Bureau, the average age difference between men and their wives is 2.3 years.)

This year's Ig Nobel prizes.

If you want a few chuckles, have a look at this link. The prize winning work this year shows that cats can be simultaneously solid and liquid because of their ability to adopt the shape of their container.

Does it matter whether we believe in free will or not?

From Genschow et al.:

Significance

The question whether free will exists or not has been a matter of debate in philosophy for centuries. Recently, researchers claimed that free will is nothing more than a myth. Although the validity of this claim is debatable, it attracted much attention in the general public. This raises the crucial question whether it matters if people believe in free will or not. In six studies, we tested whether believing in free will is related to the correspondence bias—that is, people’s automatic tendency to overestimate the influence of internal as compared to external factors when interpreting others’ behavior. Overall, we demonstrate that believing in free will increases the correspondence bias and predicts prescribed punishment and reward behavior.

Abstract

Free will is a cornerstone of our society, and psychological research demonstrates that questioning its existence impacts social behavior. In six studies, we tested whether believing in free will is related to the correspondence bias, which reflects people’s automatic tendency to overestimate the influence of internal as compared to external factors when interpreting others’ behavior. All studies demonstrate a positive relationship between the strength of the belief in free will and the correspondence bias. Moreover, in two experimental studies, we showed that weakening participants’ belief in free will leads to a reduction of the correspondence bias. Finally, the last study demonstrates that believing in free will predicts prescribed punishment and reward behavior, and that this relation is mediated by the correspondence bias. Overall, these studies show that believing in free will impacts fundamental social-cognitive processes that are involved in the understanding of others’ behavior.

Also, you should have a look at Frith's essay on how our illusory sense of agency has a deeply important social purpose. Belief in free will and agency is important if a distinction critical to all legal systems is to be made: between intentional and accidental wrongs. Further,

Responsibility... is the real currency of conscious experience. In turn, it is also the bedrock of culture. Humans are social animals, but we’d be unable to cooperate or get along in communities if we couldn’t agree on the kinds of creatures we are and the sort of world we inhabit. It’s only by reflecting, sharing and accounting for our experiences that we can find such common ground. To date, the scientific method is the most advanced cognitive technology we’ve developed for honing the accuracy of our consensus – a method involving continuous experimentation, discussion and replication.

Greater internet use does not correlate with faster growth of political polarization.

Continuing a topic from MindBlog's April 20 post...Most writing on the increase in political polarization over the past decades argues that it is facilitated by more extensive use of the internet, enhancing formation of social sites for like minded people which form isolated 'echo chambers.' Boxell et al. find, to the contrary, that polarization has increased the most among the demographic groups least likely to use the Internet and social media.

We combine eight previously proposed measures to construct an index of political polarization among US adults. We find that polarization has increased the most among the demographic groups least likely to use the Internet and social media. Our overall index and all but one of the individual measures show greater increases for those older than 65 than for those aged 18–39. A linear model estimated at the age-group level implies that the Internet explains a small share of the recent growth in polarization.

“No problem” vs “you’re welcome”

My daughter pointed me to this piece by Gretchen McCulloch, which gives me some insight into what I have considered the annoying habit of younger people to always say 'no problem' instead of 'you're welcome.' A clip:

Speaking of linguistics, there’s one particular linguistic tick that I think clearly separates Baby Boomers from Millennials: how we reply when someone says “thank you.”

You almost never hear a Millennial say “you’re welcome.” At least not when someone thanks them. It just isn’t done. Not because Millennials are ingrates lacking all manners, but because the polite response is “No problem.” Millennials only use “you’re welcome” sarcastically when they haven’t been thanked or when something has been taken from/done to them without their consent. It’s a phrase that’s used to point out someone else’s rudeness. A Millennial would typically be fairly uncomfortable saying “you’re welcome” as an acknowledgement of genuine thanks because the phrase is only ever used disingenuously.

Baby Boomers, however, get really miffed if someone says “no problem” in response to being thanked. From their perspective, saying “no problem” means that whatever they’re thanking someone for was in fact a problem, but the other person did it anyway as a personal favor. To them “You’re welcome” is the standard polite response.

