Thursday 28 June 2018

Review: Inferior by Angela Saini

This book is about the science of ... women, I think. It was a bit confusing at first because the first chapter or so is about women in science and I thought maybe the whole book was, but it's generally about what science says about women in many different respects like lifespan, health, menopause, discrimination, aptitudes, brains.

It was generally quite interesting, and some of it infuriated me when it talked about the ridiculous sexism women experience. There were lots of examples of this so get ready for lots of quotes:



In a study published in 2012, psychologist Corinne Moss-Racusin and a team of researchers at Yale University explored the possibility of gender bias in recruitment by sending out fake job applications for a vacancy of laboratory manager. Every application was identical except that half were given a female name and half a male name. When they were asked to comment on these potential employees, scientists rated women significantly lower in competence and hireability. They were also less willing to mentor them and offered far lower starting salaries. The only difference, of course, was that these applicants appeared to be female.

Another study, published in 2016 in the world’s largest scientific journal, PLOS ONE, looked at how male biology students rated their female counterparts. Cultural anthropologist Dan Grunspan, biologist Sarah Eddy, and their colleagues asked hundreds of undergraduates at the University of Washington what they thought about how well others in their class were performing. “Results reveal that males are more likely than females to be named by peers as being knowledgeable about the course content,” they wrote. This didn’t reflect reality. Male grades were overestimated—by men—by 0.57 points on a four-point grade scale. Female students didn’t show the same gender bias.

The year before, PLOS ONE had been forced to apologize after one of its own peer reviewers suggested that two female evolutionary geneticists who had authored a paper should add one or two male coauthors. The paper itself was about gender differences among doctorates. “Perhaps it is not so surprising that on average male doctoral students co-author one more paper than female doctoral students, just as, on average, male doctoral students can probably run a mile a bit faster than female doctoral students,” wrote the reviewer.

In 2015 virus researcher Michael Katze was banned from entering the laboratory he headed at the University of Washington following a string of serious complaints, which included the sexual harassment of at least two employees. BuzzFeed News (which Katze tried to sue to block the release of documents) ran a lengthy account of the subsequent investigation, revealing that he had hired one employee “on the implicit condition that she submit to his sexual demands.”

 ^ What the fuck?! Who does that?!


The Royal Society of London, officially founded in 1663 and one of the oldest scientific institutions still around today, failed to elect any women to full membership until 1945. It took until the middle of the twentieth century, too, for the prestigious academies of Paris and Berlin. “For nearly three hundred years, the only permanent female presence at the Royal Society was a skeleton preserved in the society’s anatomical collection,

Even assuming she was given the same schooling as a boy, it was unusual for a girl to be allowed into universities or granted degrees until the twentieth century. “From their beginnings European universities were, in principle, closed to women,” writes Schiebinger. They were designed to prepare men for careers in theology, law, government, and medicine, which women were barred from entering. Doctors argued that the mental strains of higher education might divert energy away from a woman’s reproductive system, harming her fertility.
 Cambridge would wait until 1921 to award degrees to women. Similarly, Harvard Medical School refused to admit women until 1945. The first woman applied for a place almost a century earlier. This doesn’t mean that female scientists didn’t exist. They did. Many even succeeded against the odds. But they were often treated as outsiders and routinely overlooked for honors. The most famous example is Marie Curie, the first person to win two Nobel Prizes, but nevertheless denied from becoming a member of France’s Academy of Sciences in 1911 because she was a woman.
When mathematician Emmy Noether was put forward for a faculty position at the University of Göttingen during the First World War, one professor complained, “What will our soldiers think when they return to the university and find that they are required to learn at the feet of a woman?” Noether lectured unofficially for the next four years under a male colleague’s name and without pay.
ARGHH the unfairness! It just drives me insane. This isn't even to do with whether female intelligence is slightly different to male intelligence (which I think the jury is still out on), this is just completely excluding women due to pure sexism and disrespect of women. God it makes me angry. 

Also, the book made me sad because it talked about the sexism of various historical figures, particularly in evolutionary theory, who I looked up to, like Darwin and Trivers.

Quote from Darwin:



“The chief distinction in the intellectual powers of the two sexes is shewn by man attaining to a higher eminence, in whatever he takes up, than woman can attain—whether requiring deep thought, reason, or imagination, or merely the use of the senses and hands,” he explains in The Descent of Man. For Darwin, the evidence appeared to be all around him. Leading writers, artists, and scientists were almost all men. He assumed this inequality reflected a biological fact. Thus, his argument goes, “man has ultimately become superior to woman.” This all makes for astonishing reading now. Darwin writes that if women had somehow managed to develop some of the same remarkable qualities as men, it may have been because they were dragged along on men’s coattails by the fact that children happen to inherit a bit of everything from both parents in the womb. Girls, by this process, manage to steal some of the superior qualities of their fathers. “It is, indeed, fortunate that the law of the equal transmission of characters to both sexes has commonly prevailed throughout the whole class of mammals; otherwise it is probable that man would have become as superior in mental endowment to woman, as the peacock is in ornamental plumage to the peahen.”

ARGHHH. Not a very articulate review in this part perhaps, but it is absoutely maddening. And then men like to use women's fury at sexism to call us 'overly emotional', when they'd certainly be emotional if this had been done to them for thousands of years.

It's a really good point that scientists have historically taken the lower status of women as proof of women's biological inferiority when of course they're missing a pretty huge confounding variable. Then I suppose the bigger question is how were women subjugated in the first place? How did this culture start? I guess it helps that dudes are bigger and so could just manhandle women into doing their bidding.

A relevant quote from a feminist who wrote to Darwin: “Let the ‘environment’ of women be similar to that of men and with his opportunities, before she be fairly judged, intellectually his inferior, please.”

More infuriating sexism: 

They weren’t even recognized as full citizens by their own countries. By 1887 only two-thirds of US states allowed a married woman to keep her own earnings. And it wasn’t until 1882 that married women in the United Kingdom were allowed to own and control property in their own right.
The AUDACITY of trying to relate questions after conferences to evolution like this.
Through a “runaway process” in which smarter males mated more often and sired smarter offspring, Miller argues, the human brain could have reached its relatively large size as quickly as it did. “Male nightingales sing more and male peacocks display more impressive visual ornaments. Male humans sing and talk more in public gatherings, and produce more paintings and architecture,” he writes. Later he adds, “Men write more books. Men give more lectures. Men ask more questions after lectures. Men dominate mixed-sex committee discussions.” Men are better at all these things, he implies, because they have evolved to be better. For anyone who fears this might be a little unfair to women, Miller has a response. “In the game of science,” he advises his readers, “sounding sexist is not a good reason to ban a theory.” 

There was just no need for that kind of sexism. No justification.

There was a discussion of selective abortion and infanticide in Asia and god, how horrible. There was a story of a woman whose husband tricked her into eating something she was allergic to so he could bring her to the hospital and get a scan to find out the sex of her twins, and then on finding out that they were female pressured her to get an abortion, wouldn't let her eat and kicked her down the stars. Also, a doctor said that in hospitals in South Asia you can find children's wards 80% full of boys, because sick girls just aren't brought to the hospital.

Apparently biologically girls survive much better than boys; female newborns have a 10% higher chance of surviving than male ones. And yet in these Asian countries demographics are skewed in favour of boys - that's how much they're discriminating against girls. So disgusting.

Women generally survive better at every stage of life and have later ages of onset of most common diseases including heart disease and cancer, and kidney disease progresses faster in men.

Sexism is just so unnecessarily pervasive. Look at this! 


In research on the evolution of genitals (parts of the body we know for certain are different between the sexes), scientists have also leaned toward males. In 2014 biologists at Humboldt University in Berlin and Macquarie University in Sydney analyzed more than three hundred papers published between 1989 and 2013 that covered the evolution of genitalia. They found almost half looked only at the males of the species, while just 8 percent looked only at females. One reporter described it as “the case of the missing vaginas.”





