David I. Gray

Agricultural Science in the Wild: A Social Network Analysis of Farmer Knowledge Exchange

Responding to demands for transformed farming practices requires new forms of knowledge. Given their scale and complexity, agricultural problems can no longer be solved by linear transfers in which technology developed by specialists passes to farmers by way of extension intermediaries. Recent research on alternative approaches has focused on the innovation systems formed by interactions between heterogeneous actors. Rather than linear transfer, systems theory highlights network facilitation as a specialized function. This paper contributes to our understanding of such facilitation by investigating the networks in which farmers discuss science. We report findings based on the study of a pastoral farming experiment collaboratively undertaken by a group of 17 farmers and five scientists. Analysis of prior contact and alter sharing between the group’s members indicates strongly tied and decentralized networks. Farmer knowledge exchanges about the experiment have been investigated using a mix of quantitative and qualitative methods. Network surveys identified who the farmers contacted for knowledge before the study began and who they had talked to about the experiment by 18 months later. Open-ended interviews collected farmer statements about their most valuable contacts and these statements have been thematically analysed. The network analysis shows that farmers talked about the experiment with 192 people, most of whom were fellow farmers. Farmers with densely tied and occupationally homogeneous contacts grew their networks more than did farmers with contacts that are loosely tied and diverse. Thematic analysis reveals three general principles: farmers value knowledge delivered by persons rather than roles, privilege farming experience, and develop knowledge with empiricist rather than rationalist techniques. Taken together, these findings suggest that farmers deliberate about science in intensive and durable networks that have significant implications for theorizing agricultural innovation. The paper thus concludes by considering the findings’ significance for current efforts to rethink agricultural extension.

An application of SSM in the on‐farm labour situation in the New Zealand dairy industry

The on-farm labour situation is a matter of concern to the New Zealand dairy industry. Structural and demographic changes in the industry have contributed to a situation in which employers are unable to attract or retain the number and type of employees they seek. Perceptions of the issue, the nature and extent of the problem, and the likely means to address it vary among the people involved. Although used to a limited extent in New Zealand, soft systems methodology (SSM) was developed to deal with complex problem situations that are ill structured and defined differently by people in the situation. SSM was used in the on-farm labour situation in the dairy industry to structure the problem situation and to provide a number of relevant systems models for an industry group to debate and learn about the situation. This paper reports on the process and outcomes of the inquiry to date. Copyright

Developing Sustainable Farmer-led Extension Groups: Lessons from a Bangladeshi Case Study

Abstract The limited effectiveness and fiscal unsustainability of professional-led public sector extension systems in developing countries have aroused considerable interest in Farmer-led Extension (FLE) approaches in the recent decades. A key challenge facing these initiatives is a lack of sustainability of the farmer groups developed through project or programme assistance. This not only makes FLE initiatives costly, but also creates dependency among farmers. Despite this, the knowledge of what can make externally-initiated FLE groups sustainable is scant and largely anecdotal. In this paper we provide an empirically-drawn and theoretically-informed framework to fill this knowledge gap. The framework is based on a comparative case study of six non-sustained and four sustained FLE groups initiated through an innovative extension reform project in Bangladesh and a comparison of the results with the theories of collective action. We have identified four sets of inter-related factors called ‘capitals’ affecting group sustainability: ‘financial capital’ accumulated through group-based microcredit activities, an effective governance mechanism called ‘institutional capital’ devised by the members themselves, good quality group leaders and facilitators called ‘human capital’, and past relations of exchange, reciprocity, trust and respect called ‘social capital’ among members and between members and professional facilitators. While microcredit can benefit sustainability, it suits women rather than men farmers. Good quality leaders and facilitators are not only technically competent, but also fair, innovative, tenacious, self-sacrificing, trustworthy, honest, and sincere. All forms of social capital are not useful for group sustainability and social capital can make a positive impact only when the other types of capital—human and institutional—are present within a group. To improve group sustainability, FLE programmes should take a holistic approach and address the four kinds of capitals proposed in this paper. Key strategies may include: combining extension (information or advisory functions) with economic activities but avoiding a one-size-fits-all solution, recruiting group leaders and facilitators by going beyond technical considerations (e.g. taking into account the personality traits identified in this study), adopting a bottom-up approach in devising group rules and regulations, and taking into account both the positive and negative aspects of social capital. The originality of our research lies in the explanatory framework that we provide in this paper. Our study also contributes to the intellectual debates on social capital by exhibiting the dual roles that social capital plays and its complex interrelationships with other forms of capital.

