PROTOCOL: The Effects of Training, Innovation and New Technology on African Smallholder Farmers' Wealth and Food Security: A Systematic Review
Bibliographic record
Abstract
A large proportion of the world's poor live in rural areas, dependent on subsistence farming for their survival (FAO, 2011). Smallholder farmers have been credited with providing up to 80 per cent of food in developing countries (IFAD, 2012) and have the potential to feed themselves and also supply urban markets. Vietnam's smallholder farmers are often credited, for example, with transforming the country from a net-importer of food, to a major exporter (ibid). Whilst definitions of smallholder farming vary, the concept usually incorporates a number of key elements (Morton, 2007): farms on which labour is predominantly family ('family farms') (IFAD, 2009); farmers and farms that are resource poor (Nagayets 2005; Dixon et al., 2003); farms of a particular size, most commonly two hectares (Nagayets, 2005; Hazell et al. 2010; Wiggins et al., 2010; World Bank 2003; IFAD, 2011a); and farms which are predominantly subsistence, but might also include a mix of commercial and subsistence activities (Narayan and Gulati, 2002). Smallholder farming is of particular significance to Africa for a number of reasons. Africa's economy is dominated by agriculture (Massett et al., 2011) and the vast majority of farmers in Africa are smallholders (World Bank, 2007). Smallholder farmers contribute significantly to food security on the continent, for example, in sub-Saharan African smallholder farmers contribute up to 80 per cent of the food supply (IFAD, 2011b). Smallholder farmers also include many of the continent's poorest and most marginalised people (World Bank, 2007). In southern Africa in particular, large numbers of women and girls rely on smallholder farming, and it provides a survival strategy for many of the continent's young people, many of whom are orphans and head of their households. Furthermore, supporting Africa's development is a priority within the G8, and working towards increasing food security in the region is high on the agendas of the majority of international donors, including the Canadian Foreign Affairs, Trade and Development agency (DFATD), who have commissioned this review. Given both the importance of smallholder farming in Africa and its potential to contribute to the food security of so many, it is not surprising that considerable efforts are being invested in its success. Both national and international agencies are investing in improving the productivity of smallholder farming, including the International Fund for Agricultural Development (IFAD) and the Canadian Foreign Affairs, Trade and Development agency (DFATD). Additionally, in 2009, the G8's L'Aquila initiative pledged $22 billion USD for agriculture in developing countries (G8, 2009). In 2012, IFAD launched the Adaptation for Small Holder Agriculture Programme (www.ifad.org/climate/asap/). On a national level, heads of state in Africa are increasingly stressing the need for support for smallholder farmers. For instance, South African President Jacob Zuma emphasized the need for support of smallholder famers in his 2013 State of the Nation Address (RSA, 2013). Parallel efforts are being invested in agricultural research, such as impact evaluations and systematic reviews, to assess the effectiveness of these agricultural programmes. Agricultural productivity of particularly starchy cereals is important since this category of crop accounts for two thirds of the region's energy intake as well as 70 per cent of the income of the extremely poor population living in Africa (AGRA, 2013). The 2013 Africa agriculture report issued by AGRA (ibid) identifies the general production trend for Africa as somewhat erratic, but with most countries reporting a steady increase in production. According to the report, Kenya, Ghana, Mali, Tanzania, Uganda, Zambia, and possibly Mozambique have all reported steady increases in agricultural production (AGRA, 2013, 21). Areas that have experienced civil unrest, political instability, or mismanagement of the macroeconomics of the country in the last decade have seen a decrease in agricultural productivity; included among these are Sierra Leone and Liberia (AGRA, 2013, 21). Technologies typically used to increase agricultural productivity in the region include the "increased use of agricultural inputs, modern farming techniques, and reduced market inefficiencies" (AGRA, 2013, 20). However, a much larger array of factors come to bear on agricultural productivity. Political, technological, physical environmental, and micro- and macroeconomic factors related to each country play a pivotal role in shaping the region's agricultural productivity. World prices of inputs and outputs, and international trade policies also influence the agricultural productivity within countries (AGRA, 2013). As such, any technology addressing any one of these aspects may be expected to have an influence on the food security or income of smallholder farmers in Africa. Examples of specific technologies include treadle pump irrigation technology (Adeoti et al., 2009); biofortification