Most of the empirical research on sex differences and cultural variations in morality has relied on within-culture analyses or small-scale cross-cultural data. To further broaden the scientific understanding of sex differences in morality, the current research relies on two international samples to provide the first large-scale examination of sex differences in moral judgements nested within cultures. Using a sample from 67 countries (Study 1; n = 336 691), we found culturally variable sex differences in moral judgements, as conceptualized by Moral Foundations Theory. Women consistently scored higher than men on Care, Fairness, and Purity. By contrast, sex differences in Loyalty and Authority were negligible and highly variable across cultures. Country-level sex differences in moral judgements were also examined in relation to cultural, socioeconomic, and gender-equality indicators revealing that sex differences in moral judgements are larger in individualist, Western, and gender-equal societies. In Study 2 (19 countries; n = 11 969), these results were largely replicated using Bayesian multi-level modelling in a distinct sample. The findings were robust when incorporating cultural non-independence of countries into the models. Specifically, women consistently showed higher concerns for Care, Fairness, and Purity in their moral judgements than did men. Sex differences in moral judgements were larger in individualist and gender-equal societies with more flexible social norms. We discuss the implications of these findings for the ongoing debate about the origin of sex differences and cultural variations in moral judgements as well as theoretical and pragmatic implications for moral and evolutionary psychology.
Those higher in ambivalence (seeing both sides, the pros & cons) display less bias.
Ambivalence refers to the experience of having both positive and negative thoughts and feelings at the same time about the same object, person, or issue. Although ambivalence research has focused extensively on negative consequences, recently, scholars turned their lens to the positive effects of ambivalence, demonstrating beneficial effects on judgements and decision‐making processes. So far, this work has focused on state ambivalence, which is ambivalence as a direct response to a specific stimulus. However, there are substantial individual differences in ambivalence: Some people are just more ambivalent than others. Taking a first step in understanding how these individual differences relate to judgement and decision‐making, we examine the relationship between trait ambivalence and cognitive bias in social judgements tasks. Specifically, we look at two of the most pervasive and consequential attribution biases in person perception: correspondence bias and self‐serving bias. We find a negative relationship between trait ambivalence and correspondence bias. The higher individuals are in trait ambivalence, the smaller their bias towards attributing behaviour to a person’s disposition (Study 1A and B). We find the same for self‐serving bias (Study 2A and B). In sum, we show that trait ambivalence is negatively related to cognitive bias in person perception.
In a pre-publication paper titled “Morality justifies motivated reasoning in the folk ethics of belief,” Cusimano and Lombrozo report that people “treat moral considerations as legitimate grounds for believing propositions that are unsupported by objective, evidence-based reasoning.” The researchers also found that people who deemed beliefs morally good also considered those same beliefs logically sound, even when the “good” belief lacked supportive evidence.
“Across three studies, many people prescribed motivated reasoning to others, reported that morally good beliefs require less evidence to be justified, and that, in some circumstances, a morally good belief can be justified even in the absence of sufficient evidence,” Cusimano and Lombrozo write.
Read more at Reason
Further evidence that people intuitively assume that their moral intuitions supersede the laws of physics. Also see my posts The Fundamental Premise, Truth vs Morality; Rationality vs Intuition, or Truth vs Morality II.
A stranger than fiction Roman ring mystery thread: this enigmatic Roman gold ring was found in a ploughed field near Silchester in 1785. The square bezel has a portrait of the pagan goddess Venus, inscribed backwards SUNEV for use as a signet ring by the owner. Curiously…
…around the ten-sided ring is crudely inscribed the identity of a later Christian owner, “Senicianus” who it proclaims with spelling errors “lives in god” (vivas in deo). A ring passing from pagan to Christian hands – certainly possible in the 4th century – but remarkably…
at a temple to the mysterious British god “Nodens” 80 miles away in Lydney, Gloucestershire, a lead curse tablet (defixio) was later discovered. On the tablet a man named “Silvianus” complains that his gold ring was stolen and he suspects “Senicianus” was the culprit! …
Silvianus deposited the curse tablet and donated at the temple half the value of his lost ring, in the hope that the gods would “permit no good health to Senicianus.” In 1929 the archaeologist Mortimer Wheeler would make a connection between this curse and the gold ring…
Wheeler consulted a certain young J.R.R. Tolkien, Professor of Anglo-Saxon at Oxford University, to work on the etymology of the curious deity Nodens and explore the possible connections with the enigmatic Roman gold ring…
Soon afterwards Tolkien would begin creating his legendarium of Middle-earth with both “The Hobbit” and “The Lord of the Rings” revolving around the magical, golden and often-stolen One Ring that grants the wearer invisibility. Had Tolkien been inspired by the Silvianus ring?
