Gender Mainstreaming in Miraa Farming in the Eastern Highlands of Kenya

Abstract

Miraa (Catha edulis forsk) farming is a major income earner in Kenya, but until recently, it was not scheduled as a priority crop in the country. Consequently, no gender research to identify men and women issues with the purpose of designing gender-responsive solutions for increased productivity has ever been conducted on the crop value chain. The main objective of the study was to examine gender issues in miraa production and marketing activities in Kenya. Data were collected using multiple methods. These included a formal survey that covered 962 households, key informants’ interviews, focused group discussions and a literature review. The household data were analyzed through descriptive statistics using SPSS Version 20 software. The Harvard theoretical framework was used to structure the analysis. The main findings indicate that women have less access to production resources such as land and extension services than men. Moreover, men performed almost all crop activities. Men also dominated all crop decisions. The study recommends that research scientists need to design gender-responsive technologies, innovations and management practices that are tailor made to meet men’s needs and concerns. This is because the crop appears to belong to men with less women’s operational and financial control.

1. Introduction

Miraa (Catha edulis forsk), also known as Khat, farming is a major income earner in Kenya. The plant has leaves with an aromatic odor and an astringent, slightly sweet taste. The most popular consumption method is through chewing the young tender leaves and soft twigs, which are rich in cathinone and cathine [1,2]. In Kenya, miraa is mostly grown in Meru, Tharaka Nithi and Embu Counties. Although the various gender categories (youths, men and women) play various roles in crop production and marketing activities, gender inequality exists in all areas of the value chain, from production to consumption. Women and youths have less access to production resources such as extension and land compared to men. However, young men perform most crop production and marketing activities, while adult men are the main decision makers, including usage of the proceeds.

When analyzing gender roles, there are several myths about how disfavored women and youths are in comparison with men, which are not necessarily supported by solid evidence [3,4,5]. For example, it is difficult to find evidence to support the myth that women own only one percent of the world’s land [4]. Access to resources such as land and a voice in decision making are important elements to consider for the improved adoption of Agricultural Technologies, Innovations and Management Practices (TIMP) by the various gender categories [6,7,8] for improved food and nutritional security as well as poverty reduction.

Although agricultural TIMPs might lead to increased production and income, there is no guarantee that more income will improve the poverty, food, security and nutrition security situation in the household. Who controls income and how decisions are made in relation to the use of additional income are important when considering what degree food, nutrition security and poverty will improve [6,8,9]. Surprisingly, if we close this gender gap by improving power relations in the household and improving women’s access to these resources, yields would increase by 20–30%. This would increase the outputs by 2.5–4%, thus reducing hunger by 12–17% [10].

Many gender studies have been conducted on various crop value chains in Kenya [5,11,12]. However, no studies have been conducted on the miraa value chain. This is because, until recently, miraa was not a scheduled crop in Kenya [2]. It is against this background that this study was conducted with the main objective of examining gender issues in miraa production and marketing activities. Understanding gender issues in the value chain would assist biophysical scientists to design gender-responsive tailor-made technologies, innovations and management practices for improved productivity and incomes. Arising from this objective were three research questions: (a) Which gender category performed what activities in the miraa production and marketing activities? (b) Which gender category had access to extension services? (c) Which gender category mainly made which decisions in the miraa production and marketing activities?

The study used the Harvard analytical theoretical framework as argued by [13] to analyze the data. This framework organizes data in the following profiles: (a) activity profiles, which show gender and age division of labor; (b) access and control profiles, which show the differences between men, women and youth access to and control of resources and benefits; (c) the influencing factors, e.g., social norms as well as economic and political forces, that may impact on gender roles and relations.