“You’re welcome” means to Millennials what “no problem” means to Baby Boomers, and vice versa.The two phrases have converse meanings to the different age sets. I’m not sure exactly where this line gets drawn, but it’s somewhere in the middle of Gen X. This is a real pain in the ass if you work in customer service because everyone thinks that everyone else is being rude when they’re really being polite in their own language.

The science of emotion - now at least 27 categories of emotional states.

So...I guess we knew emotions are complicated. There has been intense debate on how to describe them in semantic and geometric dimensions such as valence and arousal. Cowan and Keltner use a natural history approach to gather and analyze self descriptions of emotional states elicited by 2,185 emotionally evocative short videos (check out the geometrical space of their results in the link below):

Significance

Claims about how reported emotional experiences are geometrically organized within a semantic space have shaped the study of emotion. Using statistical methods to analyze reports of emotional states elicited by 2,185 emotionally evocative short videos with richly varying situational content, we uncovered 27 varieties of reported emotional experience. Reported experience is better captured by categories such as “amusement” than by ratings of widely measured affective dimensions such as valence and arousal. Although categories are found to organize dimensional appraisals in a coherent and powerful fashion, many categories are linked by smooth gradients, contrary to discrete theories. Our results comprise an approximation of a geometric structure of reported emotional experience.

Abstract

Emotions are centered in subjective experiences that people represent, in part, with hundreds, if not thousands, of semantic terms. Claims about the distribution of reported emotional states and the boundaries between emotion categories—that is, the geometric organization of the semantic space of emotion—have sparked intense debate. Here we introduce a conceptual framework to analyze reported emotional states elicited by 2,185 short videos, examining the richest array of reported emotional experiences studied to date and the extent to which reported experiences of emotion are structured by discrete and dimensional geometries. Across self-report methods, we find that the videos reliably elicit 27 distinct varieties of reported emotional experience. Further analyses revealed that categorical labels such as amusement better capture reports of subjective experience than commonly measured affective dimensions (e.g., valence and arousal). Although reported emotional experiences are represented within a semantic space best captured by categorical labels, the boundaries between categories of emotion are fuzzy rather than discrete. By analyzing the distribution of reported emotional states we uncover gradients of emotion—from anxiety to fear to horror to disgust, calmness to aesthetic appreciation to awe, and others—that correspond to smooth variation in affective dimensions such as valence and dominance. Reported emotional states occupy a complex, high-dimensional categorical space. In addition, our library of videos and an interactive map of the emotional states they elicit (https://s3-us-west-1.amazonaws.com/emogifs/map.html) are made available to advance the science of emotion.

Will you be above or below “the API” in the emerging economy?

An application programming interface (API) is a set of subroutine definitions, protocols, and tools that are building blocks for application software...software of the sort that Uber uses to connect taxi drivers to customers without other human intervention. From Anthony Wing Kosner:

Customers use an app interface to enter their data into the system. The app sends a request that includes account data, pickup and dropoff locations via API to Uber's servers that poll available drivers nearby and dispatches one to the customer to fulfill the request. The only two humans involved are the customer and the driver. Danny DeVito has been furloughed!

From Peter Reinhardt:

Drivers are opting into a dichotomous workforce: the worker bees below the software layer have no opportunity for on-the-job training that advances their career, and compassionate social connections don’t pierce the software layer either. The skills they develop in driving are not an investment in their future. Once you introduce the software layer between ‘management’ (Uber’s full-time employees building the app and computer systems) and the human workers below the software layer (Uber’s drivers, Instacart’s delivery people), there’s no obvious path upwards. In fact, there’s a massive gap and no systems in place to bridge it.

Kosner notes some of the longer term implication of such software:

Uber drivers, Amazon Mechanical Turk workers, 99design contestants, TaskRabbit taskers and HomeJoy cleaners are all targets for further automation...Yes, self-driving cars on the way, and it is likely that automated taxi fleets will be the first commercial application of this technology... Uberization of work may soon be coming to your chosen profession, affecting not just cab drivers and house cleaners, but extending to lawyers, doctors and even (some day) venture capitalists.

