Category Archives: books

Teamology: Evaluative Diversity Promotes Success

Teamology: The Construction and Organization of Effective Teams“Teamology” is the name of a new branch of science somewhere between psychology and sociology. It studies teams and what makes them successful. This seems like an important new science, given that the impact of evolution on the human genome has been increasing and optimizing the success of competing teams rather than of individuals. However, experiments turn out to be logistically far more difficult to conduct in teamology than in psychology. All of the research mentioned in Douglass Wilde’s Teamology: The Construction and Organization of Effective Teams relied on the power of professors to make guinea-pigs out of students (Carnegie-Mellon, Stanford, Loyola U of Los Angeles, Oregon State, Shanghai Jiao-Tong, Sungkyunkwan U., U.C. Berkley, U.C. San Diego, U. of Florida, and U.T. Austin)

Teamological evidence is crucial to management of evaluative diversity because the reasons to protect evaluative diversity are:

  1. Love: For the sake of our children and grandchildren who are likely to be diverse
  2. Religious: For the sake of the One who created diversity
  3. Selfish: For our own sake, believing that we are part of teams which need evaluative diversity (as ecosystems need biodiversity)

The first two motives assume merely that we have diverse predispositions, a hypothesis which is well-confirmed by a wide range of experiments as detailed in Predisposed: Liberals, Conservatives, and the Biology of Political Differences. The third motive additionally assumes that diverse teams are more likely to succeed. Teamology is the only field in which experiments can confirm or reject that hypothesis (or tell us which kinds of diversity are beneficial when).

There is strong theoretical reason to expect team success to rely on evaluative diversity. GRIN-diversity reflects specialization in mitigating distinct factors which limit rate of adaptation:

  • Gadfly to increase the rate at which novel configurations are produced
  • Relational to increase network localization through subjective evaluation
  • Institutional to increase fidelity with which proven configurations are reproduced
  • Negotiator to increase selection pressure privileging better configurations

If it turns out that GRIN-diversity does not maximize rate of adaptation, then there must be something wrong with our theory of evolution. One test of the GRIN model involves comparing the success of computer systems with different GRIN-diversity. Computers with a dearth of any GRIN-type fail just like any machine missing one of its essential parts. Having found that confirmation in machines, it makes sense to compare the success of human teams with varying GRIN-diversity.

Evaluative Diversity in Human Teams

Douglass Wilde taught engineering at Stanford University. Each year, his students would work in teams to produce reports which would be entered into competition against each other and against teams from other universities. Teamology presents the method Wilde developed to form and organize winning teams. The method was tested over the course of decades and at U.C. San Diego, U. of Florida, and Jiao Da (Shanghai).

Wilde’s method essentially involved:

  1. Measuring students’ evaluative types,
  2. Dividing into teams so as to maximize evaluative diversity, and
  3. Assigning roles within each team to match measured types.

Wilde’s research was conducted before there was any way to measure GRIN-types. His assignment algorithm used a survey of preferences along Jungian dimensions: Introversion (I) vs. Extroversion (E), Structure (J) vs. Flexibility (P), Facts (S) vs. Possibilities (N), and Objects (T) vs. People (F). Here are Wilde’s formulas to transform those measures into preferences for eight roles:

Wilde formulas

Wilde reports that about 25% of Stanford teams won awards when self-selected, but about 75% won awards when formed by this method. Replication studies found similar results, though they measured success differently and also found that diverse teams “took longer to coalesce” than randomly formed teams did.

How Many Types?

Jungian personality theory disagrees with the Big Five model on the question of traits vs. types. Size is an example of a trait, while sex is an example of a type. We often point-out that types are of discrete categories, while traits fall along continuous scales, but in the context of teamology it may be more important to note that stable types are interdependent, while traits are not. For example, a human society could thrive in certain environments without any especially large members, but could not thrive in any environment without any females (or males).

