Most of the
publications on the gender gap in math and science are in the fields of
psychology and education. The most important questions are about the existence
of the gap, what explains it, and whether the gap in early stages of education explains
the subsequent career paths of men and women.
Researchers use data of standardized test scores in math
and science.[i] The
methodology usually compares moments (mean, median, and variance). Benbow and Stanley (1980, 1983, and
1988), among many other papers, were the early studies to analyzing the gender
gaps in mathematical reasoning ability. They presented evidence that male and
female students performances in math and science are almost equal, on
average, and sometimes females were even better than males, however,
females are less likely to choose science and math careers.[ii]
Recent studies include The European Commission study (2009),
which analyzed TIMSS and PISA data sets to report small differences in average
performance, where males’ achievements in math are greater than females at
later school years, and are especially noticeable among students who attend the
same teaching programs and year groups. It reports very small differences in
science in favor of males. And, males are worse than females in reading.[iii]
For the United States, Hyde et al. (2008) report that
the gender gaps in math in the general population, grade 2 to 11, were trivial.
On average, they found no gender gaps in test scores of 7 million
students. They also found greater males’ variability, where ethnicity, i.e.,
whites versus Asian/Pacific Islanders, seems to matter. The causes remained
unexplained.[iv]
Andreescu et al. (2008) examined data from the Study
of Mathematically Precocious Youth (SMPY), Putnam Mathematical Competition, and
the International Mathematical Olympiad (IMO). They found that culture is not
an explanatory variable of the gender gap; and the gender gap in math is
smaller in societies with more gender equality in general.
The TIMSS’ report on gender differences (2007) finds a few
gender differences in average mathematics achievement at the 4th
and 8th grades. At the final year of secondary school, TIMSS report
that males in 18 out of 21 countries have significantly greater achievements in
mathematics. In science, gender gaps in achievement favoring males were present
in one-third of the countries even as early as the fourth grade. At the eighth
grade in science, the gender gap was even wider with males performing significantly
higher than females in nearly two-thirds of the countries.
There has been a lot of media interest in this subject
because it’s a sensational issue. When Lawrence Summers, Ex-president of
Harvard University, said that males are innately better than females in math
the news media was on fire. He resigned his position.
There is also a tendency to jump to policy. Many want to
spend more money on improving teacher’s ability, increasing teacher’s pay, reduce
poverty, build better equipped schools, etc. Everyone has an agenda and search for
evidence to support it.
From economic point of view, I do not think we have a
problem. Maybe this is why economists were relatively less active in this area
of research. It’s unclear how the ratio of male to female mathematicians (the
gender gap) or scientists affects the economy.
I tested the gender gap using the TIMSS data. The data are from
the study cycles 1995, 1999, 2003 and 2007 for 1,426,402 students drawn from 44090 schools representing tens of countries from all over the
world. However, my test is more than testing whether the means (averages) are
equal, but rather tests whether every observation in the distribution is equal.[1] Without
going into the technical details, the results are summarized as follows. These
are two matrices showing the 4th grade and 8th grade math
and science test scores. They report the percentages of countries in the total
sample, where the distribution of the scores of boys dominates; whether
the girl’s dominates; and where is gender equality (zero-gap). They also report
the same results for the top tail of the distribution (the top 10 percent). I
kept the name of the countries in the case of gender equality because they are
interesting. Boys dominate.
Gender equality is intriguing and more challenging to
explain than the gender gap because equality means no gap, or no
variation in the data. We simply cannot explain no-variability using
conventional econometric techniques.
The only information available in TIMSS that could be used
to shed light on the results of gender equality is about the type of school –
the single-sex schools – or the segregated schools. This has been identified in
the literature as a cultural issue and that it might explain why boys and girls
do equally well in these countries. I repeated the test to test whether school
segregation explains the gender equality. The test cannot reject the null hypothesis that
segregated schools distributions is equal to all non-segregated schools
distributions, except in a few cases, where females clearly dominate. In math
and science, Iran’s segregated schools at the 4th grade dominate. In
science, El Salvador, Singapore and Dubai segregated schools dominate.
Segregation explains only two of our original results for gender equality and
females’ dominance (Singapore and Iran. In the 8th grade case, the
test provides a little more support and explain why some countries have
females’ distributions dominate, but the results do not explain that for every
case where there are no gender differences or females’ domination. One wonders about
the cultural common denominator between Iran, El Salvador and Singapore. I see
none. Further, many of the countries, which have gender equality in math and
science, do not have gender equality in general.
Jonathan Kane, one of the authors of the paper cited above, has
been reported saying that “girls living in some Middle Eastern countries, such
as Bahrain and Oman, had in fact, not scored very well, but their boys had
scored even worse, a result found to be unrelated to either Muslim culture or
schooling in single-gender classrooms.”
New Zealand is one of the OECD countries in addition to
Canada and Sweden among all other non-OECD, Russia, and Islamic and Arabic
countries, where there is gender equality. So we have no gender gap issue in
New Zealand to waste our time with. Boys and girls are equally good or bad in
math and science. I do not know whether this is a bad or a good outcome, but
surely it could be good news for those who care about equality. However, if
Kane is right then there should no reason to celebrate the gender equality result
I found.
Summary of the results
Matrix I- The 4th Grade,
TIMSS, 1995, 2003, and 2007
|
|
Math
|
Science
|
||
|
|
Full sample
|
Top 10%
|
Full sample
|
Top 10%
|
|
Males
Dominate
|
56%
|
66%
|
53%
|
74%
|
|
Females
Dominate
|
12%
|
11%
|
14%
|
2%
|
|
Equal
|
1.
