An Aspect of Statistical Methods Employed in The Gendering of Language: A Comparison of Gender Equality in Countries with Gendered, Natural Gender, and Genderless Languages

(A first attempt at technical writing.  It’s not perfect but it’s not terrible either.  With more practice, this will improve as well.)

As a metaphor, social psychology is much like the epic novel of a country’s history laid bare from all perspectives including political majority and minorities viewed through the inner workings of their movements explained and interpreted through words, ideas, and points of view, which are generally limited. Statistical research, on the other hand, if it is conducted and interpreted properly, reveals numerical probabilities that cannot be ignored and are similar to the infinity of a profound piece of art,pierre august renoir like Pierre-Auguste Renoir’s “In The Meadow,” that pulls you further and deeper in each time you look to see newer details of raw art or numbers in front of you. In the case of the statistics, the numbers are interpreted through a filter, usually, software, that allows us to see details that the naked eye cannot.

The study of statistics has helped me understand concepts related to raw numbers, and statistics will continue to teach me as I learn further to understand and analyze study results and their interpretations in news articles and academic literature, such as the one I am concerned with here, “The Gendering of Language: A Comparison of Gender Equality in Countries with Gendered, Natural Gender, and Genderless Languages.” While there is more than enough detail in this article to encourage further study, I would like to understand the implications of this study, before moving on to read further academic articles and perform my own research.

The purpose of this academic article was to analyze the connection, within 111 countries, between the grammatical gender in language and societal gender equality. They , hypothesized four standard co-variables as influencers (geographic region, religion, government structure, and the Human Development Index (HDI)) upon the GGG Report (Global Gender Gap). These co-variables, while not important to the statistical results that I am interested in here, do reflect upon the gendered, natural, or genderless language of each country and influence the GGG overall.

For this study, countries were categorized, into three different categories: Gendered, Natural, and Genderless languages. Within this article, gendered languages are “defined by their nouns, which are always assigned a feminine or masculine (or sometimes neuter) gender.” In other words, when nouns refer to people, they refer to the gender of the person in question. When they refer to objects, they are also given a gender of masculine or feminine, as if the object themselves possessed gender. The descriptors of these nouns also usually reflect these same gender qualities. Gendered linguistic families and examples include Slavic (Russian), Germanic (German, but not English), Romance (Spanish), Indo- Aryan (Hindi), or Semitic (Hebrew) languages. Natural gender languages are characterized by the pronouns he and she to distinguish male and female genders, but otherwise have no marking of gender for objects. This arrangement is unlike the gendered languages described above. “English (a West Germanic language), and Northern Germanic (or Scandinavian) languages belong to what are called natural gender languages.” Finally, genderless languages are characterized by genderless pronouns. “For example, hän in Finnish refers to both he and she and has no gender. “Genderless languages generally belong to the Uralic (Finnish), Turkic (Turkish), Iranian (Persian), Sinitic (Chinese), and Bantu (Swahili) language families, along with some others.” (Prewitt-Freilino et al, 2011, p. 269)

The gender equality was measured by first determining whether the dominant language is gendered, natural, or genderless. Each language was assessed through weighted comparisons of . The authors’ first hypothesis is “Countries predominated by a gendered language system should consistently evidence less gender equality across the various indexes than countries where natural gender or genderless languages are spoken, even when controlling for geographic, religious, political, and developmental variations that could also explain differences in gender equality among countries.” Their second hypothesis is, “Countries predominated by a natural gender language system should evidence greater gender equality than countries with other grammatical gender systems.”

The criteria that the authors used upon the four independent variables (the economic, political, education-, health-based) was an analysis of variance, ANOVA, or in this case, an analysis of co-variance, ANCOVA, with government contrast, religion contrast, geography contrast, and HDI scores as covariants. With five univariate follow-up tests, the alpha level (or level of significance) was set at α = .01 for each or a total of.05 for the 5 covariants. These analyses results that showed a significant effect upon gender equality for the overall Global Gender Gap at p < .001, and the economic participation rate, < .001. The result was a very strong presumption to reject the null hypothesis. The analyses of the remaining dependent variables did not yield significant results that supported the null hypothesis.

The authors “anticipated that grammatical gender language within a given country had the potential to predict overall levels of gender equality.”(Prewitt-Freilino et al, 2011, p. 281) As they predicted in their first hypothesis, they found that countries that speak gendered languages exhibit generally less gender equality than countries that speak natural gender or genderless languages. The authors found this result especially true in instances of gender differences in economic participation, even with other conditions, such as religion and form of government influencing gender equality.

Besides the aforementioned Finland with its genderless language, several others exist, including Iran (with a very low gender equality rating) and several South East Asian countries. The results indicate less equality than even a gendered language country like Ireland and explain the decrease in equality through the obvious weighted variables described above. However, this is still a surprise because my assumption prior to reading this study would have been the opposite: that gendered language societies, whether gendered or naturally gendered, are less gender-equal than genderless language societies.   While beyond its scope, the current study suggests that it could provide an impetus to research how gendered grammar influences attempts to reform language to a genderless norm and positively change the lives of women and men. The results don’t provide anything related to specific reasons for gender equality in an individual country other than the variables above, but this topic is a subject for future study. Such a study could explore the gendered sexism of language and how it operates on a daily basis to influence individuals and how this sexism affects interpretations of language meanings and personal relations between genders in one country.

Resources:

Prewitt-Freilino, J. L., Caswell, T. A., & Laakso, E. K. (2012). The gendering of language: A comparison of gender equality in countries with gendered, natural gender, and genderless languages. Sex roles, 66(3-4), 268-281.

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