Interdependency impacts the ideal number of individuals per team. For example, since bees have three sexes, their “families” should be larger than in species with fewer sexes. In contrast, diversity in traits is valuable only to accommodate diversity of situations, so diversity in traits will afford a team no advantage over the best possible individual when the situation is stable or when the individual can adjust his/her traits to match the situation. If adjustment is not feasible, a team of just two polar-opposite members could have full diversity in traits. Thus, if traits were the only source of valuable diversity, then teamology wouldn’t be so important (at least beyond pairs).

Jung’s theory predicts at least eight types and no traits, but the statistical characteristics of measures of Jung dimensions look like traits rather than types. The Big Five model predicts all traits and no types. Truth is probably somewhere in the middle—some traits and some types. The GRIN-SQ produces the statistics to prove that at least four types exist. One might wonder whether teamology could be used to further increase the number of types proven to exist.

The studies Wilde cited involved teams of three to five members each, so they could not possibly have demonstrated the interdependence of more types. If they balanced types, those types might best be called S, N, T and F, since those variables are doubled in his formulas. In the data Wilde provided from his 2006 class, of the 13 students assigned to fill multiple roles, 92% were assigned to be both P and J and 69% were assigned to be both E and I, so any specialization would have been on other dimensions. As implied by the diagram above, the typical team had one member with primary specialization in each quadrant (though some students were also assigned to serve as back-up for other quadrants).

The experiments described in Teamology compared teams formed by Wilde’s method to teams formed randomly or though pure self-selection. It would be far more instructive to compare to teams with all but one type, so that one might identify specific types which make a difference (and perhaps characterize the difference each makes). Wilde initially doubled team performance merely by assigning the students with highest MBTI-Creativity Index (T+2E+2P+6N) to separate teams (leaving no black-hole of gadflydom), but tripled performance relative to self-selection by separating the highest scorers in all eight roles. The difference between these experiments does imply that creativity diversity isn’t the only kind that matters, but specifically what else matters remains to be measured.

Separation of Powers

The reason why the diagram above divides the roles on the left against the roles on the right is that Wilde’s scoring formulas mathematically make those on the left equal to the negative of those on the right. For example, even if a student’s two most preferred roles really were Tester/Prototyper (E+P+2S) and Visionary/Strategist (I+J+2N), the results of Wilde’s preference measure could not possibly reflect that reality. They sum to zero, so at least one is guaranteed to be zero or negative. That is a consequence of the assumption that diversity is structured around dimensions.

It would not be surprising that  the person responsible for devising visions should like to be the person with the power to decide whether those visions are good nor that the person responsible for empathizing should like to be the person with the power to interpret policies (and thus to show mercy). However the danger in mixing such roles is rather obvious—we might call it “conflict of interest”—so we can appreciate the separation of powers forced by Wilde’s method. Wilde’s claim that Visionaries should not be the Testers sounds reasonable (and is supported by his research), but this might have nothing to do with preference.

Are Teams With Greater GRIN-Diversity More Successful?

In theory, the S, N, T and F roles sound like the four GRIN-types:

  1. The S roles include “Tester”, “Investigator” and “Inspector” which match the Negotiator specialization in selection
  2. The N roles include “Innovator”, “Entrepreneur” and “Visionary” which match the Gadfly specialization in generating novelty
  3. Wilde’s measure for T associates it with “logic”, “truthful”, “unaccommodating”, “intolerant” and “impartial” all of which match the Institutional specialization in fidelity.
  4. F would be Relational by process of elimination. Specialization in network localization is undermined in Wilde’s experiments because the structure of students’ social networks is designed and enforced by the experimenter. However, students would be accustomed to social processes developed for groups formed more naturally, so a team lacking relational evaluators would have the handicap of needing to engineer new social processes (e.g. radically new ways to resolve conflicts). Thus, a Relational member might be valuable even in engineered teams.

Empirical comparison of measures confirms that teams formed by Wilde’s method would have greater GRIN-diversity than teams formed at random. N correlates strongly with the Big-Five dimension of “Openness” which is significantly related to Gadfly evaluation. F correlates moderately with the Big-Five dimension of “Agreeableness” which is significantly related to Relational evaluation. Thus, teams formed by Wilde’s method are likely to include one natural gadfly, one naturally relational person, and two people of other GRIN type(s).

