Category Archives: Links

An unusual mathematician’s biography…or not

“For the first 27 years of his life, the mathematician Ken Ono was a screw-up, a disappointment and a failure. At least, that’s how he saw himself. The youngest son of first-generation Japanese immigrants to the United States, Ono grew up under relentless pressure to achieve academically. His parents set an unusually high bar. Ono’s father, an eminent mathematician who accepted an invitation from J. Robert Oppenheimer to join the Institute for Advanced Study in Princeton, N.J., expected his son to follow in his footsteps. Ono’s mother, meanwhile, was a quintessential “tiger parent,” discouraging any interests unrelated to the steady accumulation of scholarly credentials.

[…]”

https://www.quantamagazine.org/20160519-ken-ono-mathematician-inspired-by-ramanujan/

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The mathematicians of Surathkal

http://thewire.in/62631/women-in-mathematics-surathkal/

all emphases mine

Family influence and/or patriarchal power over their children’s education and career paths and aspirations:

“Sabari […] wanted to study medicine. “My grandmother and several others at home, practise home medicine.””

““At teen ages, we do whatever parents tell us to,” she said candidly. “They said take science in 11th and 12th standards so I did.”

“Manasa was lucky because her father was the math teacher. Only one other student at her old school continued to 11th standard.”

“If they [students] join a B.Sc. in maths because they were forced to, then they will soon know the reality, that what they were taught till then is not enough.”

Parental power sustains and reproduces unequal gender roles

Parents don’t want to send their daughters out of the state. I’m in NIT-Surathkal because I come from Karnataka itself. There are constraints.”

“In a society like ours, doing a PhD. is not always encouraged, especially for women as there is an opinion among families that the man must be more qualified. The women agree that they have heard people say things like “who will search for a boy now (now that she’s a PhD.)”.

Managing the dual face of patriarchal power through humour. Family poses both an “enablement” and “constraints” (Sen); parents exercise their freedom to translate their own experiences into shaping your children’s future (“he wasn’t able to finish 10th standard”). Feeling “grateful” and “lucky” for being allowed to flourish against the odds of one’s birth gender!

“Manasa B. counts herself lucky to have a father who is very particular that all his three children be well educated. “He wasn’t able to finish his 10th standard and he was determined that we do.” While she’s grateful for that, she knows that marriage will eventually come into the picture. “They’ve told us that in between studies if we ask you to get married, you can’t say things like ‘no, only after I finish’.” In her case, Manasa joked that she is off the hook until her elder sister gets married.”

Defying family:

“Sabari says that she had to fight a lot before she was allowed to come to NITK for her PhD.“Right before I joined here, one prospective groom came asking for marriage. My parents asked me to stay back and get married. I said, no I will go to Surathkal. If he agrees to let me, then good.”However, he didn’t, and Sabari proceeded with her plans.”

Willpower – but curbed by “adaptive preferences” (Sen):

“Manasa B. realised early on that she had a penchant for mathematics but her only ambition then was to become a teacher.”

Enablements and constraints, tradition:

The intersection of gender and class opens some future avenues and closes others. However this isn’t as black and white as the concept of “discrimination” may suggest: it is overt discrimination, but also internalised beliefs that lead people to put brakes on themselves and those others whom they love and over whom they have power (their children).

“Tenth standard is the highest education students were allowed to reach, especially girls. For the boys, it is better now but back then nobody sent their children out of the village to continue studies and there was no science college nearby.”

Where you go to school matters,” says Manasa. This becomes even more evident, she says, when they interact with their contemporaries from the IITs, IISERs – India’s top research institutes. “That’s when we realise how much we know and how our background and school education plays a role.”

Some constraints are self-restrictions: 

“Manasa said that the will to learn beyond what is considered ‘necessary’ is not something everyone has.”

“From basic education itself, students are hating mathematics a lot.”

“Conversion factors” (Sen) are initiatives, institutions, spaces, “arenas” that help level the playing field for people who have had different starts in life BUT these conversion factors can only ever begin to solve the problem:

“It always helps to collaborate with peers and arenas where they can do this are at government-funded training programmes for mathematicians – specifically the ATM schools (Advanced Training in Mathematics Schools) for teachers and Ph.D. students; and MTTS (Mathematics Training and Talent Search) for B.Sc. and M.Sc. students. […]“These really help. We learn a lot,” says Manasa. At these camps, though, women remain a minority. 

Locked in, or “having a family while female”. Family situation determines professional choices, identity, delineates freedoms. Babies are “not easy to manage” but they are also “our strength”. Female time itself is different: marriage serves even as an anchoring point in time.: “I started my Ph.D. in my sixth year of marriage” rather than “I got married right after I got my undergraduate degree”. To continue with other pursuits, such as a profession, or a passion, women have no other choice but to pass on care and household labour to other women, sometimes across generations (in other cases across nationalities). Unsurprisingly, very few women continue into marriage (in this micro-unrepresentative sample 1 in 5, but this is a very similar optimistic round-up of the actual overall proportion of women with children in science).

Only Kumudakshi is married among the five. She got married right after B.Sc. and has a baby now. “I started my PhD. in my sixth year of marriage. It’s not easy to manage with a baby but they are our strength.” She admits that she is able to do this because her mother lives with them. “Otherwise, managing this would have been a bit difficult. Someone should be there to take care of the house and things.