Using educational theory and research to refine agricultural extension: affordances and barriers for farmers’ learning and practice change

ABSTRACT Purpose: To examine the factors that support and hinder farmers’ learning and to investigate the impact of an innovative learning program on farmers’ practice change. Design/methodology/approach: Individual interviews and focus group discussions were held with 24 farmers over 20 months. Observations were made of these farmers as they participated with eight agricultural and social scientists in a range of innovative experiences to learn about chicory and plantain establishment and management. These learning experiences were designed around evidence-informed educational pedagogies. Data sets were analyzed using NVivo to determine common themes of affordances and barriers to learning and actual practice changes. Findings: The affordances for learning and practice change include belonging to a learning community, enhancing self-efficacy, engaging with scientists, seeing relative advantage, reinforcing and validating learning, supporting system’s integration and developing an identity as learners. Barriers to learning and practice change include issues of: trialability, complexity, compatibility and risk. Practical implications: The importance of basing new models of extension around evidence-informed pedagogies known through educational research to promote learning and practice change. Theoretical implications: Sociocultural theory and self-efficacy theories of learning are critical to the success of effective agricultural extension programs. Originality: To date, little empirical research about the affordances and barriers for pastoral farmers’ learning has been based on contemporary educational research.

Using a ‘network of practice’ approach to match grazing decision-support system design with farmer practice

The use of pasture measurement tools and decision-support systems (DSS) for grazing management remains limited on New Zealand dairy farms. However, effective use of such tools provides opportunities to optimise pasture grown and pasture harvested. The present study used a mixed-method qualitative research approach to investigate pasture data and technology use for grazing decision making, through interviews and workshops with farmers, rural professionals, commercial software developers and a panel of farming-system specialists. Results suggest that different drivers for use of pasture data and DSS exist between farm owner-operators and corporate farming operations. Larger multi-farm businesses are collecting pasture data for use at a governance level as well as for operational decision making. Understanding the seasonal influences on decision making, and incorporating major regional differences such as pasture growth rates and impact of irrigation use, provides guidance on how to better match DSS to farmer practice. Study participants identified a need for greater integration of software tools to connect in-paddock data capture with real-time feedback. Also, data integration is needed to enable the transfer of information across different platforms for corporate farming operations. Rural professionals used commercial grazing DSS products, but also constructed their own spreadsheets to enable functionality and reporting not available in the DSS products. The research highlighted a need for farmer-orientated tools that are flexible to incorporate differences in user goals, decision making, mobility and desired outputs. Key attributes identified were seasonality, simplicity, ability to trial before purchase, flexibility in application, scalability to match farm systems, and integration with other tools. Future research and design of DSS tools requires a focus on co-creation with farmers, to merge scientific and practical knowledge.

The pros and cons of using FACET for analysing qualitative data

In this paper, the FACET approach to analysing qualitative data for the purposes of interface evaluation is described. The reliability and validity issues that arise from basing an interface evaluation on qualitative data are discussed. The practicability of carrying out an interface evaluation using FACET is then considered with particular reference to the cost, time and expertise required.

The role of functional prototyping in model validation

Summary form only given. Within the KADS framework, a model of domain expertise is built prior to system implementation. Before making important design decisions, it is necessary to check that this model correctly represents the domain and its problem solving aspects. In this paper, a framework which employs functional prototyping for validating a model of expertise is described. Before building the prototype, an object-oriented knowledge representation model is developed based on the model of expertise. This knowledge representation model provides the structure of the prototype. Since mistakes may be made in the translation from one model to another, the knowledge representation model has to be verified to ensure that it accurately depicts the information in the model of expertise. The functional prototype can then be constructed and verified. Finally, the domain experts can test out the functional prototype to see whether it accurately models the domain. This framework was applied to the summer-autumn management domain. Two important areas were prototyped: feed budgeting and production level analysis.

Lessons for co-innovation in agricultural innovation systems: a multiple case study analysis and a conceptual model

ABSTRACT Purpose: This paper highlights important lessons for co-innovation drawn from three ex-post case study innovation projects implemented within three sub-sectors of the primary industry sector in New Zealand. Design/methodology/approach: The characteristics that fostered co-innovation in each innovation project case study were identified from semi-structured interviews conducted with key stakeholders in each project, iterative discussions to confirm the findings and secondary document analysis. Common themes from the three cases are examined in relation to innovation system structure and function analysis and agricultural innovation system (AIS) literature. This study builds on the literature attempting to overcome methodological challenges in the applied AIS research space. Findings: The findings have implications for co-innovation in practice; that there needs to be network-level capability and legitimacy, an understanding of priorities between actors, and adequate resources, to ensure proposed outcomes are likely to be attained. Practical implications: Practically, project leaders need to ensure they embed an appropriate mix of actors in the research program and they also need to create and encourage room for open and honest dialogue between these actors to develop a shared vision of the future. Theoretical implications: A conceptual model is developed to highlight and simplify lessons that can inform future projects involving co-innovation approaches to create value in the primary industries and AIS more generally. This model is unique to the applied AIS research space and provides new insights on enhancing the potential value of a co-innovation approach. Originality/value: The paper adds to current scholarly debates and provides insight to key actions stakeholders need to take to foster co-innovation processes for successful outcomes in extension.

Using the KADS methodology: expert systems in farm management

Farmer decision making is an important area of farm management research. An expert systems development methodology, KADS, provides a method for analyzing the decision making processes of farmers. The KADS method provides a library of generic task models to guide the knowledge acquisition process. KADS facilitates the differentiation of domain knowledge from procedural knowledge. The authors report on the application of KADS to develop a task model of the decision making processes used by four expert seasonal supply dairy partners over the summer-autumn period.<<ETX>>