Yes, the more successful teams do have greater GRIN-diversity. Again the GRIN model is supported.

But what we really want to know is in which circumstances any of the four GRIN-types might not promote success. To measure that, we would need to compare teams with each type deficiency (and with none) in different circumstances, and it would be better to use direct measures of GRIN-type than to use Jung-types as a proxy. Also, instead of imposing team structure, it would be better to let people form (and re-form) their own teams, and teams-within-teams (unless people segregate so much that they offer no opportunity to observe naturally formed diverse teams). There is much research yet to conduct.

Moral Diversity vs. Evaluative Diversity

The Righteous MindIn his most recent book, The Righteous Mind: Why good people are divided by politics and religion, Jonathan Haidt (pronounced like “height”) reminds the reader at various points that he is telling his story in a roundabout way because typical readers would reject straight-up truth. The first four chapters are devoted to evidence that the average non-psychopath is irrational, able to learn truth only “in love” (as Ephesians 4:15 puts it). The Righteous Mind debuted at #6 on the New York Times best seller list for nonfiction hardcover, so, if you find it difficult to believe the claims in the summary below, you might want to try the roundabout version instead.

The Purpose of Division

Why are good people divided? Haidt devoted an entire chapter to defend the theory of group selection which entails that diversity will evolve if diversification is advantageous for groups. On page 365, Haidt summarized his conclusions about this advantage:

I suggested that liberals and conservatives are like yin and yang—both are “necessary elements of a healthy state of political life,” as John Stuart Mill put it.

In a similar way, bone cells and muscle cells are both necessary to the functioning of the human body, and it is for the good of the body that its cells divide and specialize.

To test the theory that diversification is advantageous for groups, one would want to compare the success of groups with different levels of diversity. Such evidence was collected by Douglas Wilde, a professor of design at Stanford University. His students divided into teams to develop designs submitted to intercollegiate competitions which were judged by blind-review. In some years, Wilde allowed students to form their own teams; in other years he forced them to team up with people who tended to think differently. Wilde, and the design professors who replicated this experiment at other colleges, found that forcing teams to be evaluatively diverse increased both internal conflict and win rates.

Instead of citing the research by the design professors, Haidt cited the research of Richard Sosis who found that the average religious commune founded in the nineteenth century United States was six times as likely as the average secular one to last over 20 years. Again, the research compared the success of different groups, but Sosis’ measure of success was longevity, while Wilde’s measure of success was win rate. Wilde’s measure would be irrelevant if we encountered a society that could survive well-enough with poor designs (i.e. had no competitors or environmental disasters pending to require rapid improvement of social designs).

The problem with Sosis’ research is that he did not manipulate or measure diversity. It is debatable whether the religious communes were more or less diverse than the secular ones. Communes are intrinsically anti-conservative—they are rebellions against the status-quo—yet religious communes have a commitment to norms. Thus, religious communes might be more likely to attract both liberals and conservatives, and it makes sense to expect them to be more diverse. Some of the greatest religious role-models created new norms while rebelling against the norms of their day (e.g. Muhammad, Jesus, Buddha, Gandhi, Confucius), yet Haidt offers an explanation which implies that religious communes would be less diverse (pg 342):

A commune that valued self-expression over conformity and that prized the virtue of tolerance over loyalty… would have lower moral capital than a commune that valued conformity and loyalty. The stricter commune would be better able to suppress or regulate selfishness, and would therefore be more likely to endure.

In Wilde’s research, the superior teams had heightened internal conflict, but Haidt’s explanation of Sosis’ research implies that we should expect the opposite. This may just be an example of Haidt trying to tell the story in a roundabout way. The bottom line is that Sosis’ research would need to be repeated with actual measures of diversity. Until then, we have Wilde’s results to support Haidt’s final conclusion that diversity is advantageous.

