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Gendered languages

Introduction

Language is an important cultural institution in human society. The World Bank (2019) estimates that 38 percent of world languages have grammatical gender, which can be defined as a system of word classification in which words are grouped into categories or “genders”. In the last decade, gendered language has attracted increasing attention from social scientists as a force shaping socio-economic inequalities and development outcomes. Evidence from recent research in economics, psychology and management has shown that the gender system of a language has causal impacts on wage inequality, female labor force participation, gender gap in math achievement, innovation output, gender norm attitudes, among others.

Source: World Atlas of Language Structure dataset (WALS)

Grammatical gender in language may or may not be linked to biological sex. In some languages, gender is based on an animacy (living/non-living) rather than a male/female distinction, such as in Swahili. Grammatically gendered languages vary in the specific location in syntax to which gender is attached (Kramer 2016). Some languages gender-mark nouns only, whereas in others gender is marked in various locations in the syntax.  Gender can manifest in (1) adverb modifiers: for example, “la voiture” the car, “le marteau” the hammer in French; (2) adjective modifiers: for example, “la nouvelle voiture” the new car, “lemarteau perdu” the lost hammer in French; (3) pronouns: For example, the sex-based pronominal gender system she/he/it in English; and/or (4) verbs: For example, “молодая медсестра пошла в больницу” – “The young nurse went to the hospital” in Russian. Here, the modifier and the verb are both conjugated to the female gender in agreement with the gender of the subject. Arabic is another language where verbs are gendered in accordance with the gender of the subject. Some languages whose noun gender system is sex-based do not indicate sex in pronouns, such as Tamil and Farsi; whereas some gender-mark pronouns only, not nouns, such as English.  

Operationalizing grammatical gender as an independent variable

What does genderedness of a language capture?

Explanations vary regarding the mechanism through which grammatical gender impacts decision-making and behavior. Proponents of one view posit that grammatical gender, like other language structures, arises from evolutionary pressures shaping patterns of reproduction and the division of labor in the history of a given society (Dahl 2004; Johansson 2005; Galor et al. 2018; Shoham 2019). Language structure, along this view, has been described as “institutional memory” (Hicks et al. 2015), “gender roles mirror” (Shoham 2019) and “a vehicle for cultural transmission” (Gay et al. 2013). Therefore, grammatical gender encodes historical institutions and acts as a proxy for their effects. Another view suggests that variations in language structures give rise to differences in individuals’ reasoning, learning, and other mental activities (Whorf 1956; Lucy 1997).

Exploring mechanisms is especially relevant to policy because determining what policy can change and cannot change requires elucidating the source of constraints or shifters of preference. It is difficult for policy to cause wholesale change in social and cultural norms. So if gendered language has no independent effect apart from mediating that of social and cultural norms, language reform policy has little leverage. However, if gendered language alone constitutes a source of psychological constraints or primers with impact on behavior or decision-making, language reform policy can be an easy-to-implement and low-cost way of attaining desired change in agents’ behavior or decision-making.

Language as a measure of culture

Language structures are part of culture, broadly understood. However, unlike other cultural features which evolve independently, language structures are highly correlated with other subsets of culture. Attributing autonomous causal power to gendered language faces difficulty given the presence of a rich set of confounders (Maviskayan 2015). For example, what historically caused the emergence of certain features of linguistic structures may directly shape the outcome variable, eg. historical migration and labor specialization patterns.

Scholars have used language structure as an instrumental variable for culture. For example, Licht et al. (2007) use the grammar of pronouns as an instrumental variable to study how countries that favor autonomy, egalitarianism, and mastery exhibit less corruption. However, this approach assumes that language structure has no autonomous, unmediated causal impact on individual propensity to corruption, which is contradicted by the linguistic relativity hypothesis. Studies, such as Gay et al. (2013), have shown that linguistic structures can have significant effects on socioeconomic outcomes after controlling for measures of culture.