2. Literature Review

2.1. Gender and Division of Labor

Women in Africa play an important role in agricultural production, contributing about 50–80% [4,10,11]. Despite this huge contribution, women have less access to agricultural resources and decision-making powers than men due to inequalities constructed by patriarchal norms [4,6,7,14,15]. Furthermore, farm activities, access to resources and opportunities are influenced by gender, i.e., the social construction that assigns roles and responsibilities to men and women in a given society [15,16]. Consequently, in the household, various activities in the domestics, food crops and cash crop realms are gender differentiated. For instance, men dominate cash crop production and other income-generating activities, while women cultivate food crops [14,17]. Indeed, the introduction of cash crop production has attracted men into commercial agriculture, while women are entrusted with domestic activities and the small-scale production of food crops [14,16]. This assignment of responsibilities is nested in social norms that delegate men the responsibility of providing financial needs to the household while women provide food and nutritional needs [5,14,18]. Furthermore, cash crop production and marketing as well as control of the proceeds are often gender differentiated and sometimes vary by the type of crop [8,11,14]. In tandem with this conceptualization, women in Kenya generally cultivate food crops such as beans, maize, vegetables, fruits and tubers for home consumption, with the surplus being sold in the local market, and may retain the proceeds to cater for the household requirements. Men, on the other hand, are responsible for the marketing and control of incomes from cash crops such as tea, coffee and miraa [8,11,15,16].

2.2. Gender and Decision Making

There is ample evidence to show that men dominate decision making in cash-generating crops. A study in Tanzania by [19] found that men cultivated and dominated decisions in cash crops such as tea and coffee, while women were responsible for food crops. In Uganda, ref. [20] found that men dominated almost all decisions on the coffee value chain, including how to utilize the proceeds from the crop. This situation is not much different from Colombia, where [21] found that despite the fact that women performed a lot of coffee activities, they had little say in the production and marketing domains, where men dominated the decisions. The same case is applied in Indonesia, where [22] found that decisions related to coffee activities were made exclusively by men who owned the crop. In Kenya, the situation was not different because although women worked in coffee farms, men controlled the production and marketing activities [16,23]. Similarly, in Ghana, ref. [24] found that men dominated decisions in cocoa production and marketing activities. There is also evidence to suggest that whenever women’s traditional crops change from subsistence to the cash economy, men appropriate them. This is confirmed in the case of rice farming in Gambia, where the commercialization of rice shifted the power dynamics in the household, with men appropriating the crop that was traditionally regarded as women’s [25,26]. The same scenario is observed in groundnuts in Zambia [27], French beans and avocado in Kenya [8,16], hybrid maize in Zambia [27], and African leafy vegetables in Kenya [28].

2.3. Access to Extension Services by Gender

The agricultural extension service is a vital instrument for the provision of agricultural technology, innovations and management practices [29,30,31,32]. Extension can improve food and nutritional security as well as reduce poverty by bridging the gap between new technological knowledge and farmers’ own practices [29]. Effective extension services can also obtain information about men and women farmers’ needs and concerns and feedback to research and development centers to ensure that research agendas are gender responsive [33]. However, extension services often fail to reach women farmers, particularly women-headed households [32,33,34]. This is partly because extension agents tend to approach progressive farmers who are well endowed with resources such as land, labor and capital and who might have had a history of adopting agricultural technologies, innovations and management practices with the belief that the spillover effects will eventually reach the other cultivators. Consequently, women who are generally less endowed compared with men are left out of these extension endeavors [5,7,32]. Moreover, extension agents make the erroneous assumption that men who receive agricultural technology, innovations and management practices will disseminate to their wives if they need it. Furthermore, traditional research and extension agents usually assume that farmers are men. As a result, extension is typically directed to men farmers about male crops and activities [33]. However, this is not the case because the household is not always a homogenous economic unit with shared goals. Women and men often farm different crops and have access to different resources, opportunities and benefits [32,33]. Therefore, men and women’s differential constraints on productivity, division of labor and control of resources have widespread implications on who has access to extension and the accruing benefits.

3. Material and Methods

3.1. Study Sites

The study was conducted in Meru, Embu, and Tharaka Nithi Counties, as shown in Figure 1. The three counties were selected because they are the main miraa-growing areas in Kenya.