We might fancifully conclude then that in the mid 4th century AD, Silvianus – a late-Roman man still clinging on to the old pagan gods, had his beloved Venus ring stolen from him by a Christian that he knew named Senicianus. The pious thief then rededicated the pagan ring…
…with his own ironic inscription, saying he “lives in God”. The bitter Silvianus then travelled to an ancient pagan temple to deposit a curse on the Christian thief. We know the ring was subsequently lost but are left to imagine if fate ever caught up with Senicianus…
Two millienia later, both the ring and the curse on its thief are both discovered 80 miles apart. Wheeler and Tolkien, titans in their fields, analyse the mysterious artefacts and just maybe, the gold ring goes on to inspire one of the greatest works of fantasy literature.
Can you tell me what’s wrong with this ad?
How about this headline?
Still can’t see it? Maybe this will help:
All of these pictures — especially the one that appeals to racists — are missing a key statistic. One that, since it’s missing, gets filled in by your intuition. In this case, a bias called the Adjustment Heuristic.
Let’s look at the first one. Someone hit at 30mph is twice as likely to die than at 25mph.
Twice as likely! That’s like, multiplying by two! Anything multiplied by two is some gargantuan number!
Fun fact: You’re twice as likely to win the lotto if you buy two tickets! How has this life hack not been exploited already?
And therein lies the bias. Your intuition inserted a number where twice that number makes the ad scary. Is someone hit at 25mph 30% likely to die? 3% likely? 0.3%?
Let’s look at the last picture, which appeals to racists. As I wrote on Quora:
Racism/sexism is what happens when you use too little information (one’s sex or race) to make too large an inference. Or in other words, it’s a failure of statistical reasoning.
Let’s take racism. If black people commit crime at twice the rate of white people, what does this say about the next black person you meet? Are they twice as likely to be a criminal as a white person?
With no other info other than their race, sure. But unless white people are already terribly criminal, this should have very little influence on how you interact with this black person: double of some number that is almost zero (the white person crime rate) is still almost zero. Racism in this case is thinking your behavior should be significantly different between this black person and a white person.
The same sort of failure of reasoning lies behind most sexism. That there are average differences between the sexes shouldn’t alter your behavior towards individual women. Averages gives you information about the population they belong to. And the population someone belongs to only gives you a prior probability about their behavior as an individual. There’s plenty more info about them as an individual that one should be using to inform your judgement.
Ignoring them as an individual is racism/sexism.
This is why the only way to overcome bias is to shut up and multiply. Make the probabilities that already exist in your head explicit. Any method that doesn’t do this is more than likely going to exacerbate bias. And it should, since most unconscious bias training doesn’t understand what causes bias so just introduces other biases that they think will counteract the biases they’re trying to avoid.
Let me be clear: Bias is what happens when we use our intellect to defend conclusions reached by our (moral) intuitions or emotions. So of course if you just teach people about bias, they’re going to use their knowledge of bias to defend their biases.
So yeah. When overcoming bias, don’t forget to shut up and multiply. Or you’re just spinning your wheels in the dirt.
I sometimes ask students what their position on slavery would have been had they been white and living in the South before abolition. Guess what? They all would have been abolitionists! They all would have bravely spoken out against slavery, and worked tirelessly against it.
Of course, this is nonsense. Only the tiniest fraction of them, or of any of us, would have spoken up against slavery or lifted a finger to free the slaves. Most of them—and us—would have gone along. Many would have supported the slave system and happily benefited from it.
So I respond by saying that I will credit their claims if they can show evidence of the following: that in leading their lives today they have stood up for the rights of unpopular victims of injustice whose very humanity is denied, and where they have done so knowing:
(1) that it would make them unpopular with their peers, (2) that they would be loathed and ridiculed by powerful, influential individuals and institutions in our society; (3) that they would be abandoned by many of their friends, (4) that they would be called nasty names, and
(5) that they would risk being denied valuable professional opportunities as a result of their moral witness. In short, my challenge is to show where they have at risk to themselves and their futures stood up for a cause that is unpopular in elite sectors of our culture today.
