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Gender differences in chess

1/9/2012 – A new and very commendable women's live rating list of top players is being maintained by the Russian chess news portal ChessPro. Fired by this list we did a little additional research to find out how many female players there are in the top 100 and top 1000. What would you estimate? And what are the possible reasons for the superiority of males in certain intellectual activities? Latest research.
 

Gender differences in chess

It was a very nice Christmas present: the Russian news portal ChessPro has started to publish a Women's Live Ratings, similar to the one we know for 2700+ players called Live Chess Ratings. There only one female player is ever present, so we cannot track the strongest women players in the world on a day-to-day tournament-by-tournament basis. Now we can and are deeply gratified to see that ChessPro is updating it regularly. The following live list was calculated immediately after the World Women’s World Team Championship at the end of December.

1 Polgar, Judit 2710 2710.0
2 Hou, Yifan 2578 2604.6
3 Koneru, Humpy 2600 2588.5
4 Muzychuk, Anna 2562 2579.7
5 Lahno, Kateryna 2549 2559.3
6 Ju, Wenjun 2543 2551.9
7 Zhao, Xue 2541 2550.7
8 Kosintseva, Nadezhda 2546 2537.4
9 Dzagnidze, Nana 2516 2534.7
10 Stefanova, Antoaneta 2531 2522.9
11 Harika, Dronavalli 2512 2515.7
12 Kosintseva, Tatiana 2526 2513.0
13 Sebag, Marie 2512 2512.0
14 Zatonskih, Anna 2506 2511.1
15 Gunina, Valentina 2514 2510.2
16 Cmilyte, Viktorija 2503 2503.0
17 Chiburdanidze, Maia 2500 2500.0
18 Socko, Monika 2479 2495.3
19 Cramling, Pia 2495 2490.6
20 Galliamova, Alisa 2490 2490.0
21 Danielian, Elina 2497 2489.6
 
22 Khotenashvili, Bela 2497 2489.5
23 Muzychuk, Mariya 2460 2483.1
24 Ruan, Lufei 2483 2483.0
25 Atalik, Ekaterina 2481 2481.0
26 Paehtz, Elisabeth 2457 2471.3
27 Zhu, Chen 2471 2470.8
28 Krush, Irina 2476 2467.0
29 Xu, Yuhua 2472 2465.0
30 Skripchenko, Almira 2468 2460.2
31 Dembo, Yelena 2468 2460.0
32 Munguntuul, Batkhuyag 2459 2459.0
33 Mkrtchian, Lilit 2469 2458.2
34 Ushenina, Anna 2463 2458.0
35 Javakhishvili, Lela 2475 2454.4
36 Pogonina, Natalija 2451 2448.9
37 Kosteniuk, Alexandra 2439 2447.7
38 Tan, Zhongyi 2448 2446.4
39 Shen, Yang 2448 2446.4
40 Khurtsidze, Nino 2440 2443.5
41 Hoang Thanh Trang 2446 2439.0
42 Arakhamia-Grant, Ketevan 2443 2434.4

The above got us thinking: how many female players are there in the top levels of chess? In the top hundred the answer is one percent, and that 1% is named Judit Polgar. But how about the top thousand? Using the latest available FIDE rating list for all players we were able to extract exactly 22 female players, which works out to (whip out your calculators, boys and girls) 2.2%.

No.  Player
Title
W-Ti.
Nat
Rtng
born
1  Polgar, Judit
GM
 
HUN
2710
1976
2  Koneru, Humpy
GM
 WGM
IND
2600
1987
3  Hou, Yifan
GM
 WGM
CHN
2578
1994
4  Polgar, Zsuzsa
GM
 WIM
USA
2577
1969
5  Xie, Jun
GM
 WIM
CHN
2574
1970
6  Muzychuk, Anna
IM
 WGM
SLO
2562
1990
7  Lahno, Kateryna
GM
 WGM
UKR
2549
1989
8  Kosintseva, Nadezhda
GM
 WGM
RUS
2546
1985
9  Ju, Wenjun
 WGM
 WGM
CHN
2543
1991
10  Zhao, Xue
GM
 WGM
CHN
2541
1985
11  Stefanova, Antoaneta
GM
 
BUL
2531
1979
12  Kosintseva, Tatiana
GM
 WGM
RUS
2526
1986
13  Dzagnidze, Nana
GM
 WGM
GEO
2516
1987
14  Gunina, Valentina
 IM
 WGM
RUS
2514
1989
15  Harika, Dronavalli
 GM
 WGM
IND
2512
1991
16  Sebag, Marie
 GM
 WGM
FRA
2512
1986
17  Zatonskih, Anna
IM
 WGM
USA
2506
1978
18  Cmilyte, Viktorija
GM
 WGM
LTU
2503
1983
19  Chiburdanidze, Maia
GM
 WIM
GEO
2500
1961
20  Danielian, Elina
GM
 WGM
ARM
2497
1978
21  Khotenashvili, Bela
 IM
 WGM
GEO
2497
1988
22  Cramling, Pia
GM
 
SWE
2495
1963

Which forced us to continue thinking: why is this so, why on earth are there not many more? Of course we have heard many theories – and have a rare one of our own. And then we ran across the scientific study below, which investigates the gender difference in mathematical skill. When you read our summary please replace every mathematical reference with chess – you will find that it is quite illuminating.

