The fifth Future of Government Disruptive Debate hosted by the World Bank tackles the issue of citizens’ trust in government. Together with a diverse group of high-profile practitioners, renowned experts, and thought leaders, I discuss how the natural state of affairs is corruption and the challenges government face in getting citizens to trust higher levels of cooperation.
My opening remarks can be found from 7:12 to 14:07 in the recording above. A rough summary of my talk can be found on my substack: https://muthukrishnalab.substack.com/p/trust-governance-and-cultural-evolution
The fifth Future of Government Disruptive Debate will tackle the issue of citizens’ trust in government. The Disruptive Debate series aims is to bring together a diverse group of high-profile practitioners, renowned experts and thought leaders to generate new knowledge and perspectives.
The issue of trust has been a frequent theme arising during the Disruptive Debate series. The panel addressed questions such as: Why is trust important for poverty reduction and shared prosperity? What is the relationship between inequality and trust? What can governments do to increase, or re-build, trust? How can citizens influence and hold governments to account? What has been the role of information, data and social media, particularly during COVID-19?
I gave a talk on “Cooperation and the moral circle: When cooperation harms the collective good” as part of the SPSP 2021 Justice and Morality Pre-Conference. It’s part of some new work on the problem of the expanding moral circle as it links to cooperation, corruption, prosocial, and antisocial behavior. A related working paper is available here: https://www.biorxiv.org/content/10.1101/2021.02.19.432029v2
I had a fun, far-reaching, free-ranging conversation about my research and research motivations with Kensy Cooperrider on Many Minds.
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Today’s episode is a conversation with Dr. Michael Muthukrishna, an Associate Professor of Economic Psychology at the London School of Economics.
Michael’s research takes on a suite of topics that all start from a single big question: Why are we so different from other animals? Part of the answer has to do with our neural hardware. There’s no question we’ve got big brains—and Michael has some cool things to say about why they may have gotten so big. But Michael is just as focused on our cultural software—the tools and ideas we develop, tweak, share, and accumulate over time. You might say he’s more impressed by our collective brains than by our individual brains. To study all this, Michael builds formal theories and computational models; he runs experiments; and he constructs and analyzes huge databases.
We cover a lot of ground in this episode. We talk about the finding that the size and interconnectedness of a social group affects the cultural skills that group can develop and maintain. We consider what actually powers innovation (hint: it’s not lone geniuses). We discuss how diversity is a bit double-edged and why psychology needs to become a historical science. And that, my friends, is hardly all—we also touch on cetaceans, religious history, and spinning plates.
I’ve been hoping to have Michael on the show for months now. His work is deeply theoretical, advancing the basic science of what it means to be human. But it’s also engaged with important practical issues—issues like corruption and cultural diversity. Without further ado, here’s my conversation with Dr. Michael Muthukrishna. Enjoy!
A transcript of this show will be available soon.
Notes and links
4:30 – An introduction to “dual inheritance theory.”
11:00 – A 2013 paper by Dr. Muthukrishna and colleagues about the relationship between sociality and cultural complexity.
12:15 – A paper on the loss of cultural tools and traditions in the Tasmanian case.
21:20 – A 2016 paper by Dr. Muthukrishna and Joseph Henrich on innovation and the collective brain.
28:30 – The original paper on the notion of cultural “tightness” and “looseness.”
30:20 – A recent short piece by Dr. Muthukrishna on the paradox of diversity.
34:50 – A 2019 popular piece of mine on the phenomenon of “global WEIRDing.”
40:27 – The so-called Flynn Effect refers to the puzzling rise of IQ scores over time. It is named after James Flynn, who died only weeks ago.
42:30 – A paper about the significance of Luria’s work on abstract reasoning in Uzbekistan.
50:26 – A paper on the “cultural brain hypothesis,” the subject of Dr. Muthukrishna’s dissertation.
51:00 – A paper on brains as fundamentally “expensive.”
58:00 – Boyd & Richardson, mentioned here, have authored a number of highly influential books. The first of these was Culture and the Evolutionary Process.
59:35 – A 2015 paper on head size and emergency birth interventions.
1:01:20 – The stylized model we mention here is discussed and illustrated in this lecture from the 2020 Diverse Intelligences Summer Institute.
1:03:15 – The paper by Dr. Muthukrishna and colleagues on cetacean brains and culture.
1:11:38 – The paper by Dr. Muthukrishna and colleagues on ‘Psychology as a Historical Science.’