There was a chapter on brain differences between men and women, basically asking whether the well-known physical differences in e.g. physical strength extend to mental differences. Lots of different studies and scientists were presented but really the impression I got of the field was that it's a mess; so many people seemed to be operating based just on their opinions of how things should be, or using archetypes like (ugh) Simon Baron-Cohen with his 'empathizing' vs 'systematizing' shite.

The chapter talked about the 'missing 5 ounces of the female brain' and wow it's so dumb, they just kept insisting absolute brain size was the important thing rather than even brain-to-body-ratio. A quick gripe first: PICK A UNIT! How am I supposed to compare between these three different units?!


1,150 grams (approx. 2.5 pounds), around five ounces less than the average male brain




George John Romanes, an eminent evolutionary biologist and friend of Charles Darwin, also weighed in. “Seeing that the average brainweight of women is about five ounces less than that of men, on merely anatomical grounds we should be prepared to expect a marked inferiority of intellectual power in the former,” he argued in Popular Science Monthly. “We must look the facts in the face. How long it may take the woman of the future to recover the ground which has been lost in the psychological race by the woman of the past, it is impossible to say; but we may predict with confidence that, even under the most favourable conditions as to culture, and even supposing the mind of man to remain stationary,…it must take many centuries for heredity to produce the missing five ounces of the female brain.”

Some researcher (in contemporary times) found that there's more blood flow through the male brain and made a very big deal of it. But this part was interesting to me: 


In the 1970s sex difference research had experienced a decline because gender scholars and women’s rights campaigners argued that it was sexist to look for biological gaps between women and men, just as it was racist to look for differences between black and white people. Gradually, though, it became acceptable again.
Why IS it acceptable to do it by sex but not by race? I'm not really for banning looking for sex differences, though I do take issue with how they're interpreted, but by that logic we should do it by race too. Which brings me to a similar point - I've noticed that the word 'racist' seems much scarier to people than the word 'sexist' does; sexism, at least in my experience, is more accepted than racism. Neither should be accepted and this inequality in inequalities pisses me off. 

She mentions stereotype threat uncritically, but I've heard that the famous stereotype threat study is actually overcooked and failing to replicate and wow very dodgy stats that I don't know how they got away with in the first place.

Also, she said 'From breasts and vaginas to brain structure and cognitive ability, for every difference or similarity we see, there must be some evolutionary purpose to it', which is something the author of Junk DNA also said and remains untrue -- things can just be there by drift or descent, no? Sure, less likely for big anatomical things to happen by drift maybe, but she says every difference.


Expectant mothers almost always have people to help them when their babies are due. In my case, it was an entire team, including my husband, sister, doctors, and a midwife. Anthropologists Wenda Trevathan at New Mexico State University and Karen Rosenberg at the University of Delaware have noted that childbirth is a lonely activity in few human cultures. Helpers are so important that women may even have evolved to expect them, they’ve argued. Their theory is that the awkward style of delivery of human births and the emotional need that mothers have to seek support during birth may be adaptations to the fact that our ancestors had people aiding them when they delivered their babies.

How is that an adaptation? What? Am I missing something?

Something funny: '“One of the primary traits that we have is that we’re sort of the rabbits of the great ape world,” explains Richard Gutierrez Bribiescas, professor of anthropology at Yale University,'.
Apparently this is a thing; 


In Amazonian South America, there are communities that accept affairs outside marriage and hold a belief that when a woman has sex with more than one man in the run-up to her pregnancy, all their sperm help build the fetus. This is known by academics as “partible paternity.”

I don't get this at all. Has no one told them the science?  Do they actually believe this? And it's just okay for them to be wrong? If they found out would the other fathers stop supporting 'their' kid? What.

She has this ~controversial~ quote (cos trans people): 'the biological fact that women give birth and lactate'. 
There was an interesting bit about how babies are brought up unconsciously differently:



In her most recent research project, Fausto-Sterling has tried to get closer to answers by filming mothers playing with their children. She recounts one vivid example: “You see a little three-month-old boy, just slouched on the couch. He’s not even big enough to sit up on his own, but he’s kind of propped up with pillows. His mother is trying to engage him in play, and she’s stuffing little soft footballs in his face, American footballs… . She’s thrusting this football at him and saying, ‘Don’t you want to hold the football? Don’t you want to play football like your daddy does?’ And he’s just sitting there like a kind of blob. He has no interest one way or the other,” she describes. The impact of actions like these, small as they may seem, can be long lasting. “If that kind of interaction is going on iteratively in the early months, then if at some point he does reach out and grab, when he’s big enough to do that, at four months, five months, or six months, he’s going to get a very positive reinforcing response from his mother,” Fausto-Sterling explains. This relationship between the boy and footballs is strengthened as he sees how happy they make his mother, and also because the toy is already so familiar to him. “He may see them again at an older age, when he is more capable of physically interacting with them. And just seeing them and recognizing them may give him a certain kind of pleasure.” By the end, the boy appears to love football. Fausto-Sterling adds that evidence is emerging from her team’s observations of mothers that boys are also handled differently from girls, which might be influencing the way they grow. “The mothers of sons in my cohort are moving them around a lot more. They’re shifting them, they’re playing with them, and they’re talking to them less. They’re more affectionate to them when they’re moving them physically.” This could simply be because boys demand more physical movement from the start, but again, it’s another element of the development process that hasn’t been fully studied.


Some people have suggested that the means for male and female intelligence are pretty much the same but men have more variability, so more at the top and bottom of the IQ scale. But apparently that effect is concentrated at the bottom because boys are much more likely to have mental retardation. They did see a significant different at the top end too though which is worrying.

One of the most interesting chapters was 'Choosy or Chaste?', which talked about how women do actually have sexual desire but men have specifically suppressed it throughout human history in a manifestation of mate guarding. 

Infidelity



Hanuman langurs of Mount Abu forty years ago showed that a female monkey can benefit from mating with more than one male because it confuses them all over their possible paternity of her children, making them less likely to commit infanticide.


When Scelza started doing fieldwork with the Himba in 2010, women would ask her why she didn’t have men coming to her hut. “Well, I said, ‘You know, I’m married.’ And they said, ‘Yeah, yeah, but that doesn’t matter. He’s not here.’ So then I tried to explain that my marriage was a love match, because then I thought they would understand. And they said, ‘It doesn’t matter. It’s okay, it’s okay. He’s not going to know; it’s okay,’” she recalls. “They really hold a very different idea in their heads about love and sex, that it wouldn’t be a bad thing at all for me to say, on the one hand, that I really love my husband but that I’ll still be having sex with somebody else when we’re apart. That, to them, was not a transgression.”


There was apparently some campus study that purported to show that men were more promiscuous than women because when researchers went to bars and asked them to sleep with them the men usually said yes whereas the women never did, but a later redo of the experiment found that women were much more likely to say yes than before when the experiment was done in a safe place so not just going back to some random dude's house when he could attack you.