Measurements

What constitutes a grammatically gendered and a grammatically genderless language is subject to contested definitions. Authors of the World Atlas of Language Structures (WALS) articulate four gender-related grammatical features of language, each of which can be represented in a dummy variable as follows (summarized in Gay et al. 2013):

Measurement strategy Definition Binary/continuous Adoption (# articles)
Gay I (2013) GII = SBI + NGI + GAI + GPI Continuous (0-4) 6
Gay II (2018) GII = SBI × (GPI + GAI + NGI) Continuous (0-3) 1
Jakiela & Ozier (2018) GG = SBI × GAI Binary 2
Stahlberg (2007) A grammatically gendered language is one where every noun is assigned feminine or masculine or neuter gender. It is distinguished from natural gender languages and genderless languages Binary 1
Givati & Troiano (2012) The number of cases of gender-differentiated pronouns Continuous 1
Mavisakalyan (2015) A language is either highly gendered, mildly gendered, or gender neutral Continuous (0-2) 1
Table 1. Measurement strategies

Other measurement strategies exist: in Jakiela & Ozier (2018) define grammatical gender by requiring formal gender assignment (GAI=1), combined with sex-based assignment (SBI=1) to create their metric (GAI × SBI); Stahlberg et al. (2007) classify languages into three categories: grammatical gender languages (nouns have gender), natural gender languages (no grammatical gender, but pronouns may reflect sex), and genderless languages (no gender in nouns or pronouns). Givati & Troiano (2012) quantify grammatical gender as the number of gender-differentiated pronouns, e.g. Spanish has four cases of gender-differentiated pronouns (third-person singular, first-person plural, second-person plural, and third-person plural). Lastly, Mavisakalyan (2015), building on Siewierska (2008)’s categorization of languages based on the intensity of gender distinctions in pronouns into six types, offers a revised framework with three types: highly gendered (Gender distinction in third-person and also the first- and/or the second-person singular pronouns), mildly gendered (Gender distinction in third-person singular pronouns only), and gender-neutral (No gender distinction in pronouns).

Table 2. Grammatical gender features in WALS

  0 1
Sex-Based Intensity (SBI)[1] languages without a sex-based gender system languages with a sex-based gender system
Number Gender Intensity (NGI) languages with three or more genders or with no gender distinctions languages with exactly two genders
Gender Assignment Intensity (GAI) languages with no gender assignment system or where the gender assignment system is only semantic[2] Languages where the gender assignment system is both semantic and formal[3]
Gender Pronouns Intensity (GPI) languages which do not distinguish gender in pronouns (or does so only in the third-person pronoun). languages with a gender distinction in third-person pronouns and also in the first and/or the second person
Table 2: Four gender-related grammatical features of language according to classification by authors of the World Atlas of Language Structure dataset (WALS)

Existing Evidence

A large body of work in psychology exploring the effect of gendered language on psychological processes and attitudinal and cognitive outcomes exist; however, the recent economics literature has increasingly focused on socioeconomic outcomes. Existing literature on the effect of gendered language predominantly find a negative effect of gendered language on gender equality, understood as women’s attainment, or the parity between men and women, of socioeconomic outcomes. These outcomes include the Global Gender Gap Index score (Prewitt-Freilino et al. 2012); education attainment (Davis & Reynolds 2018; Galor et al. 2020); labor force participation (Givati and Troiano 2012; Gay et al. 2013; Mavisakalyan 2015; Jakiela and Ozier 2018; Gay et al. 2018); political participation (Gay et al. 2013), access to land and credit (Gay et al. 2013); representation of women on corporate boards (Santacreu-Vasut et al. 2014; Pisera 2023); gender wage gap (Van der Velde et al. 2015; Shoham & Lee 2018); entrepreneurship activity (Hechavarría et al. 2018; Xie et al. 2021); women’s math performance (Kricheli-Katz & Regev 2021; Cohen et al. 2023).

Exceptions include Del Caprio & Fujiwara (2023), focusing on women’s application to online tech jobs, which finds no evidence of a significant effect of changing the gendered form of address in job ads except for fields where there is existing substantial representation of women; and Santacreu-Vasut et al. (2013), who find a positive relationship between gendered language and gender equality, although equity is legislated (gender quota in a parliament) hence possibly reflecting that a society with gendered language is more likely to require a quota for representation than a society able to move toward equality more naturally.


[1] SBI includes nomial as well as pronominal sex-based gender system. English, for example, is considered to have SBII=1 since it has sex-specific pronouns, although it is otherwise usually considered a grammatically genderless language.

[2] Semantic gender assignment is based on the inherent meaning or characteristics associated with nouns. Nouns are assigned to gender classes based on their semantic properties, such as biological sex, animacy, or natural gender. In this system, the gender assignment of a noun is often predictable based on the noun’s meaning, eg. “la grand-mère”, the grandmother; “le fils”, the son.