1:14:00 – The 2020 paper by Dr. Muthukrishna and colleagues introducing a tool for the measurement of cultural distance.
You can keep up with Dr. Muthukrishna’s work at his personal website and on Twitter (@mmuthukrishna).
Many Minds is a project of the Diverse Intelligences Summer Institute (DISI) (https://www.diverseintelligencessummer.com/), which is made possible by a generous grant from the Templeton World Charity Foundation to UCLA. It is hosted and produced by Kensy Cooperrider, with creative support from DISI Directors Erica Cartmill and Jacob Foster, and Associate Director Hilda Loury. Our artwork is by Ben Oldroyd (https://www.mayhilldesigns.co.uk/). Our transcripts are created by Sarah Dopierala (https://sarahdopierala.wordpress.com/).
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We review interdisciplinary evolutionary psychology that takes seriously both our primate heritage and our uniquely cultural nature – a “cultural evolutionary psychology”. Why, how, when, and on which things do different humans work together?
Humans in all societies cooperate far more than other mammals. We’re more prosocial than nonhuman primates who often look like rational choice models (these models are like Hardy-Weinberg models – null models without the effect of evolving norms & other culture).
A more complete explanation needs to explain scale, intensity, and domain differences between societies-people cooperate on different things to different degrees. Need to explain the scaling up in the last 12k years. And that many mechanisms can support maladaptive behav.
Explanations like language, intelligence, & institutions are insufficient. We can use language to lie, our cognitive abilities to cheat, & institutions can be undermined by lower scales of cooperation. Where did these come from anyway? See the cultural brain hypothesis & the collective brain. Also summarized in this lecture:
We use cultural evolution, dual inheritance theory, and the extended evolutionary synthesis as our theoretical framework & evaluate connected theories and evidence. For approach, see: https://www.nature.com/articles/s41562-018-0522-1 … (summarized).
Social norms and institutions – their origins and evolution is key to explaining the 4 features / puzzles of human cooperation mentioned before.
Some key concepts and behavioral experiments in cooperation.
Social norms shape cooperation, differ b/w societies, kids copy adults. Fairness is not the same everywhere – e.g. inequity aversion is not universally symmetric. We don’t like when things are unequal and we have less, but folks differ on unequal where they have more.
We review key mechanisms in broad strokes: kin-based, direct reciprocity, reputation, punishment, signaling. Origins of institutions. WEIRD intuitions are not a good guide – take partner choice for example.
So you have societies with different norms & sustained by different mechanisms of cooperation. Which ones spread? Competiton w/ sufficient resources can favor higher scales, but lower scales can undermine higher scales – corruption or autocracy or insurrection etc. Need alignment between levels.
The mechanisms of cooperation discussed are not alternatives to this competition. They are solutions to the free-rider problem with limits on scale and that can undermine one another. You also need to solve the equilibrium selection problem.
Social norms can create selection pressure on genes, they can self-domesticate. Institutions as connected and sometimes formalized social norms can create interdependence and fusion. They can align interests.
We end by revisiting the opening challenges. Check out the paper here:
I gave a public lecture on “A theory of human behavior? What would it look like and what would it offer?” and a workshop talk on “Beyond WEIRD Psychology and toward an understanding of evil eye and differences in economic productivity” at the LEVYNA Laboratory for the Experimental Research of Religion at the Masaryk University, Brno, Czechia
The public lecture was largely based on a recent Nature Human Behaviour piece “A Problem in Theory” on the role of theory in the psychological and behavioural sciences.
The workshop talk was a more indepth discussion of a recent working paper on measuring cultural distance “Beyond WEIRD Psychology: Measuring and Mapping Scales of Cultural and Psychological Distance” (pre-print) and some in-progress follow up work somewhat based on another recent paper published in Nature Human Behaviour, with some context published in Evonomics and ProMarket (pre-print).
I presented some work on measuring cultural distance “Beyond WEIRD Psychology: Measuring and Mapping Scales of Cultural and Psychological Distance” (pre-print) and some in-progress follow ups using the technique at the University of Economics, Prague, Czechia.
I also presented some in progress theoretical and empirical work on “Hunter-gatherer egalitarianism and the evolution of evil eye beliefs”. Part of this work was based on a recent paper published in Nature Human Behaviour, with some context published in Evonomics and ProMarket (pre-print).