Robert P. George
How do you know your belief in science is not akin to someone’s faith in spirits? What epistemologically separates the belief that science works from the belief in spirits?
There are a number of reasons.
However, the most important is that the method of scientific investigation is vastly different than belief in spirits. There’s no real “methodology” when it comes to belief in spirits. It’s whatever seems intuitivelycorrect. In this sense, there’s absolutely zero intellectual humility involved.
Contrast this with the scientific method that takes into account human fallibility and attempts to place safeguards that will help us from fooling ourselves.
This is a massive difference in epistemic “first principles” if you will. Belief in spirits assumes that your senses and your interpretation of those sensory inputs are flawless. The scientific method assumes the opposite: That you are the easiest person for you to fool.
Notice that I keep saying “scientific method” and not “science”. This is for a reason: When people talk about belief in science in contrast to belief in some other “way of knowing”, they are attempting to compare dogmas, or lists of facts. If you think the most important thing about science is that it’s a list of facts that you have to believe or you’re “wrong” then you’re already starting on the wrong foot.
The power of science lies in its methodology. The only reason any list of facts that come from the scientific method have any relevance in the first place is because of the methodology. The methodology is all about inching closer to what’s actually real, and as we inch closer and closer those “lists of facts” may change. It’s all about constant refinement and improvement, the hallmark of any endeavor that has any worth. No such methodology exists for belief in spirits.
Distilled to its most basic form, the scientific method is a system of logic applied to uncertainty. Or in other words, probability theory. Other systems of logic that operate under uncertainty, if they want to get at what’s most likely correct, properly utilize probability theory. This applies to science, medicine, law, history, military intelligence, and many other fields that are serious about getting the best footing possible in a sea of uncertainty.
Belief in spirits follows no models of probability. And in many cases, actively fights against having cold, impersonal logic and probability applied; any field that has a negative view of logic and probability is an anti-epistemology.
And is worthless as knowledge.
That is the main difference between the scientific method and belief in spirits. One is actually a rigorous, self-improving, and self-critical system. The other actively tries to obscure any acquisition of knowledge.
The term, “not falsifiable” to describe a concept as not real science is completely obscure to me. What does it refer to?
What if I told you that the entire universe was created last Thursday. All of our memories of everything past last Thursday were also created last Thursday.
There’s no way to disprove this. Someone can point out how we have observed scientific data like supernovae, coupled with what we know about the speed of light, which shows that these stars’ explosions took place both a long time ago and far away.
Nope. Those were created in media res last Thursday as well.
As I’ve presented it, there’s no observation possible that can be inconsistent with Last Thursdayism. This is what it means to be “not falsifiable”.
The concept of falsifiability was put forth by philosopher of science Karl Popper. But falsifiability is not just a philosophical defense of science. The drawbacks of having a non falsifiable model can be described mathematically.
This is Bayes Theorem:
P(H | E) means “the probability of H given E”. Let’s say H means “hypothesis” (or “model”) and E means “evidence” (or “data/observation”).
Bayes shows you how much more or less probable a hypothesis is given some evidence.
Instead of Last Thursdayism, let’s take on a real-world unfalsifiable hypothesis: Creationism / Intelligent Design. Creationists say that everything in the biological world was created by the Christian god. The Christian god is all powerful, so nothing is beyond His capabilities, right?
Let’s say our hypothesis H is Creationism, and our evidence E is “dolphins having a whole hand in their flippers”. Let’s also assume a position of agnosticism about Creationism, or P(H) = 50%.
Creationists says, dolphin skeletons showing a friggin’ HAND in their flippers fits perfectly with the hypothesis, right? In other words, assuming Creationism is true there’s nothing inconsistent with God giving dolphins hands in their flippers; meaning a 100% likelihood of dolphins having fingers and thumbs in their flippers. Or P(E | H) is 100%.
Now we get to the tricky part, so bear with me.
P(E) in the denominator is the probability of the evidence. It’s also called the Total Probability, and also has a formula:
Assume that A is actually E, and B is H for consistency. This reads, P(E) is a sum of various probabilities; with E staying the same but with alternative hypotheses (H). Which means we should be taking hypotheses other than Creationism into account when evaluating Creationism.