[3] Formal gender assignment, also known as grammatical or arbitrary gender assignment, is based on the form or shape of nouns rather than their inherent meaning. Nouns are assigned to gender classes based on grammatical rules and patterns within the language, which may not correspond to natural or semantic gender distinctions, eg. “la voiture”, the car; “le Pakistan”, Pakistan.


Glossary

Grammatical gender A system in which nouns are always categorized into classes, which are often but not always linked to biological sex
Syntax The order in which words are arranged in a sentence
Syntax agreement Agreement occurs when a word changes form depending on the other words in a sentence to which it relates.
Semantic Relating to meaning in language
Modifier An adjective or an adverb used to modify a noun
Lexical Relating to the words or vocabulary of a language
Lexical gender Semantic property carried in lexical units, such as “mother” and “son” in English which assign female or male quality to the referent
Referential gender A sub-category of lexical gender where referential lexical units, ie. pronouns have gendered semantic property, such as “he” and “she” in English
Social gender (also called natural gender) Socially imposed dichotomy of masculine and feminine traits associated with nouns, such as “trucks” (masculine) v. “lamp” (feminine), which often but do not always coincide with grammatical gender
Generic masculine (also called false generics) Male generic usage in cases of gender-indefinite reference. E.g., the singular generic masculine in English, “An American drinks his coffee black”; the plural generic masculine in Spanish, “Los olímpicos han vuelto” (The Olympians have returned).
Speaker-gender dependent expressions Expressions or linguistic structures which male or female speakers of the language ought to use exclusive to their gender, eg. politeness expressions reserved for women in Japanese; separate languages for men and women in the Ubang community in Nigeria

Patterns of household food consumption across food groups and sources in sub-Saharan African countries

Background

In most low- and middle-income countries (LMICs), per capita food expenditure has been steadily rising over the past few decades despite challenges from climate change, conflict, and COVID-19. Trends in food consumption are driven by urbanization, higher incomes, globalization, increased economic integration, and consumer preferences. In sub-Saharan Africa (SSA) there has been a shift away from the consumption of staple foods toward an increasingly diversified diet. Understanding these trends, however, remains constrained by the lack of large-scale cross-national data on the pattern of consumption across a broad set of food items. In particular, there is little information on cross-country and within-country variations in food consumption patterns and how households acquire food. Agricultural livelihoods dominate most LMICs, with many households’ food consumption coming predominantly from their own production. As economies transform and agriculture transitions from subsistence to commercial farming, it is expected that households will increasingly source food from markets. Increasing consumption from locally sourced production can incentivize investment in productive farm technologies and reduce import dependency, thereby contributing to food security. In this blog, we discuss an effort led by the University of Washington Evans School of Policy Analysis and Research (EPAR) group to standardize data on the value of food consumption patterns for a large number of food items and countries in SSA. We then leverage the data to discuss some insights regarding patterns of value of food consumption by food categories, food sources, and socio-demographics.

Standardizing food consumption indicators in large-scale household survey datasets

We leverage large-scale household datasets collected by the World Bank and country National Statistical Offices to construct food consumption indicators for 16 SSA countries over the period 2008-2021. These surveys ask households to report the amount of consumption from own-production and gifts, and the amount and value of food purchased over the past 7 days prior to the interview. Consumption from purchases comprises food items that are accessed from markets. Consumption from own production refers to consumed food items that are produced by households. Consumption from gifts encompasses food items households received from other households, non-governmental organizations, and the government. The value of food consumption from own production and gift was constructed using unit values estimated in reported quantities and values of purchases. For household food item observations for which no market purchase was reported, unit prices are imputed using the median purchase price of the same food items at the lowest administrative level with at least 10 observations. Food items were aggregated into broad categories: cereals, roots and tubers, pulses, legumes and nuts, dairy, fish and seafood, fruits and vegetables, livestock products, non-dairy beverages, oils and fats, processed food, other food, meals away from home, and tobacco. For comparability across countries, the monetary value of consumption was annualized and converted to 2017 Purchasing Power Parity (PPP).

Current patterns in average total value of food consumption at the aggregate level and by food items

Figure 1 presents a graph of the average annual per capita consumption in 2017 PPP for the most recent wave of data available for included countries. Nigeria had the highest average per capita value of food consumption in 2018, while Ethiopia had the lowest average per capita value of food consumption in 2021.