I presented some work on measuring cultural distance “Beyond WEIRD Psychology: Measuring and Mapping Scales of Cultural and Psychological Distance” (pre-print) and some in-progress follow ups using the technique at City University in London, UK.
I also presented some in progress theoretical and empirical work on “Hunter-gatherer egalitarianism and the evolution of evil eye beliefs”. Part of this work was based on a recent paper published in Nature Human Behaviour, with some context published in Evonomics and ProMarket (pre-print).
I recently helped the UK Home Office with their anti-corruption, #FlagItUp campaign to encourage accounting and legal professionals to report more suspicious through a suspicious activity report.
I presented some in progress theoretical and empirical work on “Hunter-gatherer egalitarianism and the evolution of evil eye beliefs” at the Biological Anthropology seminar series at University College London (UCL) in London, UK.
I presented some in progress theoretical and empirical work on “The Evolution of Evil Eye Beliefs and Related Behaviors” at the 2nd Cultural Evolution Society (CES) conference.
Part of this work was based on a recent paper published in Nature Human Behaviour, with some context published in Evonomics and ProMarket (pre-print). But the main part was work in progress on understanding the evolution of evil eye beliefs and hunter-gatherer egalitarianism.
I presented work on “Corruption, Cooperation, & the Evolution of
Evil Eye” at the Human Behavior and Evolution Society (HBES) annual conference.
Part of this work was based on a recent paper published in Nature Human Behaviour, with some context published in Evonomics and ProMarket (pre-print). The other part was work in progress on understanding the evolution of evil eye.
I presented work on “Corruption, Cooperation, & the Evolution of Prosocial Institutions”, including some new work on the evolution of evil eye belief and related behaviors at the CIFAR Institutions, Organizations, and Growth program’s annual meeting.
Part of this work was based on a recent paper published in Nature Human Behaviour, with some context published in Evonomics and ProMarket (pre-print). The other part was work in progress on understanding the evolution of evil eye.
I presented a the “Cultural Evolution of Economics” with some illustrations on how cultural evolution can help economists and how economists can help those interested in cultural evolution. To illustrate this, I presented some recent and upcoming work on cooperation, corruption, democracy and economic growth. Abstract below:
Homo Economicus are extinct or on the verge of extinction, or so it would appear from outside economics. But within economics, reports of their death have been greatly exaggerated. Economicus’ persist, in part because alternative theories of human behavior are not readily integrated into existing economic approaches. To paraphrase Buckminster Fuller, criticism is not sufficient—you need to build a better model. I’ll discuss collaborations at the London School of Economics that are attempting to build that better model by integrating cultural evolutionary theory into economics. A cultural evolutionary approach seats corruption as a special case of cooperation, offering new means to understand and combat it (Muthukrishna, et al., 2017, “Corrupting Cooperation and How Anti-Corruption Strategies May Backfire”, Nature Human Behavior). A cultural evolutionary approach helps identify the invisible cultural pillars that support successful economic and democratic institutions (Stimmler & Muthukrishna, 2017, “When Cooperation Promotes Corruption and Undermines Democracy”, Working Paper; Muthukrishna, et al., in prep, “A WEIRD scale of cultural distance”). A cultural evolutionary approach reveals the relationship between economic growth, inequality, tolerance for inequality, and widespread beliefs—like “evil eye” and witchcraft—that have economic implications (Li & Muthukrishna, 2017, “The coevolution of Economic Growth, Inequality, Tolerance for Inequality, and Belief in Evil Eye”, Working Paper). These related studies reveal how cultural evolution may offer new approaches to age old problems, but also how the economic toolkit may be deployed to understand culturally evolved beliefs and behaviors.
Li presented an economic model and corresponding experimental test on the co-evolution of economic growth, inequality, tolerance for inequality and the widespread belief in “evil eye“.
Introducing the possibility of bribes into an institutional punishment public goods game results in reduced contributions.
In an institutional punishment public goods game, stronger leaders result in more cooperation. In our modified “bribery game”, stronger leaders result in less cooperation.
Anti-corruption measures including transparency and tying leaders payoffs to the success of the public good result improve contributions, except if economic potential is low and leaders are weak. Here, they can actually further reduce contributions.
Culture matters. Exposure to corrupt norms via living in corrupt places increases bribes, but having an ethnic heritage that includes corrupt countries, but not having actually lived there yourself results in less bribery.