3.2. Sample Size and Sampling Technique

The study adopted the descriptive research design using quantitative and qualitative methods. In the quantitative method, a survey was conducted based on 2421 i.e., the total population of farmers who were growing miraa. To calculate the sample size, we assumed a 95% confidence level and p = 0.5 for the equation, as argued by [35].

$$\mathrm{n}=\frac{\mathrm{N}}{1+{\mathrm{N}\left(\mathrm{e}\right)}^2}$$

where n is the sample size, N is the population size and e is the level of precision. When this formula is applied to the population of 2421, we obtain a sample size (n) of 962 farmers, as shown below.

$$\mathrm{n}=\frac{2421}{1+{2421\left(0.05\right)}^2}=962 \mathrm{f}\mathrm{a}\mathrm{r}\mathrm{m}\mathrm{e}\mathrm{r}\mathrm{s}$$

3.3. Sampling Procedure

A combination of purposive and systematic sampling techniques was used. When these techniques are used in combination, they produce a powerful way of validating the research findings [36]. Thus, we purposively selected the three counties where miraa is largely cultivated. Then, in every county, we purposively selected a location and a sub-location where data were collected through the systematic sampling of farmers.

3.4. Data Collection

Data were collected by a team of well-trained enumerators using a questionnaire that had been pre-tested using Open Kit Data (ODK) software for collecting and managing data. Enumerators were chosen based on pre-selected criteria. The criteria included at least a university-level training, ability to speak the local language and previous experience in conducting survey interviews using ODK. This ensured that the enumerators asked the questions rightly, the respondents understood the questions the same way, and the answers were coded without the possibility of uncertainty, thus ensuring reliability. The questionnaires covered demographic and socio-economic information, gender activity profile, and gender access to and control of resources profile, as well as gender and decision making. Data were also collected through key informants’ interviews, focus group discussions and from secondary sources such as reports and journal articles. This triangulation of data from multiple methods ensured the validity of the findings.

3.5. Data Analysis

Data gathered from the household survey were cleaned, coded and entered in Statistical Package for Social Sciences (SPSS) Version 20 computer software. Then, descriptive statistics (frequency, percentages, chi-squared and means) were generated following data analysis based on the Harvard Analytical Framework [13], which organizes data into which gender category has access to and control of what resources, which gender does what activity, which gender makes what decisions, and the underlying influencing institutional structures (e.g., cultural norms). Focus group discussions and key informant interview transcripts were analyzed through content.

4. Results and Discussion

4.1. Demographic and Socio-Economic Characterization of Farmers

4.1.1. Sex of the Household Heads per County

Results revealed that the majority (90%) of households were headed by men who were also miraa owners, as shown in Figure 2. The fact that the majority of the households were headed by men may favor the adoption of miraa technologies, innovations and management practices. This is because various studies have shown a positive relationship between men-headed households and the adoption of agricultural technologies. This is mainly because men generally have more access to resources such as land, capital and credit compared with women, which can make them easily afford the cost of improved agricultural technologies [30,37,38]. Furthermore, in a patriarchal society such as in Eastern Kenya, men usually are the main decision makers in the household [15,16,23]. Therefore, they have the power to decide how many miraa trees to plant, where to plant and when to plant. Moreover, the socio-cultural norms may not favor women’s freedom of mobility to participate in forums such as farmer field days, agricultural shows and trainings where agricultural technologies are disseminated [15,39].

4.1.2. Age of Household Head

The majority (75%) of the household heads in the overall sample were within the age bracket of 26–55, years clustered as 26–35 years at 23%, 36–45 years at 27% and 46–55 years at 25%, as shown in Figure 3. Only 21% of the households in the overall sample were above 56 years, which meant that there were slightly younger farmers in miraa farming than in the general agricultural sector in Kenya [2,15]. This implied that miraa productivity had a bright future since the energetic and innovative youths who are the future farmers were highly involved in farming. This argument is based on key informants and focus group discussions that revealed age had a negative relationship with the adoption of miraa technology, innovations and management practices. In this study, younger farmers were characterized as shrewd, innovative and more exposed to information, which enabled them to make decisions on marketing options and the adoption of new agricultural technologies, innovations and management practices. The older farmers relied on their indigenous knowledge, which was becoming unreliable due to climate change and variability.