Let’s go with a simple alternative hypothesis: dolphins and humans have a common ancestor, which explains why the appendages have similar bone structures. Since related probabilities have to add up to 100%, and we’ve already assumed P(H) is 50%, this means that P(~H) — the theory of evolution — is also 50%.
This means we’re working with the long form of Bayes Theorem:
P(E | ~H), or the probability of dolphins having what looks like the skeleton of a human hand in their flippers, given that the theory of evolution is correct, is some value. Let’s say we are a die-hard Creationist and just assert that there is only a 1% chance of this being true.
Here’s the part where we start explaining why a non-falsifiable hypothesis is bad, beyond the arguments and assertions of philosophers of science.
I explained that P(H) and P(~H) together has to add up to 100%, which is why if P(H) is 50%, P(~H) is also 50%. But there are other terms in Bayes Theorem that have to exhaust the hypothesis space like P(H) + P(~H) have to.
P(E) plus P(~E) equals 100%
P(E | ~H) plus P(~E | ~H) equals 100%
P(E | H) plus P(~E | H) equals 100%
It’s this last one we want to pay attention to: The probability of not having the evidence given that the hypothesis is true.
For Creationism, what would that be? Assuming for Creationism the evidence we have — dolphins having the bone structure for grabbing things in their flippers even though they absolutely cannot grab things with their flippers — is expected. P(E | H), or P(Dolphins With Five Fingers | Creationism), is 100%.
But remember that P(E | H) plus P(~E | H) equals 100%. Which means if we assert that P(Dolphins With Five Fingers | Creationism) is 100% we are also asserting by inference that P(Dolphin With Some Other Skeletal Form In Their Flippers | Creationism), is 0%.
Would Creationism really concede that, if we had discovered dolphins with a bone structure that looks like a single flipper instead of a hand, this disproves Creationism? That there’s a zero percent chance of this happening? That this is beyond God’s abilities?
Of course not.
So instead of that concession, we have to concede — based on the rules of basic math — that P(Dolphins With Five Fingers | Creationism) is not 100%. It’s some number less than 100%. What this number is, is besides the point. The actual point is… what type of flipper structure is inconsistent with an all powerful god?
I’ve only introduced two hypothetical datapoints: P(Dolphins With Five Finger Bones | Creationism) and P(Dolphins With One Flipper Bone | Creationism) = 100%. Or, written in shorthand, P(E1 | Creationism) + P(E2 | Creationism) = 100%. What’s stopping God from other hypothetical evidence? P(E3 | Creationism), P(E4 | Creationism), P(E5 | Creationism), P(E100 | Creationism)? Is there any P(En | Creationism) that is so beyond God’s capabilities that it shouldn’t be included? Isn’t the limit really no limit at all? With God, all things are possible!
And that’s the problem. If P(E1 | Creationism) + P(E2 | Creationism) + P(E3 | Creationism) + … P(En | Creationism) = 100%, the probability of any one of those possible observations — with no other way to differentiate them — is n / 100. if n is infinity, what does this say about P(Dolphins With Five Finger Bones | Creationism) or P(Dolphins With One Flipper Bone | Creationism)? They are evidence out of an infinite sea of God’s possibilities; their individual likelihoods are vanishingly (infinitely…) small.
On the other hand (lol), P(Dolphins With One Flipper Bone | Theory of Evolution) should be zero, since dolphins that have a single flipper bone instead of a hand would be, rightly so, evidence against common descent.
As a somewhat off topic note, notice that Bayes Theorem doesn’t say anything about “scientific” in and of itself. Even though it’s not explicit, a lot of other problem-solving endeavors take a Bayesian approach to creating solutions. Your plumber, when diagnosing what’s causing your plumbing problems, does not bother with unfalsifiable explanations (e.g., invisible gremlins from the 5th dimension are responsible for your plumbing problems). Almost everything, from astrophysics to finding where you left your keys, are inferences to the best explanations.
Falsifiability might have been introduced as a defining element of science, but falsifiability is actually Bayesian, and science is just a special case of strong Bayesian evidence.
Other elements of good science — like extraordinary claims requiring extraordinary evidence, Occam’s Razor, absence of evidence is evidence of absence, the provisional nature of science — are also Bayesian and able to be expressed mathematically. Meaning that all of those things that are elements of good science are also elements of good troubleshooting in more mundane, everyday areas. Even and especially things that don’t claim to be science but are attempting to model the world.