Figures 1, 2 and 3, reproduced below illustrate these results.
Raw contributions (of the ten endowed points) and 95% confidence intervals for each within-subject treatment (control, BG, BG with partial transparency or BG with full transparency) in each between-subjects structural context (strong versus weak leader and poor versus rich economic potential). These data are consistent with our theory that predicts that more powerful leaders increase contributions in the IPGG but decrease contributions in the BG.
Darker blue indicates greater public goods provisioning and darker red indicates reduced public goods provisioning. All coefficients were extracted from a single model by changing reference groups. The columns represent the reference group treatment (control versus BG), while each row shows the coefficient of each treatment compared with this reference group. The contributions were z scores, so the coefficients represent s.d. The full model is reported in the Supplementary Information. In all models, we accounted for the clustering inherent in the experimental design by including a fixed effect for the number of subjects and random effects for participants within groups. Note that in all treatments and structural contexts, the BG has lower contributions than the structurally equivalent IPGG (control). Corruption mitigation effectively increases contributions (although not to control levels) when leaders are strong or the economic potential is rich. When leaders are weak and the economic potential is poor, the apparent corruption mitigation strategy, full transparency has no effect and partial transparency further decreases contributions. *P < 0.10; **P < 0.05; ***P < 0.01; ****P < 0.001.
Odds ratios and 95% confidence intervals are shown for each behaviour (accept bribe, punish or do nothing).
There is nothing natural1 about democracy. There is nothing natural about living in communities with complete strangers. There is nothing natural about large-scale anonymous cooperation. Yet, this morning, I bought a coffee from Starbucks with no fear of being poisoned or cheated. I caught a train on London’s underground packed with people I’ve never met before and will probably never meet again. If we were commuting chimps in a space that small, it would have been a scene out of the latest Planet of the Apes by the time we reached Holborn station. We’ll return to this mystery in a moment.
There is something very natural about prioritizing your family over other people. There is something very natural about helping your friends and others in your social circle. And there is something very natural about returning favors given to you. These are all smaller scales of cooperation that we share with other animals and that are well described by the math of evolutionary biology. The trouble is that these smaller scales of cooperation can undermine the larger-scale cooperation of modern states. Although corruption is often thought of as a falling from grace, a challenge to the normal functioning state—it’s in the etymology of the word—it’s perhaps better understood as the flip side of cooperation. One scale of cooperation, typically the one that’s smaller and easier to sustain, undermines another.
When a leader gives his daughter a government contract, it’s nepotism. But it’s also cooperation at the level of the family, well explained by inclusive fitness2, undermining cooperation at the level of the state. When a manager gives her friend a job, it’s cronyism. But it’s also cooperation at the level of friends, well explained by reciprocal altruism3, undermining the meritocracy. Bribery is a cooperative act between two people, and so on. It’s no surprise that family-oriented cultures like India and China are also high on corruption, particularly nepotism. Even in the Western world, it’s no surprise that Australia, a country of mates, might be susceptible to cronyism. Or that breaking down kin networks predicts lower corruption and more successful democracies (Akbari, Bahrami-Rad & Kimbrough, 2017; Schulz, 2017). Part of the problem is that these smaller scales of cooperation are easier to sustain and explain than the kind of large-scale anonymous cooperation that we in the Western world have grown accustomed to.
So how is it that some states prevent these smaller scales of cooperation from undermining large-scale anonymous cooperation? The typical answer is that more successful nations have better institutions. All that’s required is the right set of rules to make society function. But even on the face of it, this answer seems incomplete. If it were true, Liberia, who borrowed more than its flag from the United States, ought to be much more successful than it is4. Instead, these institutions are supported by invisible cultural pillars without which the institutions would fail. For example, without a belief in rule of law—that the law applies to all and cannot be changed on the whim of the leader—it doesn’t matter what the constitution or legal code says, no one is listening. Without a long time horizon, decisions are judged on how well they serve our immediate needs making larger-scale projects, like reducing the effects of Climate Change, harder to justify5. Similarly, institutions often lack the punitive power to actually punish perpetrators. For example, most people in the US and UK pay their taxes, even though in reality the IRS and Her Majesty’s Revenue and Customs lack the power to prosecute widespread non-compliance; your probability of getting caught is low. The tax compliant majority may never discover that they can cheat or how to get away with it (Chetty, et al. 2013) and they may not actively seek this information as long as the probability of getting caught is non-zero, the system seems fair, and it seems like everyone else is complying. Or in other words, it’s a combination of norms and institutions. But, it gets tricky—institutions are themselves hardened or codified norms6 and the norms themselves evolve in response to the present environment and due to path-dependence of previous environments, past decisions, and the places migrants come from. Modern groups vary on individualism (Talhelm, et al., 2014) and even sexist attitudes (Alesina, et al., 2013) based on their ancestors’ farming practices7. The science of cultural evolution describes the evolution of these norms and introduces the possibility of out-of-equilibria behavior (people behaving in ways that do not benefit them individually) for long enough for institutions to try to stabilize the new equilibria. For a summary of cultural evolution, see Joseph Henrich’s excellent book and for an even shorter summary see this chapter). How do we begin to understand these processes?