Studies on age and technology adoption have shown inconsistent conclusions. While some findings showed a negative relationship between age and technology adoption [6,30,40,41], others showed a positive relationship [42,43]. Age may show a positive correlation with technology adoption based on the fact that older farmers may have more experience in farming compared with younger farmers. Farmers accumulate more wealth as they become older. Consequently, this wealth may facilitate the adoption of technologies, innovations and management practices.

4.1.3. Education Level of the Household Head by Gender

The majority (over 50%) of all the households headed by men and women had attained primary school education, as shown in Figure 4. The highest percentage of farmers with primary education were men in Tharaka Nithi at 69%, followed by women in Meru at 55%. The highest percentage of farmers with secondary education were women in Tharaka Nithi at 50%, followed by men in Embu and Meru at 31% and 19%, respectively. The majority of those who had tertiary education were men at 12%, 10% and 7% in Meru, Embu and Tharaka Nithi, respectively.

The education level of the household head plays a key role in farming, especially in determining the adoption of agricultural technologies, innovations and management practices. Many studies have shown a positive correlation between education and the adoption of noble technologies and management practices. For instance, [37] found that household heads with higher education levels adopted inorganic fertilizer and improved maize varieties technologies more than the less educated. This correlation has been shown by many other studies [30,38,40].

We therefore support the argument that the education of the household head had a positive influence on the adoption of miraa technologies. Consequently, the combined relative youths and education levels of miraa farmers provided a favorable opportunity for the adoption of new technologies, innovations and management practices in the subsector. This implied high profitability of the crop because youths tend to adopt the more profitable varieties while the aged according to focus group discussions may retain the old varieties due to loyalty to historical and socio-cultural benefits. For instance, culturally, miraa products are central during marriage and dowry payments [2]. Indeed, education has the power to change the knowledge, skill and attitude of farmers [30,37,40]. Furthermore, more educated farmers can use information and communication technologies (ICTs) to access farming technologies such as crop agronomy, pest and disease management as well as real-time market information than the less educated.

However, as argued by [37], tertiary education, though positive in influencing technology adoption, was weak according to key informant interviews.

4.2. Decision Making by Gender on Miraa Production and Marketing Domains

All decisions related to miraa domains were made by men compared with women with significant differences (p < 0.05). Some of the domains where men dominated decisions included land use, (b) varieties to grow, (b) use of cash generated, (c) price to sell miraa, and (f) use of income from miraa, as shown in

Table 1. Decision making by gender on the miraa production and marketing domains.

Variable	Women		Joint		Men		Chi-Square	p-Value
	n	%	n	%	n	%
Land use	77	8.7	140	15.8	668	75.5	21.85	<0.001 ***
Which varieties to grow	74	8.8	79	9.4	686	81.8	21.89	<0.001 ***
Use of cash generated	78	8.9	199	22.8	595	68.2	55.58	<0.001 ***
Who and number of farm laborers to hire	97	11.2	145	16.7	626	72.1	28.11	<0.001 ***
Price to sell	70	8.1	97	11.2	696	80.6	17.45	<0.001 ***
Whether to borrow money and from where	72	8.7	208	25.0	551	66.3	74.06	<0.001 ***
How to use borrowed money	70	8.4	121	14.5	645	77.2	88.96	<0.001 ***
Which inputs to buy	70	8.4	121	14.5	645	72.2	58.86	<0.001 ***
Use of income from generated from the crop	69	8.3	230	27.7	531	64	68.64	<0.001 ***

NB/***—significant at 0.1%. Source: Miraa household survey 2019.