Greece; 2. Ireland; 3. New Zealand; 4.Algeria; 5. Kuwait; 6. Qatar; 7.Yemen;
8. Dubai; 9. Iran; 10. Georgia; 11. Latvia; 12. Russia; 13. Ukraine; 14.
Chinese Taipei; 15. Singapore; 16. Mongolia
32%)
|
1.
Greece; 2. Ireland; 3. Algeria; 4. Tunisia; 5. Moldova; 6. Georgia; 7.
Russia; 8. Ukraine; 9. Kazakhstan; 10. Philippines; 11.Thailand; 12. Mongolia
(22%)
|
Canada
(BC); 2. Israel; 3. New Zealand; 4. Sweden; 5. U.K.; 6. Algeria; 7. Kuwait 8.
Morocco; 9. Qatar; 10. Yemen; 11. Dubai; 12. Iran; 13. Latvia; 14.Lithuania;
15. Russia; 16. Ukraine; 17.Kazakhstan
(33%)
|
1.
Norway; 2. Sweden; 3. Algeria4. Morocco; 5.Tunisia; 6. Dubai; 7. Moldova; 8.
Georgia; 9. Russia; 10. Kazakhstan; 11.Philippines; 12.Mongolia
(24%)
|
Matrix II - The 8th Grade,
TIMSS, 1995, 1999, 2003, and 2007
|
|
Math
|
Science
|
||
|
|
Full sample
|
Top
10 %
|
Full sample
|
Top 10%
|
|
Males
Dominate
|
58%
|
78%
|
70%
|
83.33%
|
|
Females
Dominate
|
7%
|
1.37%
|
7.1%
|
5%
|
|
Equal
|
1.Finland; 2.Iceland; 3.New
Zealand; 4.Norway; 5.Slovenia; 6.Sweden; 7.Egypt; 8.Kuwait; 9.Jordan;
10.Oman; 11.Palestine; 12. Qatar; 13.Saudi Arabia; 14.Syria; 15.Dubai;
16.Bosnia & Herzegovina; 17.Iran; 18.Moldova; 19.Malaysia; 20.Georgia;
21.Macedonia FYR; 22.Lithuania; 23.Romania; 24.Russia; 25.Ukraine; 26.Chinese
Taipei
(37%)
|
1. Canada (BC); 2. Finland; 3.
Iceland; 4. Syria; 5. Dubai; 6.Bosnia & Herzegovina; 7.Iran; 8. Moldova;
9.Malta; 10.Cyprus; 11.Armenia; 12.Georgia; 13.Ukraine; 14.Philippines; 15Mongolia
(20.54%)
|
1. Algeria; 2.Egypt; 3.Kuwait;
4.Jordan; 5.Oman; 6. Palestine; 7.Qatar; 8.Saudi Arabia; 9.Bosnia &
Herzegovina; 10.Iran; 11.Moldova; 12.Malta; 13. Macedonia, FYR; 14. Serbia;
15.Philippines; 16.Mongolia
(22.85%)
|
1. Canada (BC); 2.Lebanon; 3.Dubai;
4. Iran; 5.Moldova; 6.Malta; 7.Armenia.
(11.66%)
|
Referencs
Andreescu T., A., J. A. Gallian, M. Kane, and
J. E. Mertz, (2008), Cross-Cultural Analysis of Students With Exceptional
Talant in Mathematical Problem Solving, otices of the AMS, Vol. 55, no.10,
1248-1260
Benbow, C.P., (1988), Sex Differences in Mathematical
Reasoning Ability Among The Intellectually Talanted, Behavioral and Brain
Sciences, 11, 169-183, 225-232.
Benbow,
C.P. and J. C. Stanley, (1983), Sex Differences in Mathematical Reasoning
Ability: More Facts, Science, 2222, 1029-1031.
Benbow,
C. P. and J. C. Stanley, (1980), Sex Differences in Mathematical Reasoning
Ability: Facts or Artifacts? Science, 201, 1262-1264.
Benbow, C.P., D. Lubinski, D.L. Shea, and H. Eftekhari-Sanjani,
(2000), Sex Differences in Mathematical Reasoning Ability: Their Status 20
Years Later, Psychological Science, 11, 474-480.
Hutchison, D. and I. Schagen, (2007), Comparisons
between PISA and
TIMSS: Are we the man with two watches? In Loveless,
T. (Ed.), Lessons learned: What international assessments tell us about math
achievement, 227–261, Washington, DC: Brookings.
Hyde, J.S. and J. E. Mertz, (2009), Gender, Culture and
Mathematics Performance, Proceedings of the National Academy of Science, USA,
106, 8801-8807.
Hyde, J.S., S.M. Lindberg, M.C. Linn, A. Ellis, and C.
Williams, (2008), Gender Similarities Characterize Math Performance, Science
321, 494-495.
Hyde, J.S., (2005), The Gender Similarities Hypothesis,
American Psychologist, 60, 581-592.
Hyde, J.S., E. Fennema, M. Ryan, L.A. Frost, and C. Hopp,
(1990), Gender Comparisons of Mathematics Attitudes and Effects, Psychology of
Women Quarterly, 14, 299-324
[1] First-Order
Stochastic Dominance is tested using the powerful Rank Sum Test of (Wilcoxon,
1945).
[i] Commonly used data include Program
of International Student Assessment (PISA) of the World Bank, Trend in
International Math and Science Study (TIMSS), The U.S. SAT test scores, Study
of Mathematically Precocious Youth (SMPY), Putnam Mathematical Competition, and
the International Mathematical Olympiad (IMO).
[iii] Also see for
example Hutchison and Schagen (2007).
[iv] Also see, Hyde (2005),
Hyde et al. (1990), and Hyde and Mertz (2009).
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