Beyond this historical legacy to contend with, Edelman identified contemporary challenges of how we “know” how many hectares are being grabbed. What are our sources, and how reliable are they? Who produced them and why? Is this, Edelman asked, a case of ‘Garbage In, Garbage Out’? Researchers who want to use these datasets have to keep in mind that even datasets are framed in ways that are not always explicit, with systematic biases that must be identified.
Sources of information on land grabs may be based upon press reports— in which case we must ask what the journalist’s sources are and who initiated the article. As Edelman pointed out, journalists may focus on some areas and downplay or ignore others.
Carlos Oya followed this with an equally dynamic talk, where he posed the question: Why have land databases? Oya issued important cautions: he cautioned against falling prey to easy dichotomies (small farms vs. large farms, family farming vs. capitalist farming, locals vs. outsiders, subsistence vs. market-oriented, etc.). He expressed concern about the lack of baseline evidence in some research, and suggested that since many deals are just starting or recently underway, researchers are in a prime position to start a study and return to the site in five or ten years. Oya also pointed out that when it comes to impacts of land grabs, we need to bring labor and exploitation back into the analysis.
In his conclusion, Oya urged researchers to engage in reflexivity, and ask ourselves: who are we taking the part of? What is our position? There is a real danger, he warned, that by not reflecting on their own assumptions and positions, critical academics could alienate themselves and not become a part of the debate. Another danger is discrediting the struggles we study by using poor evidence.
These reflections were followed by responses from the Land Matrix Partnership, GRAIN, and Oxfam, focusing largely on how data is complied and why. Quality and creation of land grab data is a fascinating topic, with no obviously easy solution: crowdsourced data or press data has the advantage of being has obvious selection biases, remote sensing data may be misleading, corporate data may be unavailable.
There is a genuine dilemma here: there is an urgency to the impulse to raise awareness and disseminate information. Putting out inaccurate data risks unfairly damaging the reputation of people or businesses. This data clearly needs to be checked: but is total accuracy an achievable goal or a red herring?
In any case, something may be lost if we just focus on the “big numbers”. Lorenzo Cotula had an interesting comment in the Q and A. We’ll never get to one precise number of how much land is being grabbed, he said, but it’s important to look at how land grabbing affects people’s lives, in a way that tells us something new. If measuring hectares eludes us, focusing on measuring impacts could be another valuable approach.