Correlates of maleness and femaleness

Introduction

"Female" and "Male" are here defined as "Having chosen the corresponding option in the test registration form". When "Female" is encoded as 0, "Intersexual" as .5, and "Male" as 1, the following statistics result:

Statistics of Sex as of 26 January 2023

Contents type: Personal information.   

• n: 3015
• Male: 2352
• Female: 548
• Intersexual: 1
• Unknown: 114
• Proportion of males among candidates of known sex: 0.811

Remark: This male/female ratio of 4.3 understates the sex difference in high-range test participation considerably; on the level of test submissions, this ratio is more like 11, because males take more tests per candidate.

Correlation of Sex with other mental ability tests

Weighted average of correlations: 0.126 (N = 8107, weighted sum = 1023.81)

Conservatively estimated minimum g loading: 0.36

Ranking in above table is based on the unrounded correlations. All available data is present in this table, no tests are left out except for those with less than 4 score pairs. All known pairs are used, including possible floor/ceiling scores or outliers.

Remark: For clarity, a negative correlation here means that females score higher than males on that test. With regard to the size of the correlations, one should keep in mind throughout this report that these are correlations wherein one of the variables is a dichotomy, which tends to result in lower values than is the case with regular correlations.

Estimated loadings of Sex on particular item types

These are estimated g factor loadings, but against homogeneous tests (containing only particular item types) as opposed to non-compound heterogeneous tests. Although tending to surprise the lay person, it is not uncommon for tests to have high loadings on item types they do not actually contain themselves. Such loadings reflect the empirical fact that most tests for mental abilities measure primarily g, regardless of their contents; that the major part of test score variance is caused by g, and only a minor part by factors germane to particular item types. It is of key importance to understand that this is a fact of nature, a natural phenomenon, and not something that was built into the tests by the test constructors.

N = 5661

Compound tests have been left out of this table to avoid overlap.

Balanced g loading = 0.37

Remark: This table implies that the sex score difference on high-range tests is smallest on heterogeneous tests and largest on one-sided verbal tests.

National means for Sex

For reasons of privacy, only countries with 2 or more candidates are included in this table. Ranking is based on the unrounded means, and then alphabetic.

Notice that these national means represent the proportion of males among the candidates from that country.

Correlation with national I.Q.'s of Sex

Correlation of this test with national average I.Q.'s published by Lynn and Vanhanen:

• r = -0.06 (n = 1671)

Although very small, this negative correlation is significant as a result of the large number of candidates. In words, it means that in countries with higher average I.Q.'s, female participation in high-range testing is greater. This concords with the author's hypothesis that sex differences are smaller in populations of higher average I.Q.

Correlation of Sex with personal details

These correlations reveal that females are markedly higher than males on neo-Marxist attitudes, and less often engage in negative behaviours like test fraud and insulting responses to disappointing scores. Males, on the other hand, are higher on the PSIA scales Just, Antisocial, Rare, System factor, Cold, Aspergoid, Rational, and Cruel.

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