and health information (de Brauw et al., 2013); and adopting an export crop and marketing techniques (Ashraf et al., 2008). In the context of this considerable and growing emphasis on smallholder farming, there is a need to understand the relative effectiveness of the different interventions targeting smallholder agriculture in achieving various outcomes. Today, there are a multitude of agricultural interventions in place across Africa (Sapa, 2009). The focus of these interventions has shifted as understanding of the relationship between agriculture and poverty has developed (Massett et al., 2011). Early interventions focused on increasing productivity to meet a perceived lack of food. With the realisation that undernourishment persists alongside high levels of production (Reutlinger & Pellekaan, 1986), structural issues came to the fore and the concept of food security was introduced (Sen, 1981). Interventions shifted towards income generation, access to markets and the production of more nutritious and calorific foods. Two groups of interventions have specifically sought to increase food security and reduce poverty by training farmers and / or encouraging them to adopt agricultural innovations and new technologies. Interventions that are categorised as innovations emphasise the introduction of a 'new' farming method, product, or service. An example of this kind of intervention is the introduction of home gardens to increase the intake of vitamin A. A new technology intervention places emphasis on the introduction of a previously unfamiliar agricultural input. This could be a different piece of equipment or genetically modified seeds. Training interventions would place emphasis on providing some kind of training to farmers. The content of such training may not necessarily be new to farmers, but rather previously unemployed. However, we acknowledge that some training interventions will centre on the introduction of new technology and/or innovation. For instance, an example of this kind of study is de Brauw et al.'s evaluation of biofortification and a health information intervention on the food security of smallholder farmers (2013). A recent systematic map of the evidence of interventions targeting smallholder farmers (Stewart et al., 2013) found that there were gaps in the African evidence base, including: 1) a lack of systematic reviews addressing various interventions' impacts on the financial wealth of smallholder farmers, and 2) a lack of assessments of the impact of interventions on smallholders' food security. The scope of the present review has been influenced by these gaps as well as by consultation with our advisory group and funders. Training interventions for farmers vary considerably. Some interventions focus directly on teaching farmers, using top-down 'train and visit' approaches (Hume, 1991). Such training interventions are also often packaged as 'extension services', a broad term for programmes which aim to "support and facilitate people engaged in agricultural production to solve problems and to obtain information, skills and technologies" (Anderson, 2007:6). Although traditionally considered as a top-down approach to training, extension services have over time become more participatory in nature (Waddington et al., in press). Specifically 'farmer field schools', which may be one component of broader agricultural extension services, use a more bottom-up approach to training and knowledge transfer (Waddington et al., 2009). Farmer field schools are participatory, empowering and experiential in nature and draw on problems and priorities identified by farmers themselves, rather than those determined by outsiders (Waddington et al., in press). Initially developed to tackle an over-reliance on pesticides, field schools have now been implemented across over 80 countries (van den Berg, 2004). Another important aspect of these interventions relates to the training objectives: there is a clear distinction in the literature between courses that are directed to improve agricultural practices and increase yields (for example, training on natural resource management; integrated pest management; conservation agriculture), and those which focus on aspects of farm management (for example, social organisation; management; institutional development). Perhaps the most straightforward way of considering the range of training interventions available is to consider three facets of the interventions: how experiential or participatory the training is; the duration of the training; and the content of the training – see Table 1. An example of an evaluation of this kind of intervention is Anyango et al. (2010), who evaluated a five-year project in Kenya aimed at improving the income and food security of smallholder farmers through a number of training interventions, including introducing new cultivars to the farmers and training them through farmer field schools, as well as providing training on marketing skills, amongst other things. Ashraf et al. (2008), on the other hand, evaluated agricultural interventions that worked with pre-existing farmer self-help groups and provided farmers with information and short