Also, apparently Bateman's seminal fly study about how female flies don't really bother with mating but get enough but males have high variability in whether they'll get a mate or not was super flawed, which is concerning because I read that uncritically for Schols. 


d contradicted Bateman in the most fundamental way. “We observed the movements of females and males in vials during the first five minutes of exposure to one another. Video records revealed females went toward males as frequently as males toward females; we inferred that females were as interested in males as males in females,” they wrote in their paper, published in the journal Evolution in 2002. This raised the dilemma of just how Bateman managed to see what he claimed to see in his own fruit flies. Investigating further, Gowaty soon began to notice problems with Bateman’s study. In a subsequent paper, published in 2012 in Proceedings of the National Academy of Sciences, Gowaty and researchers Yong-Kyu Kim and Wyatt Anderson at the University of Georgia, wrote, “Bateman’s method overestimated subjects with zero mates, underestimated subjects with one or more mates, and produced systematically biased estimates of offspring number by sex.” They claim that Bateman counted mothers as parents less often than fathers, which is a biological impossibility, since it takes two to make a baby. Another error is that the same genetic mutations Bateman needed his flies to have so he could distinguish the parents from their offspring also affected the fruit flies’ survival rates. A fly with two severe and debilitating mutations, such as uncomfortably small eyes and deformed wings, could have died before Bateman had the chance to count it. This would have almost certainly skewed his results, too. The mistakes are so clear, claims Gowaty, that Bateman’s 1948 paper could only have been published if the editor—who should have checked for errors—hadn’t actually read it. Failure to replicate scientific findings is a big deal. Often it leaves grave doubts about the original experiment. And for an experiment as important as Bateman’s it should cause enormous concern. In this case, though, the reaction to her findings has been mixed.

Female Genital Mutilation as an extreme example of mate guarding (gory quote)


Infibulation is what was done to Wardere. It happened forty years ago, but she remembers it as vividly as if it had been this morning. She grew up assuming that being cut was something to be proud of. It was a feeling reinforced when her female relatives threw a party in her honor to celebrate the big moment. They cooked her favorite food. They told her she was about to become a woman. In her six-year-old innocence she excitedly imagined that this might mean finally trying on her mother’s makeup. “They made you feel like something amazing was going to happen,” she tells me. “It was not like that. It was the beginning of a nightmare.” In Somalia, female genital mutilation is often carried out by a respected female elder, who’s likely to have cut hundreds of girls already. Wardere recalls the woman who did it to her. “Her eyes haunt me even today. She instructed my mother, my aunties, and other helpers to hold me down, and they did. My mother looked away, but the others did hold me down. Then she ripped my flesh as I screamed and struggled and prayed to die. She just kept on going. It didn’t bother her that I was just a child. It didn’t bother her that I was begging for mercy.” Wardere’s torn flesh lay on the floor. The life sentence had been served. The cut was cruel enough, but she would also suffer recurrent urinary infections and scarring. The flashbacks would haunt her forever.
The puzzling thing about female genital mutilation is that there seem to be no winners. Not men, not women. Wives have reported depression and domestic abuse because their husbands can’t accept that they don’t want to have sex. One young man admitted to her that he couldn’t bring himself to sleep with his wife on their wedding night because she had undergone infibulation and he was scared of hurting her. If men would accept brides who weren’t mutilated, she notes, the stigma might go away. Yet, however damaging it might be to their wives and their marriages, few men stand up against the practice. And the reason for this is simple. The torture continues because it does what it was always intended to do. A woman who has been cut as a child will almost certainly remain a virgin when she’s older. It would be too painful for her to be anything else. And once she’s married, a husband can be confident that she’ll be a reliably faithful wife. Throughout history, mutilating a girl’s genitals has been the most viciously effective means of assuring a man that his children will be his own and not someone else’s. It’s as brutal a manifestation of sexual jealousy and mate guarding as anyone has ever seen. The practice has been absorbed into some cultures so fully and for so long that women now have little choice but to give it their full cooperation. Without it, they risk being ostracized. Girls put pressure on each other to be cut, like they did when Wardere was six years old. Mothers take their own daughters to be cut, like Wardere’s did. And female elders do the cutting. “It’s all instigated by women."

And another, similar enough thing that's also revolting:

When this standard isn’t enough to limit her behavior, humans have gone to elaborate lengths to enforce it. The most aggressive include forced marriage, domestic violence, and rape. One member of the gang who violently raped and killed a student on a bus in India in 2012 claimed to the BBC in an interview from prison that it was her own fault for taking the bus in the first place. As far as he was concerned, she was the one who had transgressed. “A decent girl won’t roam around at nine o’clock at night,” he told the reporters. “Housework and housekeeping is for girls, not roaming in discos and bars at night doing wrong things, wearing wrong clothes.” This double standard is even written into the laws of some countries.
Woman the Gatherer

There was also a cool discussion of 'Woman the Gatherer' rather than 'Man the Hunter' saying that women were actually vital for getting calories from the group. A study of one modern hunter-gatherer tribe found that the men were only successful in their hunts 1/30 days, so for a consistent food supply women's gathering of berries/tubers etc and hunting of small game was really important and sometimes provided more than half the group's calories.


Our Closest Ancestors

It's interesting the difference between bonobos and chimps. We're pretty much equally closely related to both, but chimps, which are aggressive and patriarchal, have long been used to explain our 'natural' behaviour whereas bonobos are only starting to be, and they're the opposite, with a more matriarchal society and mothers needed to defend their sons from being attacked by other females. 

Also, bonobos apparently love having nonreproductive sex as a sort of 'social glue', including gay sex, oral and genital massage. Also, their society runs on female friendship and cooperation (between unrelated females) -- even though males are longer, females run the place because of their alliances. And across species, size doesn't always correlate with sex or dominance.

Post-Menopausal Women

The last section posed an interesting question I wouldn't have thought of: why do women survive so long after they lose their fertility? What's the point, from an evolutionary perspective?

One interesting idea is the 'grandmother hypothesis' - childbirth was so dangerous for a woman that it was better for her to stop having babies and look after the ones she did have, or her grandchildren. There's evidence for this with the Hadza hunter-gatherers; apparently the grandmothers allow their daughters to go shorter intervals between having babies because they'll step in and mind the previous baby before it's fully independent.

An alternative hypothesis is that we're just living longer and previously would've died around menopause but now have modern medicine and tech. However, life expectancy data is flawed because once you survive childhood your life expectancy can actually be quite long, and some people in ancient times could've survived into their seventies.

Some of the other ideas are:



the follicular depletion hypothesis, which, like the extended longevity hypothesis, says that women nowadays outlive their eggs. The problem with this is that you might then expect women with more children to go through menopause later, because they’re not menstruating while pregnant. They don’t. Another hypothesis focuses on reproductive cost, saying that baby making takes such a large physical toll on a woman’s body that menopause evolved to protect her from further damage. But if this were true, we might expect to see women with more children experiencing menopause earlier, and we don’t. Another, the senescence hypothesis, offers up the possibility that menopause is just a natural feature of aging, like wrinkles or loss of hearing. And while other side effects of old age may happen gradually, including male infertility, female fertility just happens to end more abruptly for physical reasons.


Unfortunately sometimes Saini said things that I don't think were really backed up by the evidence she'd presented and she came across as a bit biased even though she said she wouldn't. I get it, I'd be biased too, but don't say you're not going to be y'know. To be clear I do think women are just as good obviously, but for specific things the  evidence to say something one way or the other just wasn't fully in and it seemed she'd already chosen a side, though in fairness she did present evidence from the other side.


4/5 stars.

Tuesday 26 June 2018

SF Multivariable Calculus

One of my favourite modules, which was a surprise since I didn't do well in Maths last year and struggled with many parts of it, especially integration. But it went a lot better this year thanks to a combination of a great lecturer and a better student since I started sitting up front, asking questions, promptly rewriting my lecture notes etc. And I got 100% in the exam! 98% overall in the module.

Topics


  • parametric curves
  • polar curves
  • vector-valued functions
  • functions of several variables
  • partial derivatives
  • double integrals
  • triple integrals
  • polar, cylindrical and spherical coordinates
  • planes and tangent planes to surfaces
  • directional derivatives and the gradient vector
  • Lagrange multipliers
  • the Jacobian matrix and determinant
Experience

I really loved the course. I'd been nervous but things just clicked this time round -- for example, I remember struggling last year to get the crossproduct of vectors using the 3x3 determinant method and using that long complicated formula instead, but it just clicked seeing this lecturer do it on the board as part of another problem (she didn't revise previous topics). It was the same with integration - I just got the hang of it eventually. One nice thing was that because of that I was good at explaining it to people who hadn't got it yet, because it hadn't come naturally to me. Now I love integration, apart from the long bit at the end with all the arithmetic and errors.