Proximate Causes of Division

From an evolutionary perspective, one could say that the cells of our bodies specialize into diverse types because this brings advantages to the body as a whole, but it is also correct to say that cells specialize because they are genetically programmed to do so. Genes are a proximate cause. In a similar way, while Haidt points to group-selection as the ultimate cause of division, he also points to research indicating that genetic and physiological differences (products of evolution) predispose us to disagree with one another.

After summarizing some of the research described in greater detail in John Hibbing and Kevin Smith’s Predisposed: Liberals, Conservatives, and the Biology of Political Differences, Haidt attempts to navigate the controversial issue of how our natures interact with nurture. This comes to a head in the recounting of Keith Richards’ testimony that he became a liberal when he was betrayed by the choir master of his school (pg 330):

Richards may have been predisposed by his personality [and genes] to become a liberal, but his politics were not predestined. Had his teachers treated him differently… he could have ended up in a more conventional job surrounded by conservative colleagues and sharing their moral matrix.

Of course a sufficiently controlled environment can manipulate the typical person into developing values contrary to his/her own genetic predisposition. Haidt also mentions that sufficiently controlled environments can flip a switch he calls the “hive switch” to shift a person’s values temporarily. He discusses oxytocin regulation, but dopamine regulation and ego depletion would be other such switches. However, Haidt stops short of discussing what the costs of manipulating people’s values might be.

Assuming one were to manipulate an environment to promote conservativism, it would see a decline in liberalism. If this sufficiently unbalances the society, then, according to the theory Haidt quoted from John Stuart Mill, it would collapse like an unbalanced ecosystem. That is one example of a cost. It is a cost to the group.

But we should also consider the consequences for an individual like Keith Richards. How would he like to have values contrary to his predispositions? Would he be frustrated like a short basketball player, a gay person in a heterosexual marriage, or someone with high IQ who cannot access the Intenet? Keith Richards is the lead guitarist of The Rolling Stones—it is difficult to imagine him being so successful in that role without genes predisposing him against conservativism—how would it have felt not to exercise those genes? Here’s one theory:

Theory #1: In more tolerant environments, people are more likely to hold values which align with their genetic predispositions and those who have such alignment experience better mental well-being (e.g. greater engagement in their career, family and community, and less depression, apathy, guilt, and desire to commit suicide).

To test this theory, psychologists would measure the values, predispositions and mental-well-being of people in environments with different levels of evaluativism. The benefits of this research could be huge: if it confirms the theory above, we could use it to improve mental well-being for our children and grandchildren. Most of the people with jobs today are not happy with their jobs, and our own lives might not be so bleak if our grandparents had conducted this research. So we have to ask, “Why have no psychologists tested this theory?”

Haidt’s subtitle “Why good people are divided by politics and religion” seems to ask about the causes of intolerance. If it turns out that intolerance has such significantly negative health consequences, that discovering them would motivate us to be more tolerant, then it is fair to say we are intolerant because psychologists have not measured those consequences. Psychologists have determined that suicide is the 10th leading cause of death in the U.S. and that gay youth facing anti-gay environments are more likely to attempt suicide, but this just a beginning to measuring the consequences of intolerance. Homophobia isn’t the only form of discrimination, and mental distress includes more than just suicide.

A 2014 study by Shanto Iyengar and Sean Westwood found that 80% of us, if asked to judge a scholarship competition, would discriminate against applicants with opposing values. That kind of discrimination is called “evaluativism” and the researchers offer every reason to believe it is pervasive, producing every manner of frustration. For the 13 years previous to that study, the only major study comparing kinds of discrimination was Haidt’s own study with Evan Rosenberg and Holly Hom. They found that people discriminate far more on the basis of values than on the basis of demographic differences, such as race, class and religion. His conclusion, in 2001, was that values diversity (which they called “moral diversity”) creates so much discrimination that it must be a bad kind of diversity.