orientation-sessions about switching to export crops and offered in-kind loans and facilitated transactions with exporters. Agricultural innovation interventions aim to facilitate adoption of new technologies including: fertilisers; new crops (including genetic modification, Hall, 2010); more nutritious crops; and new industries (Ton et al., 2013); and incorporate these technical developments with new systems (Adjei-Nsiah et al., 2008). Sunding and Zilberman (2001) provide a useful framework of these interventions, in terms of mechanical, biological, chemical, agronomic, biotechnological, process and product innovations – see Table 2. The literature includes a number of examples of evaluations of these innovations and new technologies. For example, Bennett et al. (2003) evaluated the impact of a biological innovation - the introduction of insect-tolerant Bt cotton in South Africa. Panin (1995), on the other hand, assessed a mechanical innovation, evaluating the effectiveness of mechanisation (the introduction of tractor farm technology) on factors such as smallholder farming yield, income and resource utilisation in Botswana. The intended outcomes of these innovations are wide-ranging: from investment (in seed, land, livestock, or labour), to increased yields, productivity, income generation, health, nutrition, food security, and poverty reduction (World Bank, 2007). In particular, there is increasing emphasis amongst international donors on the 'end-point' outcomes of food security and poverty reduction. Smallholder farming has long been credited with the potential to end food insecurity (Sen, 1981; Reutlinger & Pellekaan, 1986). The argument is that it is both an effective subsistence strategy and a potential income-generating activity enabling poor farmers to purchase additional food (IFAD, 2012). Furthermore, it is thought to benefit those segments of the population that are most vulnerable to the effects of poverty, namely women, children, and youth (World Bank, 2007). Whilst there is demand for evidence of the effectiveness of training and innovation and new technology on the financial wealth and food security of smallholder farmers, the mechanisms by which these interventions work involve several intermediate steps. These are multi-faceted, and are dependent on factors such as the environmental context, political stability and economic climate, as well as more direct elements such as farmers' scope to change their practice and increase their productivity. As Figure 1 illustrates, there are key intermediate outcomes on the pathway to increased food security and financial wealth, specifically: investment, knowledge transfer, adoption of innovation, diffusion of innovation, and increase in yield and productivity. An initial causal pathway We will interpret yield broadly. We will include studies that refer to the extent of food production, the growth rate of crops, crop output, as well as crop losses (Stewart et al., 2013). These categories may include studies of the impact of interventions on: the improvement or conservation of soil fertility, of the quality of output, disease resistance or reduction, and food storage conditions (Stewart et al., 2013). Productivity is defined by Stewart and colleagues (2013) in the systematic map of African evidence as "the efficiency of production". This includes various aspects, such as "measures of technical efficiency, better resource management, reduced input costs, impacts on labour requirements, 'stronger' systems, and 'better' utilisation of available resources" (Stewart et al., 2013). The importance of smallholder farming in Africa, and the multitude of interventions to increase the wealth and food security of smallholder farmers has been outlined already. We initiated discussions with government agencies and non-governmental organisations supporting these farmers to identify their priorities for evidence to inform their programmes. Having consulted widely on the range of interventions implemented and their intended outcomes, we identified the need for clear evidence on the effectiveness of innovation and / or training interventions, and their impacts on both poverty reduction and food security. An initial scoping review to ascertain the extent to which published reviews had already answered these questions highlighted how more focussed reviews provided evidence on one intervention, but did not answer the question that donors and NGOs raised around which intervention to invest in and why. (See Box 1 and Appendix 1 for more on this preliminary scoping work.) A total of 21 systematic reviews of relevance to smallholder farming in Africa were found. Of these, 18 reviews were complete, two protocols were published (Loevinsohn & Sumbug 2012; Knox et al., 2013) and a third protocol is currently under peer review (Dorward et al. 2013). The protocols both focus on agricultural infrastructure (Loevinsohn & Sumbug, 2012; Knox et al., 2013), whilst Dorward and colleagues' review will focus on agricultural finance. The scopes of the 18 completed reviews were categorised into four broad intervention categories: training, innovation and new technology, infrastructure and