Debunking Myths about Gender and Mathematics Performance

For a long time we have known that there is a gap in performance between boys and girls in mathematics skills. In a new study, Debunking Myths about Gender and Mathematics Performance, Jonathan Kane, a professor of mathematical and computer science at the University of Wisconsin, Whitewater, and Janet Mertz, a professor of oncology at the University of Wisconsin, Madison, examine this gender gap and test several popular explanations. Their cross-cultural analysis seems to rule out several causal candidates, including coeducational schools, low standards of living, and innate variability among boys.

The greater male variability hypothesis states that variability in intellectual abilities is intrinsically greater among males. If gender differences in means and variances are primarily a consequence of innate, biologically determined differences between the sexes, one would expect these differences to be similar among countries regardless of their culture and to remain fairly constant across time. Such a finding would suggest that little can be done to diminish these differences.

To this PZ Myers, a biologist and associate professor at the University of Minnesota, Morris, remarks on his very interesting (and immanent recommendable) blog Pharyngula:

The most common explanation I hear for the disparity, over and over again, is that it's an accurate reflection of ability: men do better at the higher ranks of science and math because they have better brains. And the most frequent rational for that is the greater male variability hypothesis: the bell curve of performance for women is better tuned to achieve a greater likelihood of median ability, while men are more erratic – they produce more damaged, faulty brains than do women, but at the same time, they produce more brilliant brains. The male population exhibits greater extremes.

This has never made any sense to me.

There are deleterious traits which men have at higher frequency than women: color blindness, for instance, or haemophilia. There is also a known higher incidence for objectively measurable mental defects in males vs. females, diagnosable at birth. But how does this lead one to conclude that the greater variability should lead to greater beneficial variability? There is never any specific explanation of a mechanism that would allow greater variability to promote greater intelligence in males. There is much flapping of hands over the greater male frequency of autism, reading disorders, juvenile delinquency, etc. (all true), and then a dangling "therefore…" leading to the conclusion that there must be compensatory intellectual benefits for men.

It is conceptually possible that the universe could have screwed over the females or the males of our species. We know, for instance, that human physiology carries specific mechanisms that increase male body size over that of women; you could imagine a species in which there was a similar coupling of hormones to brain growth, and in a science fiction world you could imagine a race with great gender disparities in intelligence. That doesn't seem to be our world, though, and it also wouldn't make sense to explain such a phenomenon by greater noisy variation.

You have to look at the data. And the data all seem to be saying that men and women who make it to the point of entering the academic world have roughly equal intellectual potential, and that the differences between them are shaped by sociocultural influences, not biology.

Back to the Debunking Myths study: "We have pretty clear data debunking the greater male variability hypothesis," Mertz says. The two researcher examined datasets 86 countries. If the greater male variability hypothesis, which posits that men have a greater range of intelligence than women, is true, then that variability would persist, consistently, across all 86 countries. Instead, "For any given country, you quite reproducibly measure the same variance ratio," Mertz says. But between countries the variance ratio changes. Persistent cultural factors, in other words, seem very important in setting variance ratios. "That was one thing that really shocked me," Mertz says.

Some scholars have speculated that coeducational schools put women at a disadvantage in learning math. But Mertz and Kane's research found that gender-segregated schools make no difference in improving math scores for girls or boys. By comparing test scores across cultures, they indict local social factors as the likely primary culprit. Gender gaps vary from place to place, showing that cultural factors swamp biological ones.

What, then, is the cause of the gender gap? Like the gap itself, the cause varies, the authors conclude. Mertz and Kane don't rule out the existence of very small biological difference. Women’s nature might include a tendency to prefer the more nurturing fields, such as nursing and teaching young children, to the more quantitative ones, such as mathematics, physics, and engineering. If so, it might not make sense to encourage and direct any but the unusual female toward studying and seeking employment in these latter fields. This viewpoint has led some folks to propose that it may be a waste of time and money to expend resources directed toward trying to increase participation of women in these mathematics-intensive fields.

The study suggests social factors are key, but figuring out which particular social factors make the most difference will require further study. "I think there's a whole societal issue to combat," says Deanna Haunsperger, chair of the department of mathematics at Carlton College in Northfield, Minnesota. "When girls are looking for a career, they're looking for a career where they can be helpful to society and make a difference. And there's just such a negative stereotype about math they don't see that as a viable option."

Data may show that girls can do math as well as boys, but the stereotype that girls aren't good at math persists and does persistent damage. Just being in a culture that believes boys are better suited to science and math than girls is enough to have a negative effect on women, as work by Joshua Aronson, associate professor of applied psychology at New York University, demonstrated. When Aronson administered a math test to "fabulously good" undergraduates in their third year of calculus – but prefaced it with a statement that the test had never shown a gender difference – women’s scores rocketed past men’s, suggesting that the women’s performance up to that point had been hampered by self-image and stereotype.

Because stereotypes tend to create self-fulfilling prophecies, it's reasonable to surmise that knocking down those stereotypes would improve girls' (and women's) performance. One way of doing that is to raise women's economic and social standing, letting girls see smart women in high places.

Dear readers, before you click open your emailer to give us your take on the subject we urge you to read the three articles mentioned above in full detail. There is much more than we have quoted in our summary.

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