The generative and motivational belief in the dominance of personal willpower and tenaticy – but intertwined with a false consciousness

The hope? Willpower to discover and pursue your own grains of talents, develop personal tenacity:

“actually, I don’t think it’s true that students will do better in private schools. If they want to study, they will study anywhere.”

Yet, with the above statement – which I’m sure she sincerely believes, not least because I notice the same contradictory tendence in my own thinking and that of many people I’ve talked to –  the same mathematician actually contradicts her own experience when she compares her own educational journey to that of her colleague, the maths’ teacher daughter:

“had told me [the journalist] earlier that her experience studying at a government school was not as challenging as Manasa K.J.’s.”

 

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More about Grothendieck

Yet More About Grothendieck

(Reposted from the Not Even Wrong blog)

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The problem with technological ignorance, or Don’t take your smartphone for granted

“When we, as a society, fail to appreciate the staggering complexity of our modern technologies, we don’t just lose a sense of awe toward what is around us. We lose a sense of what we as humans can build, as well as where we might fall short. It is impressive that people can build and grapple with these astonishingly complex systems at all, something we seem to neglect when we focus on the shortcomings of a technology, rather than its successes and the effort that has gone into it. For example, autocorrect is mostly known for its failures, but in fact it’s an amazing technical feat that dramatically improves text entry speed.
But related to this is something else: Recognizing the overwhelming complexity of our technologies makes it easier to see that bugs and glitches are essentially an inevitability. When anything becomes as complicated as Dijkstra describes, unanticipated consequences will arise. Baked into a proper recognition of the phenomenal complexity around us must also then be a sense of humility—our limits in the face of the technologies we have built—something that we need to acknowledge more and more.”

From “The problem with technological ignorance”, http://www.slate.com/articles/technology/future_tense/2015/12/the_problem_with_technological_ignorance.html

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Semantic Scholar: the AI which, knows your field better than you (and a Short Rant to Science Policy-makers)

“What if a cure for an intractable cancer is hidden within the tedious reports on thousands of clinical studies? In 20 years’ time, AI will be able to read — and more importantly, understand — scientific text. These AI readers will be able to connect the dots between disparate studies to identify novel hypotheses and to suggest experiments which would otherwise be missed.

AI-based discovery engines will help find the answers to science’s thorniest problems.”

— Oren Etzioni

“Semantic Scholar” is a better idea than the REF. But wait, what do they have in common? Here’s what.  Semantic scholar looks through existing scholarship and lets you use it and build up on it. It may uncover an article which no one has read many years after it was published, and let a new researcher learn something. It helps cut through the bullshit – perhaps not in the best possible way, but AIs are work in progress and will surely evolve into cleverer versions. The REF, conversely, fosters the production of bullshit. Its existence scares scientists into producing more crap (sorry, dear colleagues) because that’s the way in which we, and our university departments, are assessed. We all know it’s a game, and some refuse to play it, but people in their early careers have more incentive to play along than to protest by producing fewer, better pieces of work – even though it actually is in our long-term interests, we are fooled by fear. And so we write, and publish, instead of thinking and publishing less, better stuff.

If I were a science policy-maker, I’d put my money on tools that facilitate tedious, or downright impossible, tasks such as sifting, navigating and organising existing knowledge and debates.  And I would leave scientists with a bit more freedom to actually think, be curious, produce ideas, hypotheses and sometimes even knowledge, and – very importantly – also to make mistakes in the process. Oh, and having access to jobs that last longer than a year or two before having to move continent with or without your significant other, or instead of deciding to have children, would help. But that’s another rant, perhaps for a future post entitled “If I were a science policy-maker”.

For more about Semantic Scholar, see: https://www.newscientist.com/article/dn28434-ai-tool-scours-all-the-science-on-the-web-to-find-new-knowledge/

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Conference: Association for the Philosophy of Mathematical Practice

There’s a very interesting conference in Paris right now. Such a pity I’m not there. In fact, this post only appears now, because I only just found out about it. Looking forward to reading the papers.

3rd Congress of the Association for the Philosophy of Mathematical Practice (APMP) Paris, Institut Henri Poincaré, 2-4 November 2015

Programme: http://conference-apmp.sciencesconf.org/?lang=en

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Male STEM scientists reluctant to see gender bias in science (new study)

New study by Ian M. HandleyElizabeth R. BrownCorinne A. Moss-Racusin and Jessi L. Smith:

“Ever-growing empirical evidence documents a gender bias against women and their research—and favoring men—in science, technology, engineering, and mathematics (STEM) fields. Our research examined how receptive the scientific and public communities are to experimental evidence demonstrating this gender bias, which may contribute to women’s underrepresentation within STEM. Results from our three experiments, using general-public and university faculty samples, demonstrated that men evaluate the quality of research unveiling this bias as less meritorious than do women. These findings may inform and fuel self-correction efforts within STEM to reduce gender bias, bolster objectivity and diversity in STEM workforces, and enhance discovery, education, and achievement.”

Read the full article here (free access): http://www.pnas.org/content/early/2015/10/06/1510649112.abstract

A mathematician’s nightmare: Lockhart’s lament

I might have posted this already, but here it is again for George! One of my favourite texts written by a mathematician about mathematics and the way in which it is (but ought not be) taught.

https://www.maa.org/external_archive/devlin/LockhartsLament.pdf

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