Farmers' Participation in Knowledge Circulation and the Promotion of Agroecological Methods in South India

Abstract

In the context of widespread agrarian distress in rural India, finding ways to secure livelihood sustainability of small farmers have become urgent concerns. Agroecological methods (AEMs) are considered by some to be effective in solving structural problems with farmers' production processes engendered by the use of resource-intensive technologies. AEMs generally require extensive participation by farmers for further development through on-farm experimentation and collective learning. This article studies learning through the lens of knowledge circulation between farmers and “experts” in a local innovation system. In particular, it analyzes farmers' participation in knowledge circulation using network data on problem-solving knowledge flows to and from an innovative south Indian village. The findings suggest that farmers' participation was restricted by formal and informal institutions governing the knowledge interactions between the development organizations that promoted AEM and the farmers. Any new ways of working (technological and institutional innovations) are argued to be filtered through the sediments of extant techno-institutional context, leading to the profusion of hybrid forms of technology and organization. However, despite this profusion, or perhaps because of it, epistemological and sociocultural hierarchies continue to operate in avowedly participatory projects organized to promote AEMs based on farmers' “traditional knowledge.”

Keywords:

• indigenous knowledge
• innovation systems
• institutions
• rural development
• social networks

Acknowledgments

This article has been a long time in the making and I have accrued the debt of many people on the way. Initial guidance was provided by my Ph.D. supervisor, Robin Cowan. Additional comments came from Professors Arno Riedl and Alan Kirman. In India, Andy Hall and his colleagues at CRISP helped to set up the fieldwork. People at the NGOs in Hyderabad and Khammam gave their time and encouragement. Residents of Ananthadudem were the most gracious hosts and enthusiastic respondents. I will be forever indebted to them all. Interviews in Telugu were conducted by my friend Poorna Chandra and his contacts. Recent drafts of the article have benefitted from comments by Tommaso Ciarli, Koen Frenken, and two anonymous referees of this journal. Any errors of course remain mine and mine alone.

Notes

1 In India, these include the Indian Council for Agricultural Research (ICAR) and various state agricultural universities.

2 Note here that it is the process of (participatory) learning that makes an innovation pro-poor, that is, helps to sustain livelihoods of smallholders and the landless. Perhaps due to their process focus, agricultural innovation system studies have rarely defined the traits of an innovation (product, technological artefact) itself that make it work in favor of the poor. Older studies on the “benefits” of the green revolution argued that labor-intensive, cost- and risk-reducing technologies are likely to have greater poverty-reducing impact. However, the actual impact of any technologies depends on a number of other local institutional factors (see De Janvry and Sadoulet 2002 for an overview). In the present article, I follow agricultural innovation system scholars in retaining the process focus.

3 Agroecological methods and chemical input-intensive farming can be considered as embedded in two different competing technological paradigms or regimes. A technological paradigm defines the sociocognitive space (design heuristics, mental models) for further technological development in certain directions while excluding others (Dosi 1982). A broader related concept is a technological regime which includes social conventions, economic interests and knowledge infrastructures in addition to the cognitive routines (Malerba and Orsenigo 1997; Geels 2004).

4 I wrote a computer program in C++ to identify cycles in Ananthagudem's knowledge network. The program is in two parts. The first part reduces the knowledge network to nodes that have at least one incoming and one outgoing link (as a node can only be part of a cycle if it has these two links). The second part takes the reduced network as input and does a depth first search on it to find paths (http://www.ics.uci.edu/~eppstein/161/960215.html). All paths that start and end in the same node are cycles. The list and composition of the cycles and the computer program used to find them are available from the author on request.

5 The preponderance of small and marginal landholdings underlines the importance of a pro-poor approach to agricultural sustainability in the village. In villages with larger diversity in landholdings, a niche-based approach may be more appropriate. In such a niche-based approach, for instance, different types of agroecological projects may be designed and implemented for small, mid-sized and large farmers.

6 I used the amount of land owned and numerical strength in the village as measures of economic power to identify the dominant caste in Ananthagudem, as defined by Srinivas (1955). Using other more ambiguous measures such as the level of education, availability of irrigation (most land in Ananthagudem is either rain-fed or bore-well irrigated) and type of house (concrete-slab roof house versus a thatched hut) did not lead to the identification of a dominant caste in Ananthagudem.

7 As the focus of this article is on individual farmers who joined knowledge circuits, I do not perform an in-depth examination of the influence of inter-caste difference on knowledge network structure at the group level. A quick examination of the knowledge network between Ananthagudem residents revealed that, for each caste group, the number of intra-caste knowledge flows is smaller than inter-caste flows. Thus, at the group level, inter-caste difference does not appear to curtail knowledge transfers in the village.

8 It has however been observed that women's interests are not completely independent of those of their households (Razavi 2009, 209). This interdependence may be treated as a rather weak antidote to the gender-bias of the present article.

9 Note that I do not have data on the actual amounts of credit taken by the farmers. These amounts are likely to be higher for pesticide users, simply because of the higher costs of chemical pesticides.

10 Farmers from neighboring villages were sometimes reported as recipients of knowledge from Ananthagudem farmers. I was unable to interview the non-Ananthagudem farmers directly and, thus, they are not the focus of the present study.

11 Of these, 109 links transfer knowledge among Ananthagudem residents. The remaining 17 links transfer knowledge from Ananthagudem farmers to farmers residing in neighboring villages.

12 NGO representatives generally considered farmers who were enthusiastic about the NGO's development projects (and expressed it for instance through the early adoption of and experimentation with sustainable agriculture techniques) as “progressive.”