Something I really struggled with during the course was parametrization, e.g. parameterize this curve or this surface. I just didn't understand what it meant or what the point of it was and so I couldn't understand how to use it, but I finally got it just before the exam and it felt brilliant - I was even able to check an answer I got by another method in the exam using parameterization, and that independent verification gave me extra confidence that the answer was right. It was so cool finally cracking it.

The lecturer was brilliant, and it really felt like she set us up for success, which is something that can't be said for all college maths lecturers. She wrote everything out on the board and balanced theory with examples, so there was one example for each concept and she wouldn't go deep into things like the epsilon-delta definition of a limit, she'd just say 'for x arbitrarily close to' so that we could get to the examples. It was so much easier to understand and it was great because I picked up loads of skill with calculus and vectors that I hadn't got before. Yeah there's a place for proofs-based maths, but I really appreciated this course giving us what we needed as scientists. 

I wrote down what she was saying and then directly after the lecture or as soon as I had a gap I'd rewrite the notes into another, neater, notebook. She also provided scans of all her notes online in case we missed something.

She gave good homeworks - sometimes challenging but generally just in a fun way, and relevant to the course so there'd usually be some example in the notes we could refer to and see how to approach the problem rather than just searching in the dark. After the deadline, she promptly uploaded the Solutions for that homework so we could check mistakes and learn where we went wrong quickly. Coming up to the exams, she held office hours, and posted (because it was her first year teaching the course) two sample papers and also posted full solutions to them. It was brilliant, as someone with anxiety, to know how I was doing.

Another nice thing she did when I told her that I can't visualise: met with me for an hour outside class to help me come up with ways to 'visualise' the surfaces and solids in other ways so that I could solve the problems.

She also gave a really fair exam - I'd been worried about her giving us random stuff that was just barely mentioned like the triple integral Jacobian or even some stuff that was covered and in homework like symmetry properties of polar curves, but she pretty much just asked us stuff that was central to the course. Or maybe that's just because I'd covered it thoroughly.

My only gripe with the course is that I had some of my homeworks marked down a bunch for things like not putting labels on graphs or not putting coordinates on when it just said to sketch a curve, since I took the word 'sketch' literally. And the TA insulting my graph and calling it a scribble when I complained about it (it wasn't! It was a parabola, it was just very slightly shorter on one end and the center didn't perfectly coincide with the y axis but was close!).

But overall it was a brilliant course and obviously I'm delighted with my score. Helps that I literally couldn't have done better (in the exam). I learned so much that I hadn't even known I didn't know. 

(I also liked that I did one maths-for-physics module (this one) and one maths-for-non-physicists module (Stats; it conflicts with one of the Maths modules required for Physics so it's de facto not for physicists), and got 100% in this one, because now I can tell mean physics people to feck off saying I'm bad at maths coz I'm doing biology.)

Monday 25 June 2018

SF Statistics

(Technically this module was called Numerical Data Analysis and Visualisation, but there was very little visualisation and it was pretty much just core statistics soooo.)

Topics 

  • Bayes Theorem and the Monty Hall problem - adored this part
  • Probability: sample space, events, probability measure, partitioning the sample space
  • Binomial experiments
  • Random variables, expected value, variance, standard deviation
  • Continuous vs discrete random variables, probability density function 
  • Poisson, exponential, uniform and Gaussian distributions
  • Joint probability distributions
  • Sample mean, sample variance, law of large numbers, central limit theorem, confidence intervals (except we didn't really do anything about hypothesis testing, confidence intervals were just mentioned in the slides. If only we'd done stuff about C.I.s and hypothesis testing!)
  • Chi-square: we didn't do what a lot of statistics classes do, which is get data and do the chi-square test on it. Instead, we'd be given some data and a proposed model e.g. y = ax^2, and have to work out from the definition of chi square what the parameter a was which minimised chi square and then use the parameter to calculate chi square and see how good the model is. It's kinda cool being able to do that, to just go from the general shape of the model to find its exact parameter(s) and test how good they are, but a) it was unfortunate that barely anyone else seems to do this harder version and so I couldn't really find any resources online to help b) it is very very finicky, with so many squares and dividing by tiny numbers that a small arithmetic error can result in an answer 1000x off the actual answer.
  • A little bit of algorithms, contrasting Quicksort and Bubblesort. 
  • Markov chains - a Markov chain is one in which the probability of being in state i given that you were in state j is equal to the probability of being in state i given that you were in state j and before that in state k and before that in state .... so basically only the previous state matters. We learned how to construct a Markov matrix given some of these probabilities, how to get the probability of a certain outcome several steps on, how to find the longterm steady state (eigenvector) of the system, the detailed balance conditions, how to construct a matrix given its eigenvector, and absorbing states. I liked these problems once I figured out how to deal with eigenvectors - it's quite fun.                                   

Review

Very frustratingly, the lectures, homework and exams seemed to be based off three different curricula. Fortunately the exams were the easiest of the three but it was very stressful having half the homework questions just be random impossible things we hadn't been taught. The lecturer would be doing something on the board and it'd get too long or complicated and so he'd say 'I'll just ask it in the homework'. Wat. That's not the point of homework. The homework was often extremely difficult in parts and often had components that weren't taught until the day before the homework was due, so I couldn't do it in advance as I would've liked, and had to just bang my head off the wall until eventually in the tutorial me, people around me and the TA came up with something together. Such a contrast from the lovely Multivariable Calculus homeworks, in which we didn't have to guess at what the question could possibly mean. 

The exam tended to have Chi Square and Markov matrix come up every year, often with a Bayes rule diagnostics question and probability theory question. So the exam was a lot more practical, easier, and more in line with what the course booklet said. 

The lectures, on the other hand, were super difficult and confusing, often proofs-based (which is something maths students, not science students, are there for), and seemed super aimless. The lecturer would often start a topic only to move onto another one in the next class and then come back to the first one, so the arrangement of my notes made little sense and I eventually stopped rewriting my notes after class (I'd write them during the class but wouldn't rewrite them afterwards as I would for other classes) because it was just so frustrating. Another big problem was that the lecturer, much as he seemed like a nice dude, couldn't answer our questions and the class was really struggling. Close to exams he said not to worry because people don't fail his exams so I really have to wonder what the marking scheme is like because a lot of us didn't have the slightest clue. In fairness I did get a good handle on the things that came up, i.e. probability theory, Bayes rule (<3), Chi square and Markov chains (<3), but I was very glad the papers were so predictable because if he'd asked the pretty structureless stuff he talked about in his lectures it would've been very very stressful and I don't know if I could've done well.

Final result: 92%; 93% in exam. 

Review & Recap: Junk DNA: A Journey through the Dark Matter of the Genome by Nessa Carey

This book is a tour of the human genome's 'junk DNA', which the author expansively defines as DNA that doesn't code for proteins. This is taking a bit of a liberty as she thus includes many categories of DNA that I doubt any biologist would describe as junk, like tRNA and rRNA (both crucial for making proteins), telomeres (needed as cells divide to protect the ends of chromosomes, involved in aging), centromeres (needed for the formation of the spindle apparatus in mitosis) and more. She also covers enhancers, promoters, long non-coding RNAs, miRNAs and siRNAs, among others. But I imagine it's a lot easier to market a book called 'junk DNA' than one called 'DNA other than the protein-coding bits'.