In The Righteous Mind Haidt cited his 2001 study only in a footnote to his recommendation about how to make a team, company, school or other organization more “hivish, happy and productive” (pg 277):

Increase similarity, not diversity. To make a human hive, you want to make everyone feel like a family. So don’t call attention to the racial and ethnic differences; make them less relevant by ramping up similarity and celebrating the group’s shared values and common identity.

Again, Haidt implies that our aim should be to minimize internal conflict. As Haidt would predict, in years when Wilde didn’t draw attention to evaluative diversity, his students self-segregated and experienced less internal conflict. But the hivishness and happiness did not improve production; the consequence of self-segregation was inferior designs. Furthermore, if we do not raise awareness of evaluativism in awarding scholarships (and presumably jobs as well), Iyengar and Westwood’s research indicates the awards will be significantly and systematically biased. Aiming to minimize conflict is short-sighted.

Perhaps the worst tragedy to come from ignoring differences is implied by a 2009 twin study by Peter Hatemi, Carolyn Funk, Sarah Medland, Hermine Maes, Judy Silberg, Nicholas Martin, and Lindon Eaves which found that people’s values are less likely to align with their genetic predispositions while they remain in their parent’s homes. This does not indicate intentional discriminationparents are unaware of evaluative differencesyet even accidentally preventing one’s child from aligning with his/her genetic predispositions could diminish his/her mental well-being. What parent would want to remain ignorant of differences, if accepting those differences could save their child from wishing he/she were dead?

Again, the truth is so harsh that one can understand why Haidt might want to soften the blow. Would you believe a psychologist who told you that our failure to understand differences has made normal parenting is so oppressive that getting away from parents faster could save children from wanting to commit suicide?

Moral Diversity vs. Evaluative Diversity

Aside from his 2001 study, Haidt’s most important experiment may have been the development of the Moral Foundations Questionnaire (MFQ) which measures peoples beliefs that morality is about each of the following six values: Liberty/oppression, Fairness/cheating, Care/harm, Loyalty/betrayal, Authority/subversion, and Sanctity/degradation.

This research created a stir because moral psychology was previously dominated by the theory that there is one best moral type. As it turns out, people who rate themselves as politically conservative tend to consider all six values in their definition of “morality,” whereas people who rate themselves politically liberal tend to emphasize Care/harm and discount the last three values, and people who rate themselves as libertarians tend to emphasize Liberty/oppression and discount the last four values. Thus, the MFQ demonstrates that political types are moral types. Since it is unacceptable to conclude that one political type is better than the others, the dominant theory moral psychology was overturned.

In chapter 8, Haidt admits that his list of values might not be complete; in fact, one of the six values was not on the original list, so it has already been revised once. Given what we know about GRIN types, one might think the next revision should be to add “Originality/orthodoxy” and “Effectiveness/ inefficiency.” While some people do value original ideas and effective strategies, it is debatable whether the value qualify as “moral.” For example, the debate over whether the ends justify the means may be seen as a debate over whether Effectiveness is a moral value.

As part of his roundabout story-telling, Haidt saves his own definitions of morality and moral capital until the last two chapters:

Moral capital refers to the degree to which a community possesses interlocking sets of value, virtues, norms, practices, identities, institutions, and technologies that mesh well with evolved psychological mechanisms and thereby enable the community to suppress or regulate selfishness and make cooperation possible.

The values of Originality and Effectiveness do not necessarily suppress selfishness, so they would not qualify as “moral” values by this definition. They would probably qualify, however, under Ayn Rand’s definition of “moral.” Does Haidt have a scientific basis for dismissing Rand’s perspective? Haidt admits that Loyalty, Authority, and Sanctity do not qualify as “moral” by liberal definitionsdoes he have a scientific basis for dismissing the liberal perspective as well? To the contrary, Haidt concludes that the diverse perspectives are interdependent, so he is painted into a corner.

Haidt describes himself as a liberal who wants to understand conservatives on their own terms, so it makes sense that he would accept a conservative definition of “morality,” and it makes sense that this definition would produce a survey instrument that focuses on conservative values. Reaching across the isle is noble. However, a partisan definition is still a partisan definition, even if entertained by a psychologist from the opposing party.

