Putative sex differences in verbal abilities and language cortext: A critical review

by Wallentin

This author reviewed many studies of gender differences in the brain. He found that there are some observed differences in early childhood and that some psychological problems are more likely to strike males than females, but other than that, there are no real differences in male and female brains, despite what is often printed in textbooks.

The Myth of Mars and Venus

One linguist, Deborah Cameron (2009), interprets Hyde’s (2005) findings as meaning that women and men, in truth, have more in common than pop psychologists’ books might have us believe. She writes to a popular audience and tries to convince laypeople that “evolutionary biology” is mere conjecture, and that writers like Tannen (1991) and Brizendine (2006), who emphasize the differences, are doing more harm than good. However, Cameron (2009) relies heavily on James & Drakich’s (1993) findings on amount of talk and on Hyde’s (2005) finding that the overall effect of gender on differences in communication is small. While Cameron is not fabricating numbers ala Brizendine (2006), she conveniently ignores all of Leaper’s studies that found significant differences in male and female styles of speech.

With the publication of Cameron’s The Myth of Mars and Venus (2009) as a popular/linguistic rival to Tannen’s You Just Don’t Understand (1991), two camps were created. They use different sets of data to justify different conclusions about gender’s effect on amount of talk. Only time will tell which school of thought will fade into history and which will prove lasting, or if, like Universal Grammar, one camp digs in, establishes its own universities, and refuses to listen to others in the field.

The Gender Similarities Hypothesis.

Hyde (2005) conducted a meta-analysis of the most up-to-date and methodologically sound 46 meta-analyses that examined psychological gender differences. She examined Leaper & Smith (2004) and Hyde & Linn (1988); she did not include any other study examined in this paper in her meta-analysis. Hyde found that “despite Tannen’s (1991) assertions, gender differences in most aspects of communication are small” (p. 586). The five meta-analyses concerning communication differences in gender, with a total of 13 different areas, had an averaged effect size (Cohen’s d ) of -.213, which according to Cohen’s benchmarks, is a small difference. Two of these communication meta-analyses did not study language: one examined studies on smiling and the other studied facial expression processing. The three meta-analyses concerned with language examined interruptions, talkativeness and whether the talk was affiliative or assertive (a different meta-analysis than Leaper and Sanders’ meta-analysis, discussed above), and self-disclosure. I computed that the average Cohen’s d of these three meta-analyses and their combined eight areas was -.039, which is decidedly insignificant. Hyde found some areas where the differences were statistically significant, but these areas were not related to amount of talk (they included throwing distance and amount of masturbation).

Gender differences in verbal ability: a meta-analysis.

Hyde & Linn (1988) set out to examine an adage in psychology that has been oft-repeated and seldom examined: that girls have better verbal abilities than boys. Their study included dissertations and unpublished studies, which are accessible via ERIC; all told, they examined 165 studies. The authors identified five different skills that might be measured in tests of verbal ability: definition retrieval, retrieval of names from a picture stimulus, creating relations between words, filtering for relevant information, and measures of verbal production. Unfortunately, Hyde & Linn (1988) did not report running tests without statistical outliers, instead simply excluding one study based on, apparently, their own judgment. They conclude, “that there are no gender differences in verbal ability, at least at this time, in American culture, in the standard ways that verbal ability has been measured” (p. 62). The verbal production subtests indicated that females performed better on tests that measure quality of production, but that males produced more in terms of “total talking time” (p. 64).

Race and gender in current American politics: A discourse-analysis perspective.

At least one study combined qualitative rhetorical analysis with quantitative word counts: Suleiman & O’Connell (2008) examined political guests on Larry King’s talk show. They found that the race of guests influenced the amount of non-standard speech they felt comfortable using, with Barack Obama, Condoleeza Rice, Hilary Clinton, and Colin Powell all using fewer non-standard forms than Bill Clinton. I mention this to note that researchers are beginning to take other sociological variables into account when examining discourse; I found this to be rare even in current studies. Suleiman and O’Connell’s quantitative analysis found that “Bill Clinton consistently talks the most, and Hillary Clinton the least” (p. 381). They note that this is consistent with Mehl’s finding that, contrary to the popular myth, women do not speak more than men. By comparing the amount of talk generated by political guests on a talk show to Mehl’s findings, the authors imply that the political interviewees verbal production can be generalized to the larger American population.

Gender differences across correlated corpora: Preliminary results.

Sabin, Goodwin, Goldstein-Stewart, & Pereira (2008) examined six different genres on the internet and found, consistent with Mehl (2007), no difference in amount of words generated by male and female authors, except “males generated significantly larger amounts of text than females on the topic of the legalization of marijuana” (p. 209).

Symbolic Capital in a Virtual Heterosexual Market.

Susan Herring studies computer-mediated communication and found that Italian women sending text message to a TV program sent longer text messages and used more non-standard typed methods of expressions, like emoticons and non-standard punctuation (Herring & Zelenkauskaite, 2009).