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Jensen (1980) states: The largest and most consistently found sex difference is spatial visualization ability, especially on spatial tests that require analysis, that is mentally breaking up a gestalt into smaller units in ways that facilitate spatial problem solving (eg, the Block Designs test)..[;] the sex difference in spatial ability is not established consistently until puberty, and it persists thereafter Generally, in studies of adolescents and adults, only about one-fourth of the females exceed the male median on various tests of spatial visualization (p 626) Related to this topic, Chastain and Joe (1987) performed a canonical correlation analysis using data from the entire WAIS-R standardization sample They entered the 11 subtests and a variety of background variables into the analysis, interpreting as meaningful three canonical factors, one of which, labeled Manual Dexterity, included a 72 loading by Gender (males were coded as 1, females as zero).

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Block Design (49) and being in a skilled occupation like carpentry (38) also related substantially to this dimension; other tasks with moderate loadings were Picture Completion, Object Assembly, Picture Arrangement, and Arithmetic This canonical factor, defined primarily by maleness, reiterates other findings of men generally outperforming women on visual spatial tasks Hyde (1981) calculated that about 4% of the variation in visual spatial abilities is attributed to gender differences, versus only about 1% each for verbal ability and quantitative ability According to Deaux (1984), similar small effect sizes for the variable of gender have been identified for noncognitive factors as well, such as aggression and social influence She states that, although additional evidence remains to be gathered, 5% may approximate the upper boundary for the explanatory power of subject-sex main effects in specific social and cognitive behaviors (p 108)..

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The results of gender differences on major intelligence tests are of limited generalizability regarding a theoretical understanding of male versus female intellectual functions. The results are contaminated because, as noted, test developers have avoided gender bias whenever possible when selecting tasks and items. Thus, the mean gender differences in global IQs are undoubtedly an artifact of the specific subtests included in the WAIS-III, KAIT, and other tests; to some extent, differences in subtest scores (such as WAIS-III Information or KAIT Famous Faces) may be an artifact of the specific items chosen for each subtest. However, it is possible to reach some hypotheses about true male female differences on some of the subtests (Kaufman et al., 1988). It is hard to imagine how any Block Design or Digit Symbol items could have been eliminated due to gender bias (or any other kind of bias) because of the abstract, nonmeaningful nature of the stimuli; similarly, Arithmetic items are far more dependent on the computational process than on the verbal content, and therefore are not reasonably subject to the potential impact of bias. Consequently, it seems reasonable to conclude that adult males

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API didn t always return one result. Most times, multiple results were returned, as shown in Figure 9-28. After a bit of testing, I learned that this was because of the inconsistency with which I had entered the addresses into the site, I didn t always add the ZIP code or correct street address. The API uses the address to match a review. If a full address isn t provided, the API has a harder time making an exact match. Some API calls returned one result, whereas others returned five. This option was not going to work.

are superior to adult females in the skills assessed by WAIS-III Block Design and Arithmetic and KAIT Memory for Block Designs, and that adult females clearly outstrip adult males in the ability measured by Digit Symbol. All of these conclusions are quite consistent with the bodies of research discussed in the previous sections. However, even the WAIS-III and KAIT subtests that yielded the largest gender differences produced differences of about 0.40 to 0.50 SD, which reflect small (or, at best, moderate) effect sizes (McLean, 1995). Consequently, even the tried-and-true gender differences produce discrepancies on adult intelligence tests that are too small to be of very much clinical value.

This section reports data on ethnic differences, focusing on the groups for which there are ample data based on research with the WAIS-III and other individually administered intelligence tests for adolescents and adults: Caucasians, African Americans, and Hispanics.

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