The advantage of the term “evaluative diversity”  over “moral diversity” is to escape the non-scientific bias that will necessarily result from having to define “moral”. All values are evaluative, whether they are moral or not. Thus, evaluative diversity includes Liberty/oppression, Fairness/cheating, Care/harm, Loyalty/betrayal, Authority/subversion, Sanctity/degradation, Originality/orthodoxy, and Effectiveness/inefficiency (and perhaps more).

Unfortunately, there is no field of “evaluative psychology.” The field Haidt inherited and now leads is called “moral psychology”and that isn’t his faultso he finds himself asking people “Is it [morally] wrong for a brother and sister to have sex?” Depending on their own definitions of “morality” (or whether they even bother to have one), some people may find such questions nutty. I’m not God—why ask me? However, Haidt has already revolutionized his field. Asking him to strike the word “moral” from its name might be asking too much.

Who’s to Blame for Disagreement? An Interview with John Hibbing

Beyond Dislike: Viewing the Other Party as a ‘Threat to the Nation’s Well-Being’John Hibbing and Kevin Smith co-direct the Political Physiology Lab at the University of Nebraska-Lincoln. Their recent article in Trends in Cognitive Science concludes: “Although many people want to believe that their positions on moral, religious, and political issues are the product of rational, conscious thought, the reality is that subthreshold, biologically instantiated predispositions shape all human attitudes, leading people to rationalize their positions and actions.” John generously allowed me to interview him about it:

Chris: John, first tell us about you. What got you interested in the relationship between biology and political science?
John: I was trained as a traditional political scientist and studied Congress, elections, and public attitudes, but I increasingly came to the conclusion that surveys (in which people report their own perceptions) do not reveal everything, since humans are notoriously bad at understanding themselves. Thus I became interested in techniques that would help us understand the human condition, especially as it relates to politics, without forcing people to try to explain themselves.

The lab you co-direct with Kevin Smith is unique. What kinds of journals and departments, if any, should develop elsewhere to confirm or expand your findings?
Our lab was probably the first of its kind in a political science department, but, for some time, psychologists, neuroscientists, and behavioral geneticists have been probing the extent to which political orientations mesh with non-political aspects of our person. There is a gradually growing core of people–mostly psychologists–expanding and confirming our findings. A good indication of this was a piece we recently published in Behavioral and Brain Sciences that attracted 26 commentaries.

You have been studying the role of biological factors in explaining political variation for 20 years, and the law that all human behavioral traits are heritable has been known for well over a decade. How, then, does your work in Trends in Cognitive Science qualify as a “trend”?
I’m not sure. The editors from Trends in Cognitive Science asked us to submit that piece, so they must have thought there would be interest. There is more attention to the politics-biology connection now than there was 10-20 years ago, and I think it is only going to grow.

After acknowledging that twin studies consistently find political orientation to be strongly heritable, your article highlighted research on the particular gene DRD4. Why bother studying particular genes?
In terms of understanding the pathways through which biology affects politics, it would be quite useful to know the particular genes involved because that would indicate where in the brain to look. DRD4, for example, directs attention to the dopamine reward system.

What would it cost to identify the particular genes that make behavior heritable, and who would fund such research?
It is not that expensive these days to genotype people. The problem is that, to do the research properly, you need sample sizes of many, many thousands, and that can be a problem, especially when it is not common to collect political data along with the DNA. Our lab has moved away from doing candidate gene association studies because there is so much more to biology than just the DNA nucleotide sequence. For example, many environmental experiences can eventually become instantiated in our biological characteristics, so it is important for readers to realize that biology does not have to be genetic [to be immutable].