finance. Only one of the 18 focused on training, specifically farmer field schools (Waddington et al. 2013). Reflecting the search for new and better ways of farming, we found nine systematic reviews that evaluated the impacts of innovation and new technology (Bayala et al., 2012; Bennet & Franzel, 2009; Berti et al., 2004; Hall et al., 2012; IOB 2011; Girad et al., 2012; Gunaratna et al., 2010; Masset et al., 2011; Rusinamhodzi et al., 2011). These included evaluations of the effectiveness of conservation agriculture in general (Bayala et al., 2012, Bennet & Franzel, 2009, Rusinamhodzi et al., 2011), as well as specific conservation agriculture interventions, including: parkland trees associated with crops (Bayala et al., 2012), coppicing trees (Bayala et al., 2012), green manure (Bayala et al., 2012), mulching (Bayala et al., 2012), crop rotation and intercropping (Bayala et al., 2012; Rusinamhodzi et al., 2011), traditional soil and water conservation (Bayala et al., 2012), tillage management (Rusinamhodzi et al., 2011), and residue retention (Rusinamhodzi et al., 2011). These systematic reviews also considered the impacts of organic agriculture (Bennet & Franzel, 2009) and genetically modified crops (Hall et al. 2012), as well as specific interventions aimed at increasing nutritional status of households, such as home gardening (Berti et al., 2004; Girad et al. 2012; Masset et al., 2011), cash cropping (Berti et al., 2004), irrigation (Berti et al. 2004), and biofortification (Masset et al., 2011; Gunaratna et al. 2010). The impact of interventions to increase food production have been reviewed (IOB, 2011), including particular forms of agriculture, specifically livestock (Berti et al., 2004), and in particular poultry development (Masset et al., 2011), animal husbandry (Masset et al. 2011) and dairy development (Masset et al., 2011); fish ponds (Masset et al., 2011), aqua culture (Masset et al. 2011), and mixed garden and livestock (Berti et al., 2004). Five completed reviews have considered finance for farmers, specifically: index insurance (Cole et al., 2012), micro-credit (Duvendack et al., 2011; Stewart et al., 2010, 2012), micro-savings (Stewart et al., 2010, 2012), micro-leasing (Stewart et al., 2012), and agricultural investment grants (Ton et al., 2013). Lastly, three systematic reviews focused on the impact of agricultural infrastructure interventions, specifically agricultural interventions and food security (IOB, 2011); infrastructural investments in roads, electricity and irrigation (Knox et al., 2013); and land property rights (Hall et al., 2012). Despite the somewhat extensive literature base outlined in Box 1, Stewart and colleagues (2013) found that there were three gaps in the African evidence base, two of which will be addressed by this review, namely the lack of systematic reviews addressing various interventions' impacts on 1) the financial wealth of smallholder farmers, and 2) on their food security. Given the potential for African smallholder farmers to contribute to the food security across the region, coupled with the increasing investment in the industry, there is a need for evidence as to which interventions are most effective. The wide range of options facing policy-makers and practitioners and the need to focus the limited resources available increases the importance of this review. Our objectives in conducting this Campbell systematic review are to: In doing so, we will provide valuable information to decision-makers, not in the least being DFATD who have commissioned this work. To be included in this review, a study must use an experimental or quasi-experimental design. Eligible designs include those in which the authors use a control or comparison group and in which one of the following is true: To be included a study must have: For this review, the control or comparison conditions in these studies may include farmers receiving no treatment, treatment as usual, or an alternative treatment. No restriction will be placed on duration of follow up. Studies for which the impacts within Africa cannot be isolated, will be excluded from the review. Given our focus on the end impacts of the interventions (that is, financial wealth and food security), studies for the review must include a minimum follow-up period of at least 6 months between receipt of intervention and measurement of these end impacts. Shorter follow-up may produce misleading results. For example, an intervention that introduces a new breed of cattle, could lead to increased access to meat in the diet in the immediate term, but it would be misleading to label the consumption of these cattle as an increase in food security.1 To be included, a study must include African farmers of smallholder farms. Farmers include both men and women who either own their farms or farm land owned by others. We will not limit by age as we acknowledge that there are large numbers of child-headed households in Africa, and it is feasible that smallholder farmers will be very young. For the purposes of sub-group analysis later in our review, we will define young farmers as those under the age of 20. Smallholder farms can be defined in a number