The book was quite interesting overall, with lots of new information and thankfully no tired metaphors of DNA as being stored in 23 book volumes. Each chapter focused on a type of junk DNA; I particularly liked those on X chromosome inactivation (I find the sex chromosomes fascinating), telomeres, imprinting, miRNAs, and therapeutics, but I generally found the epigenetics sections boring. I think I just don't like epigenetics and so I skimmed some of those parts; I like genetics because of its digital nature, and while I do also like biochemistry, I don't really like the combination of genetics with biochem. That said, there were some interesting aspects of that, like: 

Junk DNA that acts as an insulator between repressed and active regions of the genome loses its histone proteins. No histone proteins means no epigenetic histone modifications. No modifications means no spreading of epigenetic activity. This stops repressive modifications creeping into active genes and also prevents the opposite effect
....
Some tRNA genes can act as insulators. They can stop expression of one gene driving inappropriate expression of a neighbouring gene. This is an additional benefit of having lots of tRNA genes, which demonstrates the economical way with which evolution has made the most of raw material. ... A classical protein-coding gene is coated with epigenetic modifications that promote its expression. The enzyme that binds to this gene and copies it into RNA (which will ultimately be processed to form mature messenger RNA) can be a bit of a runaway train: once it starts copying it tends to keep going. If there is another protein-coding gene nearby, the enzyme could keep going and copy this as well. But if there are two or more tRNA genes in between, this won’t happen. tRNA genes are switched on pretty much all the time, because they are involved in the creation of all proteins. There is an enzyme that copies tRNA genes to create tRNA molecules from the DNA template. But this is different from the enzyme that carries out a similar job to generate messenger RNA molecules from classical protein-coding genes.


I really enjoyed the 'sex chromosomes' section. Here's a bit on how cells can somehow count the number of X chromosomes present:

One of the oddest things we have come to realise is that our cells can count the number of X chromosomes. Male cells contain an X and a Y chromosome and they never inactivate the single X. But sometimes males are born who have two X chromosomes and one Y. They are still males, because it’s the Y chromosome that drives masculinisation. But their cells inactivate the extra X, just as female cells do. A similar thing happens in females. Sometimes females are born who have three X chromosomes in each cell. When this happens, the cells shut down two X chromosomes instead of one. The flip side of this is when females are born who only have one X chromosome. In this case, the cell doesn’t shut it off at all.     Every daughter cell that subsequently develops switches off the same X chromosome as its parental cell

She then talked about Rett syndrome and described it as something that 'presents in some ways as a really exteme form of autism'. So I guess she's trying to not be offensive to autistic people? Still feels a bit icky but better than nothing I suppose. She then mentions that we never really see boys with Rett syndrome - how did they get so lucky? Oh, because if a boy has it he dies in utero. Oops. I've read about that sort of thing a few times and it's so macabre.

An interesting story about X chromosome inactivation was a woman who had Duchenne muscular dystrophy even though only one parent was a carrier and the woman's identical twin was unaffected; she had just gotten incredibly unlucky with the stochastic process of X inactivation, as by chance all the cells that would go on to give rise to muscle cells had turned off the good X chromosome. 

I really liked the part about pseudoautosomal regions. You'd think that a woman with trisomy X (XXX) or Turner syndrome (X0) would be phenotypically identical because in trisomy two Xs will be inactivated and in Turner the single X just won't be inactivated, but you don't see that (though to be fair there aren't huge phenotypic differences, mainly height differences). At the ends of the sex chromosomes are the 'pseudoautosomal regions', where the X and Y chromosomes have alleles and can recombine. These regions escape X inactivation and so an XX woman has four (one on each end of each sex chromosome), as does an XY man, whereas an XXX woman or XXY man would have six, and an X0 woman would have two. These regions make a big contribution to height as they contain the SHOX gene (short stature homeobox), and so we see height differences with these syndromes. Super interesting.

Another interesting sex-related (in the genetic sense) thing was imprinting. For certain genes, their expression patterns depend on whether the gene was inherited paternally or maternally, and it can be related to the evolutionary battle of the sexes, where the male wants his offspring to grow up strong, but the mother has to balance strong offspring with being able to survive to gestate another child later (whereas the father can just go do it with someone else and doesn't care if the mother survives intact). So for example genes from the father might encourage a big placenta to give lots of nutrients to the baby, whereas from the mother it might do the opposite.

Genetic analyses of the abnormal placenta have been very informative. They show that in most cases, hydatidiform moles arise when an egg that for some reason has no nucleus is penetrated by a sperm. The 23 chromosomes in the sperm are copied, to create the normal human chromosome number of 46. In about a fifth of cases the mole is formed when two sperm penetrate one of the unusual nucleus-free eggs simultaneously, again generating the correct number of chromosomes. Just like the mouse experiments, the hydatidiform mole contains the correct number of chromosomes but they derive just from one parent, and this again leads to a severe failure in developmental pathways.

...

During development, the relevant paternal genes often drive expression of a large, efficient placenta, as this is the organ that nourishes the embryos. That’s why in the hydatidiform moles, where all the genetic material is from the father, there is an abnormal and very large placenta 

I have to commend the author on her use of caveats rather than just uncritically reporting things, which is a trap popular science can sometimes fall into; she did use plenty of caveats, saying for example about telomeres: 

The data are rather preliminary and not always consistent. This is partly because measuring telomeres in a consistent way is challenging, as described earlier, and we usually measure them in cells that we can access easily. These are typically the white blood cells, and they may not always be the most relevant cell type to examine

There was also some discussion about the practice of science, which was interesting. n the subject of the big international ENCODE project, which found that 80% of the genome appears to actually be functional (with caveats that they just found places that look functional but might not be, and used methods that could've just picked up random noise):

ENCODE was an example of Big Science. These are typically huge collaborations costing millions and millions of dollars. The science budget is not infinite and when funds are used for these Big Science initiatives, there is less money to go around for the smaller, more hypothesis-driven research. Funding agencies work hard to get the balance right between the two types of research. In many cases, Big Science is funded if it generates a resource that will stimulate a great deal of other science. The original sequencing of the human genome would be a clear example of this, although we should recognise that even that was not without its critics. But with ENCODE the controversy is not around the raw data that were generated, it’s about how those data are interpreted. That makes it different from a pure infrastructure investment in the eyes of the critics.
.... The rush to create categories and nomenclature has been, and continues to be, a real problem in the whole field of genome analysis because it tends to lock us in to definitions before we really have enough biological understanding to create relevant categories. [on types of non-coding RNAs]

Unfortunately I was pretty bored while reading this book - even though it had lots of interesting information, overall it was quite dry, and very dense in parts. It did have some great quips though:

The protein is called Sonic Hedgehog, symbol SHH. Researchers went through a phase of giving genes apparently comic names. This is now discouraged as it’s suddenly not so amusing if a genetic counsellor has to pass on a whimsical gene name to the parents of a child with a severe genetic condition.
...

They work in complex partnerships and the impact that they have on the final splicing pattern is affected by other things happening in the cell, such as the precise complement of proteins in the spliceosome. The descriptions that are used for these modifying sequences usually include such words as ‘dizzying’ or ‘bewildering’. These are geek speak for ‘unbelievably complicated, way beyond anything we can get our heads around or even design predictive computer algorithms for at the moment.

...

From an evolutionary perspective, it doesn’t really matter if this means that when we are older we can’t repair our hearts. This is a problem for humans because we like living longer than evolution deems strictly necessary.
 
...

One of the first Bible stories learnt by children raised in the Judaeo-Christian faiths is the creation tale from Genesis. In this story, God creates the earth and the heavens and all that is in them, and finally he creates Adam and Eve. After that, peopling the earth is down to those two and their descendants, with no further divine intervention apart from the obvious exception in the Christian tradition at the start of the New Testament.