. It was surprising to find that men even dominated decision making over crop income. This was contrary to income generated from the dairy cattle subsector in the same region where [15] found that decisions pertaining to the utilization of proceeds from milk sales were arrived at jointly by men and women. Furthermore, [3] also found that women contributed a lot to decisions pertaining to the use of the proceeds from dairy cattle in Uganda. Meanwhile, [6] found that women played a substantial role in decisions pertaining to the use of the proceeds from food crops, milk and milk products in Kenya, Tanzania and South Africa. The results from this study implied that those who owned the crop also had control or decision-making power over the asset or the income it produced. Moreover, the ability of individuals to bargain within the household over miraa activities (e.g., which price to sell the produce and how to use the proceeds from the produce) was highly gendered, with men dominating all decisions. This was reflected in the fact that among smallholder farmers in Eastern Kenya, crops are highly gendered, with commercial crops such as coffee, tea and miraa typically viewed as men’s [5,8,16,18,23]. These findings are not dissimilar to [20], who argued that men dominated all decisions in the coffee value chain in Uganda, while [24] contended that men preponderantly owned cocoa in Ghana and therefore made almost all the decisions pertaining to crop production and marketing domains.

Furthermore, in various contexts, “cash” crops differ from “food” crops because social norms dictate that men own and dominate decision-making processes in money-generating agricultural enterprises [16,18,23].

4.3. Division of Labor by Gender Categories in Miraa Production Activities

Miraa activities were performed by all the gender categories. However, overall, young men aged 18 to 35 years performed all the activities in all the three counties with significant differences (p < 0.05) except for severe pruning. These activities included (a) planting, (b) weeding, (c) normal pruning, (d) pest control, (e) manure, fertilizer and foliar application, (f) harvesting, and (g) sorting. Men above 35 years also performed these activities but to a lesser extent. However, the only activity men above 35 years performed with significant differences (p < 0.05) was severe pruning, as shown in

Table 2. Division of labor by gender categories in miraa production activities.