Color naming across languages reflects color use

Gibson et al. do a study showing that warm colors are communicated more efficiently than cool colors, and that this cross-linguistic pattern reflects the color statistics of the world:

Significance

The number of color terms varies drastically across languages. Yet despite these differences, certain terms (e.g., red) are prevalent, which has been attributed to perceptual salience. This work provides evidence for an alternative hypothesis: The use of color terms depends on communicative needs. Across languages, from the hunter-gatherer Tsimane' people of the Amazon to students in Boston, warm colors are communicated more efficiently than cool colors. This cross-linguistic pattern reflects the color statistics of the world: Objects (what we talk about) are typically warm-colored, and backgrounds are cool-colored. Communicative needs also explain why the number of color terms varies across languages: Cultures vary in how useful color is. Industrialization, which creates objects distinguishable solely based on color, increases color usefulness.

Abstract

What determines how languages categorize colors? We analyzed results of the World Color Survey (WCS) of 110 languages to show that despite gross differences across languages, communication of chromatic chips is always better for warm colors (yellows/reds) than cool colors (blues/greens). We present an analysis of color statistics in a large databank of natural images curated by human observers for salient objects and show that objects tend to have warm rather than cool colors. These results suggest that the cross-linguistic similarity in color-naming efficiency reflects colors of universal usefulness and provide an account of a principle (color use) that governs how color categories come about. We show that potential methodological issues with the WCS do not corrupt information-theoretic analyses, by collecting original data using two extreme versions of the color-naming task, in three groups: the Tsimane', a remote Amazonian hunter-gatherer isolate; Bolivian-Spanish speakers; and English speakers. These data also enabled us to test another prediction of the color-usefulness hypothesis: that differences in color categorization between languages are caused by differences in overall usefulness of color to a culture. In support, we found that color naming among Tsimane' had relatively low communicative efficiency, and the Tsimane' were less likely to use color terms when describing familiar objects. Color-naming among Tsimane' was boosted when naming artificially colored objects compared with natural objects, suggesting that industrialization promotes color usefulness.

Separate prefrontal areas code desirability versus availability.

When we make a decision, we calculate its “expected value,” by multiplying the value of something (how much we want or need it) with the probability that we might be able to obtain it, a concept first introduced by 17th-century mathematician Blaise Pascal. Rudebeck et al. show that this value determination involves two separate prefrontal areas:

Advantageous foraging choices benefit from an estimation of two aspects of a resource’s value: its current desirability and availability. Both orbitofrontal and ventrolateral prefrontal areas contribute to updating these valuations, but their precise roles remain unclear. To explore their specializations, we trained macaque monkeys on two tasks: one required updating representations of a predicted outcome’s desirability, as adjusted by selective satiation, and the other required updating representations of an outcome’s availability, as indexed by its probability. We evaluated performance on both tasks in three groups of monkeys: unoperated controls and those with selective, fiber-sparing lesions of either the OFC or VLPFC. Representations that depend on the VLPFC but not the OFC play a necessary role in choices based on outcome availability; in contrast, representations that depend on the OFC but not the VLPFC play a necessary role in choices based on outcome desirability.

Both OFC and VLPFC send connections to the ventromedial prefrontal cortex (VMPFC), and functional magnetic resonance imaging suggests that the VMPFC may be where choices ultimately get made.

How we see what we expect to see.

Kok et al. show that expectations can induce the preactivation of stimulus templates in our brain that resemble the neural signals actually generated when the stimuls is presented:

Significance

The way that we perceive the world is partly shaped by what we expect to see at any given moment. However, it is unclear how this process is neurally implemented. Recently, it has been proposed that the brain generates stimulus templates in sensory cortex to preempt expected inputs. Here, we provide evidence that a representation of the expected stimulus is present in the neural signal shortly before it is presented, showing that expectations can indeed induce the preactivation of stimulus templates. Importantly, these expectation signals resembled the neural signal evoked by an actually presented stimulus, suggesting that expectations induce similar patterns of activations in visual cortex as sensory stimuli.