I was pleasantly surprised by the science content; as well as interesting facts, I learned stuff about biological processes that I hadn't learned in college, like how polyadenylation of an mRNA works. There was also this bit, about how that can contribute to different expression levels of a protein with no change to the protein itself, that I thought was really interesting:

This is a sequence of six bases (AAUAAA) within the junk of the untranslated region. It acts as a signal for a messenger RNA-processing enzyme. The enzyme recognises the six-base motif, and cuts the messenger RNA a little distance away, usually ten to 30 bases further downstream. Once the messenger RNA has been cut in this way, another enzyme can add the multiple A bases. This six-base motif often occurs many times in the same untranslated region. It’s not particularly clear how a cell ‘chooses’ which motif to use at any one time. It is probably influenced by other factors in the cell. But because there are multiple motifs that can be used, there may be multiple messenger RNAs that code for exactly the same protein, but which contain different lengths of the untranslated region before the multiple As. These different-length messenger RNAs will have different stabilities and so produce different amounts of protein from each other. This creates additional opportunity for fine-tuning the amount of protein that is produced.

The therapeutics section was really interesting. One idea: many drugs target proteins or enzymes and inhibit them by nestling into a cranny on their surface - but what do you do if the protein is flat and there's nowhere for an inhibitor to lodge? Target the protein while it's still an mRNA, using miRNAs which will target it and cause it to be degraded.

(One gripe: she referred to them as 'smallRNAs' the whole way through the chapter instead of just saying miRNAs and siRNAs. I don't think the more accurate form is that much harder to understand and it was super annoying to see 'smallRNAs' all the time.)

I had never thought of the drugs-go-to-the-liver thing before even during my Metabolism study where I literally cried because the liver does so much work and is underappreciated:

One of the biggest problems that companies have faced in the past when trying to develop drugs around nucleic acids has been the body’s own detoxification abilities. This is also often a problem for traditional drug discovery as well. Essentially, when a new chemical of any type enters the body, there is a very high likelihood that it will go to the liver. One of the main jobs of this vastly energetic organ is to detoxify anything it doesn’t like the look of. For all of our evolutionary history, this has served us well, protecting us from toxins in food. But the problem is that the liver has no means of distinguishing between toxins we want to avoid, and drugs we are trying to use. It will just drag them in, and try to destroy them. To use an old rubric, Alnylam and Mirna are making a virtue from a necessity. Alnylam is targeting expression of a protein that is produced in the liver. Mirna is trying to develop treatments for liver cancer. Their molecules will be taken up by exactly the organ they want them to reach. The companies have adapted the structure or packaging of their molecules to try to ensure that once they are in the liver, they will survive long enough in the cells to do their job. SmallRNA approaches have been put forward for a number of other conditions, and the preliminary cellular and animal experiments often look good. But for a condition such as amyotrophic lateral sclerosis, where the nucleic acids will have to avoid the liver and be taken up by the brain, it’s not clear yet how successful the industry will be in capitalising on this technology

An interesting example of how outside factors can influence drug development:

In 1998 an antisense drug was licensed for use in immunocompromised patients who had developed a viral infection in the retina that threatened their sight. The antisense molecule bound to a viral gene, and prevented the virus from reproducing. It was an effective drug, which raises two questions. Why did this drug work so well? And given that it worked so well, why did the manufacturer stop selling it in 2004? Both answers are quite straightforward. The drug worked well because it was injected straight into the eye. There was never a problem about it being scooped up by the liver, because it didn’t go via the liver. It was also targeting a virus, and only in one selfcontained part of the body, so there wasn’t much risk of widespread interference with human genes. All of which sounds peachy, so why did the manufacturer stop selling it in 2004? This drug was developed for severely immunocompromised patients, of whom the vast majority were people suffering from AIDS. By 2004, there were drugs available that were pretty good at keeping HIV, the causative virus, under control. The patients’ immune systems were in much better shape, and they simply weren’t succumbing to viral infections in the retina anymore.

On a more personal note, this from the telomeres section was upsetting to read as someone with anxiety. C'mon guys, now I'm stressed about the effect my stress is having on my health! You're literally killing me! It's worse than smoking and obesity!

Chronic psychological stress can be very harmful for an individual, with negative impacts on multiple systems including their cardiovascular health and their immune responses. 34 Individuals who suffer chronic psychological stress tend to die younger than less stressed individuals. A study of women aged between 20 and 50 showed that those in the chronically stressed group had shorter telomeres than the unstressed women. This was calculated to equate to about ten years of life.
It was interesting that long non-coding RNAs appear to be involved in maintaining pluripotency in embryonic stem cells; knocking down these lncRNAs induces the ES cells to start differentiating, and inducing them to start differentiating decreases the amount of lncRNAs present. The 'development can be thought of as the opposite of cancer' concept was really interesting.

There were lots of other things, like how the myotonic dystrophy mutation is related to junk DNA (the longer the repeat gets, the more it can sponge up things that should be off regulating other things). I'd recommend it if you like biology, except maybe the epigenetics bits.

Wednesday 20 June 2018

Review: Lost in Math by Sabine Hossenfelder

This is an interesting book by a theoretical physicist about how the field has gone astray by relying on subjective aesthetic criteria to judge theories in the absence of evidence. It was a weird reading experience as usually my popsci books are more of a survey of a broad area e.g. The Gene by Siddhartha Mukherjee, I Contain Multitudes by Ed Yong, whereas this one was pretty much entirely about a problem faced by theoretical physics, but it was quite good. I'd recommend it for people interesting in the scientific method  and problems facing it because that's really what it's about; don't go in expecting to learn physics. 



(I apologise in advance: this review doesn't have much of a structure as I mostly just want to record interesting bits.)

4 stars: the approach to explaining the actual physics was poor, but that wasn't the main point of the book and the main point - about how big an issue this is - was good. She's also funny.

Thesis: Theoretical physics (TP) is lost in maths; they use the aesthetic beauty of mathematical theories (in terms of simplicity, elegance, naturalness - not needing to fine-tune things and having all your unitless numbers near 1, and explanatory closure - unexpected insights) to assess theories without experimental evidence because they're so starved for evidence.

Strong points:


  • introduced me to a problem that I didn't really know much about (though I did tease theoretical physics people for their fear of evidence) and convinced me that it's a serious issue
  • funny way of writing and lots of pithy lines
    • "What the heck is an internal space?" you ask. Good question. The best answer I have is "useful".
    • On searching for dark matter particles: experimentalists working with a detector originally developed to catch neutrinos reported in 1986 on the first "interesting bounds on galactic cold dark matter and on light bosons emitted from the sun." In plain English, "interesting bounds" means they didn't find anything. Various other neutrino experiments at the time also found interesting bounds.
  • seemed to have access to lots of big names in the field
  • Her list of suggestions in the appendix seemed very good and original (at least to me)
  • I respect her for coming out and saying this stuff. I was expecting a lot of opposition (in fairness it's only out this month) but I haven't actually found much criticism online...but still. Hopefully it leads to some change in how funding is applied for and given out in foundational physics.


Weak points:


  • It's not clear who she's writing for - it's ostensibly for the public going by the book format, but it seems like it's actually for scientists in her field and the public was added as an afterthought. She didn't explain theoretical physics concepts well - and that's understandable, since I'm sure it takes a huge amount of difficult maths - but then she acted as if she had, where she'd give an explanation that was technically there but really didn't explain things, and then just refer to it by name. Some things that happened with that: U(1), SU(5), fine-tuning, gauge coupling, group. I appreciated the Kirkus review saying 'Even educated readers will struggle to understand the elements of modern physics'. 

Many of the people she spoke of seemed to be to some degree aware of but ignoring the problem, which is weird. Surely that's a lot of cognitive dissonance.