Activities	Gender Category	Embu (%)	Meru (%)	Tharaka Nithi (%)	Overall (%)
Planting		n = 419	n = 1023	n = 65	n = 1507
	Boys 10 to 17	0.0	3.1	1.5	2.2
	Men 18 to 35	36.3	53.8	24.6	47.6
	Men above 35	32.9	25.9	52.3	29.0
	Girls 10 to 17	0.5	0.6	1.5	0.6
	Women 18 to 35	16.5	12.7	12.3	13.7
	Women above 35	13.8	3.9	7.7	6.8
	Chi-square	181.0	1277.8	73.7	1523.3
	p-value	<0.001 ***	<0.001 ***	<0.001 ***	<0.001 ***
Weeding		n = 463	n = 1146	n = 99	n = 1708
	Boys 10 to 17	0.2	3.2	2.0	2.3
	Men 18 to 35	35.6	36.8	25.3	35.8
	Men above 35	30.0	16.4	33.3	21.1
	Girls 10 to 17	0.6	3.2	2.0	2.5
	Women 18 to 35	17.3	27.9	17.2	24.4
	Women above 35	16.2	12.4	20.2	13.9
	Chi-square	296.1	627.5	47.1	883.0
	p-value	<0.001 ***	<0.001 ***	<0.001 ***	<0.001 ***
Severe pruning		n = 255	n = 58	n = 10	n = 323
	Boys 10 to 17	0.0	3.4	10.0	0.9
	Men 18 to 35	39.2	41.4	10.0	38.7
	Men above 35	43.9	44.8	40.0	44.0
	Girls 10 to 17	0.0	0.0	10.0	0.3
	Women 18 to 35	9.0	6.9	20.0	9.0
	Women above 35	7.8	3.4	10.0	7.1
	Chi-square	113.2	52.0	4.4	367.4
	p-value	<0.001 ***	<0.001 ***	0.493	<0.001 ***
Normal pruning		n = 388	n = 876	n = 73	n = 1337
	Boys 10 to 17	0.0	1.5	1.4	1.0
	Men 18 to 35	38.4	51.7	30.1	46.7
	Men above 35	38.1	38.5	41.1	38.5
	Girls 10 to 17	0.3	0.8	1.4	0.7
	Women 18 to 35	12.4	5.7	12.3	8.0
	Women above 35	10.8	1.8	13.7	5.1
	Chi-square	232.8	1327.8	55.8	1674.0
	p-value	<0.001 ***	<0.001 ***	<0.001 ***	<0.001 ***
Pest control		n = 373	n = 491	n = 70	n = 934
	Boys 10 to 17	0.0	1.0	0.0	0.5
	Men 18 to 35	41.8	55.4	38.6	48.7
	Men above 35	42.4	29.3	44.3	35.7
	Women 10 to 17	0.5	0.4	0.0	0.4
	Girls 18 to 35	8.3	10.4	5.7	9.2
	Women above 35	7.0	3.5	11.4	5.5
	Chi-square	309.9	702.1	31.1	1172.8
	p-value	<0.001 ***	<0.001 ***	<0.001 ***	<0.001 ***
Manure application		n = 415	n = 1074	n = 65	n = 1554
	Boys 10 to 17	0.0	3.8	1.5	2.7
	Men 18 to 35	31.6	35.4	33.8	34.3
	Men above 35	31.8	20.3	36.9	24.1
	Girls 10 to 17	0.5	3.9	1.5	2.9
	Women 18 to 35	18.8	24.1	15.4	22.3
	Women above 35	17.3	12.5	10.8	13.7
	Chi-square	137.5	492.5	46.8	737.6
	p-value	<0.001 ***	<0.001 ***	<0.001 ***	<0.001 ***
Fertilizer application		n = 49	n = 252	n = 37	n = 338
	Boys 10 to 17	0.0	2.0	2.7	1.8
	Men 18 to 35	34.7	43.3	29.7	40.5
	Men above 35	20.4	19.4	35.1	21.3
	Girls 10 to 17	0.0	1.2	0.0	0.9
	Women 18 to 35	24.5	27.4	16.2	25.7
	Women above 35	20.4	6.7	16.2	9.8
	Chi-square	2.7	209.1	12.1	241.7
	p-value	0.445	<0.001 ***	0.017 *	<0.001 ***
Foliar application		n = 37	n = 138	n = 44	n = 219
	Boys 10 to 17	0.0	0.7	0.0	0.5
	Men 18 to 35	43.2	61.6	38.6	53.9
	Men above 35	29.7	29.7	36.4	31.1
	Girls 10 to 17	0.0	0.7	0.0	0.5
	Women 18 to 35	10.8	5.8	4.5	6.4
	Women above 35	16.2	1.4	20.5	7.8
	Chi-square	9.4	252.3	13.3	302.5
	p-value	0.025 *	<0.001 ***	0.004 **	<0.001 ***
Harvesting		n = 554	n = 1093	n = 100	n = 1747
	Boys 10 to 17	0.0	4.6	1.0	2.9
	Men 18 to 35	33.2	57.7	35.0	48.7
	Men above 35	29.4	20.2	37.0	24.1
	Girls 10 to 17	0.2	2.0	1.0	1.4
	Women 18 to 35	20.4	13.2	8.0	15.2
	Women above 35	16.8	2.3	18.0	7.8
	Chi-square	184.7	1494.4	79.0	1658.7
	p-value	<0.001 ***	<0.001 ***	<0.001 ***	<0.001 ***
Sorting		n = 448	n = 1025	n = 102	n = 1575
	Boys 10 to 17	0.4	3.3	0.0	2.3
	Men 18 to 35	41.1	58.0	36.3	51.8
	Men above 35	27.2	20.8	34.3	23.5
	Girls 10 to 17	0.2	2.5	0.0	1.7
	Women 18 to 35	19.4	13.2	11.8	14.9
	Women above 35	11.6	2.1	17.6	5.8
	Chi-square	342.4	1433.2	18.1	1731.7
	p-value	<0.001 ***	<0.001 ***	<0.001***	<0.001 ***

NB/***—significant at 0.1%, **—at 1% & *—at 5%. Source: Miraa household survey 2019.