Abstract

Perception can be described as a process of inference, integrating bottom-up sensory inputs and top-down expectations. However, it is unclear how this process is neurally implemented. It has been proposed that expectations lead to prestimulus baseline increases in sensory neurons tuned to the expected stimulus, which in turn, affect the processing of subsequent stimuli. Recent fMRI studies have revealed stimulus-specific patterns of activation in sensory cortex as a result of expectation, but this method lacks the temporal resolution necessary to distinguish pre- from poststimulus processes. Here, we combined human magnetoencephalography (MEG) with multivariate decoding techniques to probe the representational content of neural signals in a time-resolved manner. We observed a representation of expected stimuli in the neural signal shortly before they were presented, showing that expectations indeed induce a preactivation of stimulus templates. The strength of these prestimulus expectation templates correlated with participants’ behavioral improvement when the expected feature was task-relevant. These results suggest a mechanism for how predictive perception can be neurally implemented.

Computer design cues taken from human brains

Metz does an interesting article on the waning of do-it-all chips, central processing units of the sort that are running my MacBook Air as I type this, in favor distributed systems that offload specialized tasks, like hearing and seeing, to A.I. (artificial intelligence) chips specialized for those tasks, much as the human brain stem oversees the system and sends different jobs to different specialized parts of the surrounding cortex (auditory, visual, somatosensory, motor, executive, motivational, etc.):

...machines that spread computations across vast numbers of tiny, low-power chips can operate more like the human brain, which efficiently uses the energy at its disposal.

…the leading internet companies are now training their neural networks with help from another type of chip called a graphics processing unit, or G.P.U. These low-power chips — usually made by Nvidia — were originally designed to render images for games and other software, and they worked hand-in-hand with the chip — usually made by Intel — at the center of a computer. G.P.U.s can process the math required by neural networks far more efficiently than C.P.U.s.

G.P.U.s are the primary vehicles that companies use to teach their neural networks a particular task, but that is only part of the process. Once a neural network is trained for a task, it must perform it, and that requires a different kind of computing power.

After training a speech-recognition algorithm, for example, Microsoft offers it up as an online service, and it actually starts identifying commands that people speak into their smartphones. G.P.U.s are not quite as efficient during this stage of the process. So, many companies are now building chips specifically to do what the other chips have learned.

Google built its own specialty chip, a Tensor Processing Unit, or T.P.U. Nvidia is building a similar chip. And Microsoft has reprogrammed specialized chips from Altera, which was acquired by Intel, so that it too can run neural networks more easily.

The hope is that this new breed of mobile chip can help devices handle more, and more complex, tasks on their own, without calling back to distant data centers: phones recognizing spoken commands without accessing the internet; driverless cars recognizing the world around them with a speed and accuracy that is not possible now.

In other words, a driverless car needs cameras and radar and lasers. But it also needs a brain.

It’s all about tribes - not ideas, morals, or principles.

Thomas Edsall does another excellent piece on what is happening in our politics. I suggest you read it...here are a few clips:

Since the advent of Trump,

...white evangelicals went from being the least likely to the most likely group to agree that a candidate’s personal immorality has no bearing on his performance in public office.

Christopher Achen and Larry Bartels, political scientists at Princeton and Vanderbilt:

In the conventional view, democracy begins with the voters. Ordinary people have preferences about what their government should do. They choose leaders who will do those things, or they enact their preferences directly in referendums. In either case, what the majority wants becomes government policy ..... the more realistic view is that Citizens’ perceptions of parties’ policy stands and their own policy views are significantly colored by their party preferences. Even on purely factual questions with clear right answers, citizens are sometimes willing to believe the opposite if it makes them feel better about their partisanship and vote choices....group and partisan loyalties, not policy preferences or ideologies, are fundamental in democratic politics.

Edsall cites further work showing that those with strongest Republican identification are most likely to embrace Trump's swings in political stance to either the right or the left.