I'm really enjoying how much my mind is stretching over the last while, what with Schols and books like this and the research I'm doing in Genetics at the moment. It's difficult but very rewarding.

She seems to be a very incisive and snarky interviewer, which must make her fairly unpopular with her interviewees. She'll record someone saying something and then be like 'Isn't that exactly what you do?' but maybe only in the text of the book rather than immediately in the interview. That said there were perhaps a bit too many interviews - there just seemed to be an awful lot of them and it wasn't great for the book's structure. 

Cool Quotes

To derive a probability for a theory rather than a constraint, you need a probability distribution, which then needs a metatheory that tells you how probable each theory is. The attempt to get rid of human choice just moves the choice elsewhere

In our search for new ideas, beauty plays many roles. It's a guide, a reward, a motivation. It's also a systematic bias. Ooooh.

Supersymmetry is the largest possible symmetry that can be accommodated in the existing theories - and how could nature not make use of such a beautiful idea? 


Scales

One prominent TP said that historically as you go down the scales, things have always gotten simpler. Chemistry has all these weird molecules, then you classify them into the elements, then you get simpler and simpler with atoms and quarks etc. But Hossenfelder points out that this is because he conveniently started with chemistry instead of, say, galaxies, which get more complicated as you go down the scale because you hit biochemistry (my love). Also, Garrett says the idea of the laws of nature being fundamentally ugly is 'abhorrent' to him. I mean, so what? It's not his business to think they're pretty or not, scientists are supposed to find out the truth whatever it is.

Astronomers

According to this TP she interviewed called Weinberg, Copernicus came up with heliocentrism not because of evidence but because he thought that was more attractive than the Ptolemaic system, and that Newton was able to revolutionise force with his theory of gravity because he didn't find force acting at a distance ugly whereas Descartes did.

Apparently Kepler originally thought the orbits were in Ptolemaic geometrical solids. Also, an issue with people supporting heliocentrism was that until the ninteenth century astronomers couldn't detect the parallax of the stars and so either the Earth had to be stationary during the year or the planets would have to be very far away, much further than the Sun and other planets in the solar system, and this introduced an unacceptably large number.

When Kepler said that the planets moved in elliptical, rather than circular, orbits, his idea was met with opposition from people who said it was absurd because that's not what a perfect creator would have done, and it was too ugly. He was told to just add epicycles, smaller circles to fix the ellipses so they could be circles. Coz circles are pretty.

Tidbit: in a 1916 book called Harmony of the World, Kepler derived the tunes of the planet and said that Earth sings Mi-Fa-Mi. Which is yknow, odd.

Talking about the parrotfish shaping landscapes with its feces and unsubtly alluding to the state of TP: 'if you pile up enough of it, even shit can look beautiful.'

Imagine a website where you can order door signs with numbers: 1, 2, 3, 4,.  and so on, all the way up to infinity. Then you can also order an emu, an empty bottle, and the Eiffel Tower. That's how awkwardly the exceptional Lie groups sit beside the orderly infinite families

Apparently Enrico Fermi replied to a question on what he thought about the discovery of a particle called K02 with 'Young man, if I could remember the names of these particles I would have been a botanist.' Seems too polished to be true but anyway. [Side note: wooot with my recent exam results I know I won't have to do botany!]

The Multiverse

Cosmologist Martin Rees bet his dog that the multiverse is right, Andrei Linde bet his life, and Steven Weinberg had "just enough confidence about the multiverse to bet the lives of both Andrei Linde and Martin Rees's dog."

The multiverse is presented as an alternative to having to come up with parameters for theories - if you can't find a parameter that's natural i.e. close to one, and you don't find it aesthetically pleasing to just pick a parameter that works, you can avoid having to choose one at all by positing a multiverse where there's a universe with each possible parameter. Newton, for example, could have refused to just measure the gravitational constant and instead argued that there must be a universe for each possible value...You can create a multiverse for every theory -- all you have to do is drop a sufficient amount of assumptions or ties to observation. 

The idea of 'fine-tuning', and TPs hating it, is central to the book; apparently TPs hate very large or very small numbers because then the numbers aren't 'natural' and need an explanation. 

There's also a more radical 'mathematical multiverse' which is like the mother of all multiverses: any theory that describes our universe relies on the selection of some mathematics to describe it, and you can't justify that maths because it would require other maths (apparently, since TPs love maths), so the only logical final theory is one in which all maths exists. Gosh this book got awfully philosophical.

Quantum Mechanics: Interpretations

Quantum mechanics refers to observations mattering -- so telescopes and brains matter; it assumes the existence of macroscopic objects. This is bad for reductionism. 

Learned a bit about the conflict between general relativity and quantum theory, which I knew nothing about before: general relativity is not a quantum theory, but it has to react to matter and radiation, which have quantum properties. If an electron is in two places at once, which one should spacetime curve around? Its curvature can't be in two places at once.

According to the Copenhagen interpretation, quantum mechanics is a black box: we enter an experimental setup and push the math button, and out comes a probability. What a particle did before it was measured is a question you're not supposed to ask. In other words, "shut up and calculate". This is something that really bothered me about my quantum mechanics lectures last year; there was no interpretation at all, just derivations.

I do kinda like the sound of QBism (with the caveat that I know very little really about the maths of quantum mech) - it says that the wave function is a device to collect an observer's information about the real world, which is updated when the person makes a measurement.

An interesting and bizarre interpretation is the 'many-worlds' or 'many-histories' version, which says that instead of the wave function ever collapsing, it actually branches into parallel universes, one for each measurement outcome. 

Someone she interviews describes a friend of theirs describing a graduate student (phew) whose career essentially disintegrated, and I asked what went wrong and he said "He tried to understand quantum mechanics'. He could have had a perfectly good career without it. But getting into the fundamentals of quantum mechanics is a losing game. She also pre-empted me by saying: If you quote this, you can be the first person to quote someone quoting someone quoting himself quoting someone.

There followed an interesting description of how, while aesthetics are a bad metric to use for judging theories, consistency is a good one - the standard model without the Higgs boson becomes internally inconsistent at LHC energies. 

No proof is ever better than its assumptions

Bullshit

"Yes, there was this story that the LHC should find supersymmetry," I say. "Gordy Kane still thinks gluinos have to show up in run two."

"Ack," Garrett says. "The most egregious thing was his claim of predicting the mass of the Higgs, after all the rumors were already flying. And two days before the official announcement, he put out this paper. And then the announcement confirms the rumors and he calls it a prediction from string theory!"

Mathematical consistency can't be the only requirement for a theory; there are tons of theories that are mathematically consistent but don't have any relation to reality.

For it hardwired in my brain, it ought to have been beneficial during natural selection. Not sure this is true - could've just got there by drift or by common descent I imagine.

Supersymmetry: 

The idea of supersymmetry (though this wasn't really made clear in the book, just the partners bit) is a relationship between fermions and bosons that means every particle in one group has a 'superpartner' from the other group, with spins differing by a half-integer (thanks Wikipedia). Supersymmetry is called 'susy' for short, and people are very attached to it.
When I was a student, in the late 1990s, the simplest susy [supersymmetry] models had already run into conflict with data and the process of designing more complicated but still viable models had begun. To me it looked like a field where nothing new could be said without first detecting the predicted particles [superpartners]. I decided to stay away from susy until that happened. It hasn't happened. Not in the LEP which ran until 2000, not at the Tevatron which reached higher energies and ran until 2011, and not at the still more powerful LHC.

Apparently TP is a very mature field, and thus has very strong constraints already from old experiments, which rule out almost everything you can try (according to Nima). He seems to imply that this means you don't need to check things with new experiments. It's an odd concept - can biology just find out enough things and then extrapolate from there forever?