The real world is messy and before we start running randomized control trials or preparing case studies, it’s useful to model the basic dynamics of cooperation using a simpler form that gets at the core elements of the challenge. One commonly used model is called the “Public Goods Game”. The gist of the game is that I give you, and say 9 others, $10. Whatever you put into a pool (the public good), I’ll multiply by say 3, but then I’ll divide the money equally regardless of contribution. This is similar to paying your taxes for public goods that we all benefit from, like roads, clean water, or environmental protections. The dilemma is this: the best move is for everyone to put all their money in the pool. Then they’ll all go home with $30. But it’s in my best interests to put nothing in the pool and let everyone else put their money in. If I put in nothing and they put in $10 each, I’ll go home with almost $40 ($10*9*3people / 10 = $37). What happens when we play this game?
Well, if we play it in a WEIRD8 nation, where prosocial norms tend to be higher, people put about half their money in, but as they gradually realize they can make more by putting in less, contributions dwindle to zero. One way to sustain contributions is to introduce peer punishment—allow people to spend some portion of their money to punish other people. This is similar to the kind of punishment we might see in a small village. I know who you are or at least I know your parents or people you know. If you steal my crops, I’ll punish you myself or ruin your reputation. In the game, if we introduce the possibility of peer punishment, contributions rise again. The problem is that this doesn’t scale well. As the number of people grows, we get second-order free-riding—people prefer to let someone else pay the cost of punishment. When someone cuts a queue, you grumble—someone ought to tell that person off! Someone other than me… And you can also get counter-punishment—revenge for being punished. The best solution seems to be to create a punishment institution. Pick one person as a “Leader” and allow them to extract taxes that can be used to punish free-riders. This works really well and scales up nicely. It’s similar to a functioning police force and judiciary in WEIRD nations. In fact, the models suggest that the more power you give to the leader, the more cooperation they can sustain. Aha! Problem solved. Not quite. Models like these are very useful for distilling the core of a phenomenon, they can miss things. Recall where we started—smaller-scales of cooperation can undermine the larger-scale.
In our recently published paper, we wanted to show just how easy it was to break that well-functioning institution. We did it by introducing the possibility of another very simple form of cooperation—you scratch my back, I’ll scratch yours—bribery. And then we wanted to show the power of invisible cultural pillars by measuring people’s cultural background and by trying to fix corruption using common anti-corruption strategies. We wanted to show that these strategies, including transparency, don’t work in all contexts and can even backfire.
Our “Bribery Game” was the usual institutional punishment public goods game with the punishing leader, but with one additional choice—players could not only keep money for themselves or contribute to the public pool, they could also contribute to the leader. And the leader could not only punish or not punish, they could instead accept that contribution. What happened? On average, we saw contributions fall by 25% compared to the game without bribery as an option. More than double what the pound has fallen against the USD since Brexit (~12%9). Fine, bribery is costly. The World Bank estimates $1 trillion is paid in bribes alone; in Kenya, 8 out of 10 interactions with public officials involves a bribe, and as Manfred Milinski points out in his summary of our paper, most of humanity—6 billion people—live in nations with high levels of corruption. Our model also reveals that unlike the typical institutional punishment public goods game, where stronger institutions mean that more cooperation can be sustained, when bribery is an option, stronger institutions mean more bribery. A small bribe multiplied by the number of players will make you a lot richer than your share of the public good! So can we fix it?