of ways. Whilst size of farm is often cited – most commonly less than 2 hectares – the productivity of the land can mean that in some countries much larger farms are considered to be 'smallholdings'. In Tanzania for example, farms of up to 50 hectares have been classified as smallholder farms. The nature of the land, the crops grown and the types of livestock kept all shape the resource-level of farms. Farmers may own their land, although this is often not the case. smallholder farms are usually to be farms can also be This review will a of smallholder farms as the of land, labour and not currently a and family Table provides a framework for how we will our of smallholder farms. farmers, young farmers and have been highlighted by our advisory group as key of within this review. three groups will be included within the review, and study This review on two broad intervention Studies will be included in the review meet at least one of the following Interventions that not smallholder farmers specifically will be Studies will not be excluded by duration or of This review on two outcomes financial wealth and food security. We define financial wealth as any of finance or that a for example, income from food or from not to food Specifically we will on the following for financial Bennet et al. is an example of a study in which the economic impact of genetically modified cotton on South African smallholders' is Studies that not consider one of these outcomes will be excluded from the review. According to the of the World food security all people, at all have physical and economic access to nutritious food to meet their and food for an (FAO, 2013). food security is the of food and access to We consider the of food security in our review. on this our review into and We will on the following specific for food We have also included an which will consider any which not under those outcomes considered in this review will Studies will not be excluded from the review on the of will be in and for We will include studies since Both the for impact of these interventions, and the nature of the interventions have developed significantly since et al., 2003; 2009) it that we will identify any literature to this We will search for published since and on study any in a study published was to the study will be In to identify the literature for this review as as we have our search strategy to include both general and with both broad search terms and more We have from two search from the Campbell and the in the of these impact evaluations Africa African African the of the Africa IFAD evaluation evaluations The and The key in our review are We have some that four in our may be and some the concept is to search for search the large numbers of search terms and is also to for (the country a study is is usually reported in the We will search for three in these new the for smallholder impact evaluation and the interventions of in the following farm impact evaluation We have developed search in to we all search terms for the we Appendix However, some use search long of terms to The will be to each of the as we will search within the and this is not included, we will search the We will also terms We will search the of all impact In we will the of a published scoping map of agricultural innovation in sub-Saharan and A 2013) Agricultural in Africa and South A studies from key We will to key These will include of our project advisory group and authors of reviews, as in Appendix 2. Two will assess the the and each will from included will be by and a third will be available to any used in the considered to this review include and a range of designs that These include natural factors and the or the (Waddington et al., 2012). Of those study designs in which to intervention or control is we will include studies that have a comparison group with and impact using Only studies that have a group will be included in this review. studies must at the or Ashraf and colleagues study is an example of a which we including in this review. and assess impacts at one across two treatment groups of which the intervention, and one of which also and a control In example, and colleagues assess the impact of three programmes using and and of the programmes using used to to their intervention and control We will use a with information that a study is to be included or excluded for this review Appendix We will from the included studies as outlined in the including on the the of intervention, of intervention, outcomes and how were and We will use the included in Appendix to to to including and of for both control and intervention at each time of and will be on and additional for included studies will be in This will facilitate of
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
| gpt | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.046 | 0.076 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.015 | 0.013 |
| Bibliometrics | 0.012 | 0.011 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.093 | 0.008 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedLabeled directly by 2 models reading the full record.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".