She talks about how weird it is that TPs don't like assumptions that "are selected 'merely' to explain observations, since there are already so many of those that just don't get talked about, like the stability of the vacuum, which could occur in many theories that don't match the world but is included because it does happen to match the world.

I thought the description of how scientists testing SU(5) unification by just getting a big vat of water and waiting for one of its protons to decay was cool, because at least they were actually looking to experiment.

Some bullshitty sounding supersymmetry (very aware that I don't understand the maths): It didn't take long until it was noted that, even if broken at high energy, supersymmetry would lead to disagreement with exxperiment by enabling interactions that are forbidden in the standard model, interactions that hadn't been seen. And so was invented R-parity, a symmetry that, when combined with supersymmetry, simply forbids the unobserved interactions because they would conflict with the new symmetry postulate.

She gave a nice understandable description of symmetry with something like: you could say something is blue in the west, and east, and north, and south, and northwest, etc, or you could just say it's blue everywhere (rotational symmetry). 


String theorists had for a long time used a cosmological constant that was negative; when it was found to be positive they had to quickly adjust things. String theorists appear to have abandoned the idea that their idea would uniquely determine the laws of nature and instead embraced the multiverse, in which all the possible laws of nature are real somewhere. They are now trying to construct a probability distribution for the multiverse according to which our universe would at least be likely.
...String theorists' continuous adaptation to conflicting evidence has become so entertaining that many departments of physics keep a few string theorists around because the public likes to hear about their heroic attempts to explain everything. Also, they're apparently a cheap way to get a physics department since no experiments.

I did have a few 'people get paid for this?' moments, I will admit.

Ars Technica's review has a good description of the issue with supersymmetry: 'Supersymmetry was attractive because it was natural and beautiful. Unfortunately, results from the Large Hadron Collider have eliminated natural versions of supersymmetry. If it turns out that the world is supersymmetric, the theory will not be natural; it will be fine tuned, with some unusual numbers that are just baked in.'

Two sides of string theory

Good: string theory fits naturally with supersymmetry (unsure whether this is really good); there are thought to be an infinite number of string theories that are collected together in M-theory; their theory was able to predict the thermodynamics of black holes and matched the already known laws; invented some interesting maths; gauge-gravity duality; apparently showed that our universe can in theory be squeezed into 2D? Not sure what that means.


Bad: no evidence and no testable hypotheses thus kinda raising doubts about whether it's science at all


The Energy Desert

The energy desert is the 12 orders of magnitude between the LHC energies (around a thousand GeV) and the energies of grand unification and the Planck scale (10^15 GeV). This would be a pretty impossibly enormous undertaking to develop experimental equipment to bridge, but they do need experimental evidence soon.

When some scientist she interviewed discovered something that involved the multiverse, he had to go to a psychiatrist for it he was so upset.


There was a bit about how physicists can't actually solve the equations of the Standard Model so they use perturbation theory and just hope the refinements, the adjustments to the bumps of things off each other, will keep getting smaller. But they don't, and it's an issue that fundamentally physicists don't understand the theory. 

Foundational physics is the canary in the coalmine when it comes to non-empiricial theory assessment, or figuring out which ideas are worth pursuing, because its ideas are the hardest to test -- but Hossenfelder says this will affect other fields too. Theories are cheap and plentiful but experiments are expensive and few. 

Dark matter

The second rule for inventing a new particle is that you need an argument for why it's just about to be discovered, because otherwise nobody will care. This doesn't have to be a good argument - everyone in the business wants to believe you anyway - but you have to give your audience an explanation they can repeat. The common way to do this is to look for numerical coincidences and then claim they hint at new physics for a planned experiment, using phrases like 'natural explanation' or 'suggestive link'. She says the WIMP miracle (weakly-interacting massive particles), in which a calculation based on the WIMPs' mass and interaction rate gives roughly the right amount of dark matter in the early universe, is an example.

Hossenfelder mentions a large number of experimental setups - I counted 25 - that found "interesting bounds" on dark matter -- and the parameter range in which the WIMP miracle holds has meanwhile been excluded

Economics

Hossenfelder briefly turns her attention to other areas of research, particularly economics. Apparently in economics, to get into a good journal your theory has to be selfish agents maximising their preferences, and that getting one paper in one of the five top journals is enough to get you tenure at a good university. The guy she's talking to, Doyne, says it's even worse than string theory because at least string theory is making interesting contributions to mathematics, but econ is just using standard maths and even then it's not empirical. So what is it? I'm sure econ has some good things, but if it's not empirical what is the actual point of it? Do we just keep it around because we find money intrinsically interesting?

Biases

Where experimentalists go to great lengths to account for statistical biases, theoreticians proceed entirely undisturbed, happily believing it is possible to intuit the correct laws of nature. 

On the sunk cost fallacy: The more time and effort you've spent on supersymmetry, the less likely you are to call it quits, even though the odds look worse and worse. We keep on doing what we've been doing long after it's stopped being promising, because we already invested in it, and we don't like to admit we might have been wrong. It's why Planck quipped, "Science advances one funeral at a time."

On the broken process of science funding

Scientists seem to exaggerate in grant applications, especially about the future impact of their work, because they have to get funded. We have failed to protect our ability to make unbiased judgments. We let ourselves be pushed into a corner, and now we are routinely forced to lie if we want to continue our work.

Three lessons

1. If you want to solve a problem with math, first make sure it really is a problem.
2. State your assumptions. (These assumptions include naturalness and simplicity - simplicity doesn't necessarily increase as you go down scales, as in the biochemistry example). 
3. Observational guidance is necessary. Because even with good problems and clearly stated assumptions, there can still be many mathematically possible solutions. 

Flashes in the Pan

Near the end of the book, she writes a quick but depressing timeline. The diphoton anomaly, something that theorists hoped pointed to new physics at the LHC, disappeared with new data. The LUX dart matter experiment found no WIMPs. No sign of supersymmetry was found at the LHC. No axions have been found. How long is too long to wait for a theory to be backed up by evidence? ... whether or not we will find something, it is already clear that the old rules for theory development have run their course. Five hundred theories to explain a signal that wasn't and 193 models for the early universe are more than enough evidence that current quality standards are no longer useful to assess our theories. 

Suggestions for Improvement 

Here are some of my favourite of her suggestions: 


  • Be careful with peer reviewers (of research papers): of a reviewer's continued funding depends on the well-being of a certain research area, that person has a conflict of interest and should not review papers in that area.
  • Make commitments: not all science can be done by post-docs on two-year fellowships. Tenure is important. She argues that tenure should be given to a higher proportion of scientists, even if that means fewer scientists in general. I'm not sure if I agree here; tenure would be great but y'know so would being able to get into the field.
  • Encourage a change of field: Scientists have a natural tendency to stick to what they already know. If the promise of a research area declines, they need a way to get out; otherwise you'll end up investing money in dying fields. Therefore, offer reeducation support, one- to two-year grants that allow scientists to learn the basics of a new field and to establish contacts. During that period they should not be expected to produce papers or give conference talks.
  • Hire full-time reviewers, scientists who specialise in providing objective reviews in certain fields. These reviewers should not themselves work in the field and should have no personal incentive to take sides. This one is interesting because (I imagine) there's a tradeoff between objectivity and knowledge of the field, so if you're not working in the subfield you can review it more objectively but you might not actually understand the paper as well because you're not following all the advances as closely. Maybe.
  • Support publication of criticism of others' work and negative results - criticism doesn't feel nice but is essential for the scientific method. 


So what to do about the physics in general? Now, I'm not sure it's legitimate for me to agree with Hossenfelder's criticisms when I don't actually understand the maths of TP at all, but it definitely seems like the current approach of making bigger and bigger detectors trying to find the same things isn't working, and maybe scientists should step back from that area until they make progress in related fields and can come up with better ways to test these things? I don't know, but something has to give.