You also wrote about measuring biological underpinnings using EEG, the technology behind neurogaming. Does this imply that one might use a neurogaming headset to identify environments, such as particular workplaces, which are more or less likely to overwrite one’s values?
We do know that experiences, such as driving a taxi in London, can alter certain areas on the brain…

Beyond Dislike: Viewing the Other Party as a ‘Threat to the Nation’s Well-Being’The Pew Center recently reported that 27% of Democrats and 36% of Republicans in the U.S. see the opposing party as a threat to the nation’s well-being. How should they act on their beliefs, given the evidence that the disagreement stems from biological diversity?
Research by Shanto Iyengar shows that political differences are increasingly a reason for bias–people are more likely today than a few decades ago to say it would bother them to have their child marry someone with opposing political beliefs–while most other traits and factors (e.g., sexual orientation) are decreasingly a reason for bias. So the problem is real.

Our basic pitch is that, if people recognize that that their political opponents experience the world differently from a cognitive and physiological point of view, it should make them more tolerant of political differences, just as we became more tolerant when we found out that mental disabilities, left-handedness, and sexual orientation had biological bases. People should be less proud of their own beliefs, because hubris is a big reason we have the gridlock and terrorism that we do.

Lamenting terrorism, failed policy initiatives, and ruined family reunions, you wrote that research findings suggest a need to revise traditional views of political opinion. Care to elaborate?
Quit calling them names and thinking that they will “come around” when persuasive arguments are made. Compromise needs to be stressed more and deliberation needs to be stressed less.

 

The imperative for compromise is John’s big message. We spoke at length about how compromise might be determined, but ended up with unanswered questions. John’s insight that humans are bad at understanding themselves is demonstrated by his experiment in which the average conservative and liberal claim to have the same reactions to pictures of dead animals, but brain scans of those reactions reveal differences significant enough to identify political orientation. We also discussed evidence that genetic and self-report measures correspond differently at different ages. The average person seems to spend 20-50 years shifting his/her self-report, but efforts to mold the young tend to unravel, leaving us ultimately aligned with the diverse orientations we inherited at birth. John wanted to emphasize that schemes to control politics through genetic engineering oversimplify the way genes work. Many different genes interact, and they interact with major life events, including social reforms. His discoveries are tools less for social engineering than for giving politicians the same reverent respect for societies that medical doctors have gained for the human body.

To learn more about John and Kevin’s research, buy their book, Predisposed: Liberals, Conservatives, and the Biology of Political Differences, coauthored with John Alford from Rice University.

GRIN FREE — GRIN Together: How to let people be themselves (and why you should)

by Christopher Santos-Lang

Expert scholarship related through stories, this book empowers readers to free themselves from GRIN-closeting, free their loved-ones from GRIN-discrimination, and maintain environments where GRIN-diversity can flourish.

Introduction

Part 1: GRIN Free

Chapter 1: Discovering How to Be More Free
The story of how evaluative diversity is being discovered.

Chapter 2: Identify Yourself
A self quiz which allows readers to benchmark themselves.

Chapter 3: Natural Gadfly
The legacies, social value, and needs of natural gadflies.

Chapter 4: Naturally Relational
The legacies, social value, and needs of the naturally relational.

Chapter 5: Naturally Institutional 
The legacies, social value, and needs of the naturally institutional.

Chapter 6: Natural Negotiator
The legacies, social value, and needs of natural negotiators.

Chapter 7: Discovering Other Orientations
How to extend the GRIN model.

Chapter 8: Monitor Your Freedom via Smartphone
Emerging technologies for promoting GRIN-freedom.

Part 2: GRIN Together

Chapter 9: GRIN Ecosystem Management
Applying lessons from biological ecosystems

Chapter 10: Altruism
How flourishing societies balance individualism

Chapter 11: Mysticism
How flourishing societies balance reason

Chapter 12: Social Change
How flourishing societies balance inherited norms

Chapter 13: Expecting the Unexpectable
How flourishing societies balance negotiation

Chapter 14: Rules Against Rule-Following
How flourishing societies balance institutions

Chapter 15: Imitating Non-imitators
How flourishing societies balance relationship

Chapter 16: Deviating from Deviance
How flourishing societies balance gadflies

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