Issues in Interdisciplinarity 2018-19/Disciplinary Categories and Reframing Deforestation in Guinea



This chapter aims to explore how disciplinary categories can create knowledge borders, leading to a lack of information flow within problem-solving, and how hierarchy among disciplinary categories might lead to the assumption that one certain solution is best.

Disciplinary categories can be applied to a variety of contexts, therefore its precise meaning will naturally vary. As a working definition for this chapter, we understand disciplinary categories to be the bordered fields of academia. For example, mathematics and anthropology are different disciplinary categories. The rigidity and distinction in academic disciplines are intrinsic in its etymology, and these characteristics can lead to disregarding ideas that oppose the accepted canon.

Thus, there is frequently a lack of interaction between different disciplines, especially in policy-making. This prevents us from reaching holistic conclusions when thinking about real-world problems.

To present these issues of disciplinary categorisation in context, we will discuss a case study regarding environmental conservation in Guinea based on the research of Leach and Fairhead. It is a piece of interdisciplinary work exploring the previous absence of communication between disciplines, which led to essential evidence being omitted or misinterpreted, hence forming impartial conclusions.

This chapter will then draw out some key issues regarding disciplinary categories and their interactions in solving issues, in relation to this case study.

Case study


Leach and Fairhead's research took place in Kissidougou; a city located in Guinea's savanna-forest transition zone, which was believed to be undergoing a deforestation crisis.

Administrators and ecologists have maintained that forest cover in Guinea had significantly reduced since 1995.

Pieces of evidence predominantly provided by scientific disciplines, have formed a narrative with limited perspectives. Through extensive mathematical modelling and ecological analysis, policymakers and scientists established the change in the lifestyles and land use of the Kissidougou people, along with population growth, to be the primary reasons of deforestation there. Their research included identification of certain species of trees and other forms of vegetation, that are typically found in the outskirts of forest patches, which led to experts concluding that deforestation had occurred.

Leach and Fairhead challenged this by conducting research alongside existing data encompassing several disciplines such as history, economics, archaeology and anthropology, revealing that the emergence of these variant forest patches was primarily due to intervention by local communities, rather than as a result of deforestation.

The pair spoke to villagers about the history of the Kissidougou and consulted aerial photographs that showed the area's vegetation history. The data not only revealed that there actually was an increase in forest patches, but also proved that the 'rapid population growth causing deforestation' narrative was unfounded. Through analysing broader regional history, anthropological evolution, and archaeology, they found that certain areas had significantly higher rural populations in the 19th century than in 1995. Therefore, when viewing the problem through an interdisciplinary lens, it becomes apparent that the change in population demographics did not result in degradation.

The researchers also included socioeconomic analysis of Kissidougou's population to explain how their activities impacted the vegetation in the area. The villagers had adapted the land to suit changing socioeconomic conditions. They switched from coffee planting to fruit tree planting after the post-colonial period, due to falling prices, and this helped nurture the creation of the forest patches.

It is clear from this case study that a more appropriate solution can be reached considering evidence from other disciplinary categories.

A question to consider is whether the research of academic disciplines that are seemingly more objective or use quantitative data, tend to naturally be more conducive to policy-making. Difficulties arise from assessing the weight of quantitative data from some disciplines against the qualitative of others. The quality of objectivity might give leverage to 'inform policies to address [issues]', compared to other disciplinary categories that may hold other perspectives. By calculating the loss of forest cover mathematically and using these figures to drive a decision to impose policies, we neglect the understanding of important cultural values and livelihoods of locals.

Range of research methodology among academic disciplines
Data is essential in solving real-world problems, but different academic disciplines are anchored to different methods of collecting data. This can lead to differing evidence, and perhaps then a different truth and approach to solving the same issue. Research methodologies include interviews, content analysis, focus groups and language-based analysis to name a few. This becomes a problem in interdisciplinary work, when disciplines disagree about the way that research is being conducted.

However, as exemplified by the case study of deforestation in Kissidougou, by integrating viewpoints from other disciplines in discussions about how research should be conducted for particular issues, it can help highlight weaknesses of the research and factors it may be neglecting in the methodology.

Communication between and perceived hierarchy among disciplines
An issue that should be addressed whilst incorporating multiple disciplines into solving an issue is how they will interact. Academic disciplines can be seen as communities, with ‘distinctive cultural characteristics’ and ‘cultural differences’. Tony Becher, a professor at the University of Sussex, writes that 'disciplinary groups can usefully be regarded as academic tribes, each with their own set of intellectual values and their own patch of cognitive territory'.

Research integrating both quantitative and qualitative methods is becoming increasingly common. A solution to overcoming the borders of academic disciplinary research is employing overall designed systems for mixed-method research, named ‘typologies'. However many of these have been constructed in theoretical terms and are yet to be tested in real-world examples. These typologies draw attention to questions such as: which has priority, the qualitative or quantitative data? Is there more than one data strand? Are the types of data from each discipline collected simultaneously or sequentially?

It is often the case that some disciplinary categories tend to 'dominate’ in terms of their input on a range of issues, according to a hierarchical structure. This is dependent on what kinds of particular perspectives are reinforced, usually by authoritative bodies. Placing a greater weight on viewpoints from a certain discipline can lead to disregarding those derived from other disciplines. This was observed in the case study on Kissidougou, where mathematical and ecological perspectives were primarily considered and supported by policymakers, but perspectives from anthropology and history were overlooked.

Conclusion
As a counter-point to the advocacy of interdisciplinarity in solving complex issues, it might be that not all issues benefit from working across disciplines. What is important, however, is that academic disciplines are subjected to scrutiny from alternative approaches and disciplines. Encouraging communication and opening up a dialogue will always be beneficial.

As seen from the case study, there becomes a need to pull research out of disciplinary silos to solve complex problems more holistically. By travelling over the borders of academic disciplines, regardless of differences in methodologies, terminology and evidence, greater validity and a more comprehensive account of an area of inquiry can be reached. This can open the doors to new solutions, which incorporates crucial knowledge required to initiate productive change.