Figure 2 is an interactive graph allowing a user to select one or multiple countries or years and display the average per capita value of food consumption disaggregated by food items. One takeaway is that for most countries, cereals continue to be the main food item consumed, with the highest average per capita value of consumption in all countries except Benin, Cote d’Ivoire, and Uganda. The other top food item consumed in terms of monetary value is fruits and vegetables, except in Nigeria and Uganda. The least consumed food items are pulses and legumes and roots and tubers, with the exception of Uganda where oils/fats and non-dairy beverages are the least consumed food items. For countries with multiple years of data, we can examine trends in the per capita value of food consumption over time. We see, for example, a consistent increase in the value of consumption of cereals, pulses, legumes and nuts in Malawi and Mali.

Patterns in the value of food consumption by sources

Figure 3 presents the average annual share of the value of household food consumption from purchases, own production, and gifts. Across all countries and years, about 75% of household value of food consumption is from market purchases, while own production and gifts represent 20% and 5% respectively. There are substantial variations across countries and over time. Senegal had about 93% of its household value of food consumption acquired through purchases in 2018 while the lowest share was recorded in Uganda in 2011 (46%). For most countries, the relative importance of market-sourced food is growing. For example, in Uganda, the share of food from markets increased from, 46% in 2011 to 59% in 2019. Similar growth was observed in Ethiopia, Tanzania, and Niger.

Figure 4 presents an interactive graph showing the average share of the value of household food consumption from purchases, own production, and gifts, disaggregated by major food categories. It reveals that for most food categories, more than 60% of consumption comes from purchases. This is particularly true for high-value commodities such as fish and seafood, livestock products, fruits and vegetables, oils and fats, non-dairy beverages, and processed food. For staple crops such as cereals, pulses, and roots and tubers, the purchased share is lower. The consistency of shares by sources over time also varies; for example, Tanzania consistently had more than 50% of its dairy consumption from own production while in Malawi, less than 20% of dairy consumption come from own production. We see a gradual decrease in consumption of pulses, legumes, and nuts from own-production and a resulting increase in consumption from purchases and gifts. The share of roots and tubers increased for most of the waves in Tanzania while there was a consistent decrease in Nigeria.

Spatial and gender heterogeneity in the value of household food consumption

Figure 5 presents an interactive spatial distribution of the total value of food consumption from purchases, own production, and gifts at both country and administration one levels. The maps can be further disaggregated by year, location, and gender of household head. These maps show that countries in East Africa had a greater value of food consumption from their own production compared to other SSA countries. The estimates mapped can also be disaggregated by place of residence and the gender of the head of household to produce location- and gender-specific insights.  This insight holds for both male and female-headed households as well as households located in both rural and urban areas. This distinction is further strengthened when consumption is disaggregated by food items (see Figure 7).

Figure 6 explores differences in the share of the value of food consumption from different sources disaggregated by location. On average across countries, about 65% of food consumption for rural households comes from purchase. This percentage rises to about 90% for urban households in most countries, except Kenya and Uganda.

Figure 7 presents the same interactive graph as Figure 6 but is further disaggregated by the gender of the household head. Here, we see that for most countries, female-headed households (FHHs) residing in urban areas have a higher share of food consumption value from purchases compared to their counterparts in rural areas. The same distinction is also applicable for male-headed households (MHHs). The reverse is the case in Malawi where FHHs in both urban and rural areas have a lower share of food consumption value from purchases compared to MHHs. More generally, MHHs in both urban and rural areas tend to have a higher share of food consumption value from own production compared to FHHs.

Concluding remarks

This blog provides insights into the sources and patterns of the value of food consumption in SSA. It leverages a new dataset put together by EPAR processing and merging food consumption indicators in nationally representative large-scale household surveys collected in 16 SSA countries over the period 2008 – 2021. The analysis reveals that of the different sources of food examined, market-purchased consumption accounts for the highest value, even in rural areas. It also shows a rapid shift towards increased value of food consumption from purchases, marking a departure from traditional practices of consuming own-produced food and gifts. The analysis indicates that this shift is not uniform across countries and socio-demographic characteristics of households within countries. These shifts, rooted in socio-economic changes, gender roles, and urbanization, underscore the complex challenges and dynamics facing global food security and nutrition strategies. The dataset can be used to help understand changes in food sourcing and what this might mean for nutrition, resilience, and market access. The Stata codes to generate the dataset is available for download at the EPAR GitHub Repository. The more complete visualization data is also accessible on tableau visualization platform.

Blog written by Amaka Nnaji, Ahana Raina, Didier Alia and C. Leigh Anderson.