The usual answer is transparency. There are also some interesting approaches, like tying a leader’s salary to the country’s GDP—the Singaporean model10. So what happened when we introduced these strategies? Well, when the public goods multiplier was high (economic potential—potential to make money using legitimate means—was high) or the institution had power to punish, then contributions went up. Not to levels without bribery as an option, but higher. But in poor contexts with weak punishing institutions, transparency had no effect or backfired. As did the Singaporean model11. Why? Consider what transparency does. It tells us what people are doing. But as psychological and cultural evolutionary research reveals, this solves a common knowledge problem and reveals the descriptive norm—what people are doing. For it to have any hope of changing behavior, we need a prescriptive or proscriptive norm against corruption. Without this, transparency just reinforces that everyone is accepting bribes and you’d be a fool not to. People who have lived in corrupt countries will have felt this frustration first hand. There’s a sense that it’s not about bad apples—the society is broken in ways that are sometimes difficult to articulate. But societal norms are not arbitrary. They are adapted to the local environment and influenced by historical contexts. In our experiment, the parameters created the environment. If there really is no easy way to legitimately make money and the state doesn’t have the power to punish free-riders, then bribery really is the right option. So even among Canadians, admittedly some of the nicest people in the world, in these in-game parameters, corruption was difficult to eradicate. When the country is poor and the state has no power, transparency doesn’t tell you not to pay a bribe, it solves a different problem—it tells you the price of the bribe. Not “should I pay”, but “how much”?
There were some other nuances to the experiment that deserve follow up. If we had played the game in Cameroon instead of Canada, we suspect baseline bribery would have been higher. Indeed, people with direct exposure to corruption norms encouraged more corruption in the game controlling for ethnic background. And those with an ethnic background that included more corrupt countries, but without direct exposure were actually better cooperators than the 3rd generation+ Canadians. These results may reveal some of the effects of migration and historical path dependence. Of course, great caution is required in applying these results to the messiness of the real world. We hope to further investigate these cultural patterns in future work. The experiment also reveals that corruption may be quite high in developed countries, but its costs aren’t as easily felt. Leaders in richer nations like the United States may accept “bribes” in the form of lobbying or campaign funding and these may indeed be costly for the efficiency of the economy, but it may be the difference between a city building 25 or 20 schools. In a poor country similar corruption may be the difference between a city building 3 or 1 school. Five is more than 3, but 3 is three times more than 1. In a rich nation, the cost of corruption may be larger in absolute value, but in a poorer nation, it may be larger in relative value and felt more acutely.
The take home is that cooperation and corruption are two sides of the same coin; different scales of cooperation competing. This approach gives us a powerful theoretical and empirical toolkit for developing a framework for understanding corruption, why some states succeed and others fail, why some oscillate, and the triggers that may lead to failed states succeeding and successful states failing. Our cultural evolutionary biases lead us to look for whom to learn from and perhaps whom to avoid. They lead us to blame individuals for corruption. But just as atrocities are the acts of many humans cooperating toward an evil end, corruption is a feature of a society not individuals. Indeed, corruption is arguably easier to understand than my fearless acceptance of my anonymous barista’s coffee. Our tendency to favor those who share copies of our genes—a tendency all animals share—lead to both love of family and nepotism. Putting our buddies before others is as ancient as our species, but it creates inefficiencies in a meritocracy. Innovations are often the result of applying well-established approaches in one area to the problems of another. We hope the science of cooperation and cultural evolution will give us new tools in combating corruption.
1 Putting aside what it means for something to be natural for our species, suffice to say these are recent inventions in our evolutionary history, by no means culturally universal, and not shared by our closest cousins.
2 Genes that identify and favor copies of themselves will spread.
4 The United Nations Human Development Index ranks the United States 10th in the world. Liberia is 177th.
5Temporal discounting the degree to which we value the future less than the present. Our tendency to value the present over the future is one reason we don’t yet have Moon or Mars colonies, but the degree to which we do this varies from society to society.
6 Written laws can serve a signaling and coordination function; rather than having to interpret norms from the environment. When previously contentious norms are sufficiently well established, you may do well to codify them in law (legislating before they are established might mean more punishment—consider the history of prohibition in the United States).
7 Not that agriculture is the main reason for these cultural differences!
10 Singapore’s leaders are the highest paid in the world, but the nation also has one of the lowest corruption rates in the world—lower than the Netherlands, Canada, Germany, UK, Australia, and United States [source].
11 Note, there are some conceptual issues that make interpretation of the Singaporean treatment ambiguous. We discuss this in the supplementary. We’ll have to further explore this in a future study. Such is science.
