It was the Danish economist Ester Boserup who first came up with the plough hypothesis: that societies that had historically used the plough would be less gender equal than those that hadn’t. The theory is based on the relative female-friendliness of shifting agriculture (which is done using handheld tools like hoes or digging sticks) versus plough agriculture (usually driven by a powerful animal like a horse or an ox), the idea being that the former is more accessible to women.1
This sex difference in accessibility is partly because of the differences between male and female bodies. Ploughing requires ‘significant upper body strength, grip strength, and bursts of power, which are needed to either pull the plough or control the animal that pulls it,’ and this privileges male bodies.2 Upper-body mass is approximately 75%3 greater in men because women’s lean body mass tends to be less concentrated in their upper body,4 and, as a result, men’s upper body strength is on average between 40-60%5 higher than women’s (compared to lower-body strength which is on average only 25% higher in men6). Women also have on average a 41% lower grip strength than men,7 and this is not a sex difference that changes with age: the typical seventy-year-old man has a stronger handgrip than the average twenty-five-year-old woman.8 It’s also not a sex difference that can be significantly trained away: a study which compared ‘highly trained female athletes’ to men who were ‘untrained or not specifically trained’ found that their grip strength ‘rarely’ surpassed the fiftieth percentile of male subjects.9 Overall, 90% of the women (this time including untrained women) in the study had a weaker grip than 95% of their male counterparts.
But the disparity in the relative female-friendliness of plough versus shifting agriculture is also a result of gendered social roles. Hoeing can be easily started and stopped, meaning that it can be combined with childcare. The same cannot be said for a heavy tool drawn by a powerful animal. Hoeing is also labour intensive, whereas ploughing is capital intensive,10 and women are more likely to have access to time rather than money as a resource. As result, argued Boserup, where the plough was used, men dominated agriculture and this resulted in unequal societies in which men had the power and the privilege.
According to a 2011 paper, Boserup’s hypothesis holds up to scrutiny.11 Researchers found that descendants of societies that traditionally practised plough agriculture held more sexist views even if they emigrated to other countries. The paper also found that sexist beliefs correlated with the kind of geo-climactic conditions that would favour plough agriculture over shifting agriculture. This suggested that it was the climate rather than pre-existing sexism that dictated the adoption of the plough – which in turn drove the adoption of sexist views.
The plough theory has its detractors. A 2014 analysis of farming in Ethiopia points out that while farming is strongly identified with men in that country (the farmer is male in ‘virtually all Amharic folklore’), and ploughing in particular is exclusively male, the upper-body-strength argument doesn’t hold there, because they use a lighter plough (although this of course doesn’t deal with the capital investment or childcare issues).12 This analysis also cites a 1979 paper which disputes the theory on the basis that ‘even where the plough never was introduced, among South Cushites in particular, still men are the cultivators’.
Are they though? It’s hard to say, because the data on who exactly is doing the farming is, yes, you’ve guessed it, full of gaps. You’ll find no end of reports, articles and briefing papers13 that include some variation on the claim that ‘women are responsible for 60-80% of the agricultural labour supplied on the continent of Africa’, but little in the way of evidence. This statistic has been traced back to a 1972 United Nations Economic Commission for Africa, and it’s not that it is necessarily wrong, it’s just that we can’t prove it one way or the other, because we lack the data.
This is partly because, given men and women often farm together, it is difficult to accurately determine how much of the labour of either sex goes into producing an end food product. In a United Nations Food and Agriculture Organization (FAO) paper, economist Cheryl Doss points out that it also depends on how we define and value ‘food’: by caloric value (where staple crops would come out on top), or by monetary value (where coffee might win)? Given women ‘tend to be more heavily involved in the production of staple crops’, comparing calorific value ‘might indicate a significantly higher share being produced by women.’14
‘Might’ is doing a lot of work there, though, because national surveys often don’t report on whether farmers are men or women.15 Even where data is sex-disaggregated, careless survey design can lead to an under-reporting of female labour: if women are asked if they do ‘domestic duties’ or ‘work’, as if they are mutually exclusive (or as if domestic work is not work), they tend to just select ‘domestic duties’ because that describes the majority of what they do.16 This gap is then compounded by the tendency to ‘emphasize incomegenerating activities’, the result being that they often underestimate (often female-dominated) subsistence production. The censuses also tend to define agriculture as ‘field work’, which leads to an undercounting of the women’s work ‘such as rearing small livestock, kitchen gardening, and post-harvest processing’. It’s a fairly clear example of male bias leading to a substantial gender data gap.
A similar problem arises with the division of work by researchers into ‘primary’ and ‘secondary’ activities. For a start, secondary activities are not always collected by surveys. Even when they are, they aren’t always counted in labour-force figures, and this is a male bias that makes women’s paid work invisible.17 Women will often list their paid work as their secondary activity, simply because their unpaid work takes up so much time, but that doesn’t mean that they aren’t spending a substantial proportion of their day on paid work. The result is that labour-force statistics often sport a substantial gender data gap.18
This male bias is present in the data Doss uses to check the 60-80% statistics. Foss concludes that women make up less than half of the global agricultural labour force, but in the FAO data she uses, ‘an individual is reported as being in the agricultural labor force if he or she reports that agriculture is his or her main economic activity’. Which, as we’ve seen, is to exclude a substantial chunk of women’s paid labour. To be fair to Doss, she does acknowledge the issues associated with this approach, critiquing the absurdly low 16% reported share of the agricultural labour force for women in Latin America. Rural women in Latin America, notes Doss, ‘are likely to reply that “their home” is their primary responsibility, even if they are heavily engaged in agriculture’.
But even if we were to address all these gender data gaps in calculating female agricultural labour we still wouldn’t know exactly how much of the food on your table is produced by women. And this is because female input doesn’t equal male output: women on the whole are less productive in agriculture than men. This doesn’t mean that they don’t work as hard. It means that for the work that they do, they produce less, because agriculture (from tools to scientific research, to development initiatives) has been designed around the needs of men. In fact, writes Doss, given women’s various constraints (lack of access to land, credit and new technologies as well as their unpaid work responsibilities) ‘it would be surprising if they were able to produce over half of food crops’.