. Unfortunately, young men performed almost all these activities, yet this was also the age bracket of school-/college-going students. Indeed, the young men performed these activities in exchange for cash. Consequently, these young men would rather go to work in the miraa farms instead of going to school [2]. It is therefore not surprising that according to key informants and focus group discussions, the region experienced high school dropouts, which negatively affected education standards. This finding was further supported by [44,45], who argued that peer pressure and easy money from the crop’s paid labor forced young men to drop out of school to perform the various miraa activities. These results are similar to many studies that have shown men performing these activities in cash crop production [20,22,24].

The only activity performed by young women (18 to 35 years) to some noticeable extent was weeding at 46%. This implied that miraa was a men’s crop where activities were mostly performed by men.

4.4. Access to Extension Services by Gender

The study revealed that only a minority (2%) accessed extension services. These were 1% from Meru, 5% from Embu and none from Tharaka Nithi. Out of those that received extension services, overall, a whopping 86% were men compared with only 14% women, as shown in Figure 5. These results implied that women had less access to extension services compared to men. This finding was in agreement with various studies that have shown women having less access to extension as well as other resources such as credit and land than men [5,8,32,33]. Women have less access to extension partly because extension agents tend to approach the progressive farmers with resources such as land, labor and capital and who might have had a history of adopting agricultural technologies, innovations and management practices. This is usually because of the belief that the spillover effects will eventually reach the other farmers [4,5,33]. These results also implied that very few farmers had accessed extension service, yet many studies have shown the vital role this institutional support plays in the adoption of agricultural technologies and management practices [30,31,32,46]. Extension services provide various platforms through which farmers learn and adopt noble technologies, innovations and management practices. These platforms include field days, on-farm demonstrations, agricultural shows, trainings and farm visits [30,34,46]. Furthermore, [30] argued that farmers with regular interactions with the extension services were more likely to adopt new agricultural technologies than those with fewer interactions. This argument was further supported by [39,46], who asserted that regular exchanges with extension increased technology adoption by the farmers. In Kenya, the government extension officers are the main source of agricultural information as they act as the link between farmers and agricultural research scientists who develop technologies, innovations and management practices [29,31,46]. This fact explains why a huge 98% of miraa farmers had never received extension services because, previously, the crop was not scheduled [2]. Consequently, no formal extension services were offered by either the government or other development partners.

5. Conclusions

This paper contributes to the understanding of gender inequity in agricultural production and marketing. The study confirms the fact that women have less access to agricultural resources such as land and extension services than men [3,4,5,6]. Consequently, this has important implications for the adoption of agricultural technologies, innovations and management practices for improved production and marketing. Furthermore, men dominated all decisions related to the various crop domains, implying unequal power relations in the household. This finding is not unusual because previous studies by [15,16,20,23] have shown that, in a number of contexts, social norms dictate that men dominate decision-making processes for cash crops production and marketing. The study has also confirmed that men, and especially the youths, were more involved in miraa production and marketing activities compared with women. Therefore, a growing body of literature shows men being more involved in cash crop production and marketing activities than women [18,22,24,28].

We also know that, previously, no formal research had been conducted on miraa since the crop was not scheduled in Kenya. Consequently, the study recommends that since miraa appears to be a men-dominated crop, research scientists should design gender-responsive technologies, innovations and management practices that are tailor made to meet the needs and concerns of men. Moreover, gender-sensitive policies should be developed and implemented to ensure gender equity in the access to and control of resources and benefits from the miraa enterprise. Furthermore, the government needs to come up with policies and incentives that encourage young men to remain in schools and colleges instead of dropping out to perform the various miraa activities.