Keeping up with herders

I

Really-existing practices and processes of pastoralist households are known to be empirically differentiated, so much so that the popular common property resource (CPR) management narrative no longer captures (if it ever really did) the changing gist of what is going on in pastoralism(s).

Wheere so, we have then to ask ourselves how are policymakers to keep up with the changes and differentiation that even we researchers have a hard time to track?

II

More, the follow-on requirement to be provisional in our findings and open to all manner of caveats is evident on all sides of pastoralist development, i.e., not only those espousing evidence-based narratives, but also those leveling the critiques of said policies.

It’s far too early, by way of prime example, to adopt fall-and-stall narratives of the depastoralizing, deskilling, disorganizing and dewebbing of the pastoralist life-world (leaving behind corpse-pastoralism, knifed by conflicts, mummified by inequality, buried at sea in liquid modernity, and dissolved in the quicklime of disaster capitalism while harboring yet worse to come).

More, it’s highly problematic for researchers to recommend that government officials and NGO staff be in an authentic conversation with pastoralists taking the lead, when those researchers wouldn’t be caught dead in collaborating with the powers that be. This is especially problematic when (1) pastoralists bear all the risks when the recommendations go wrong and (2) government would be blamed anyway if mistakes in implementing the recommendations were not caught beforehand.

III

So it seems to me a productive question is not, “What replaces current dominant narratives for the purposes of better pastoralist development?,” but: “How do we catch up with and keep abreast of what pastoralists are actually doing?”

So what? Our not-knowing what pastoralists are doing better by way of managing under uncertainty—practices and mechanisms—is the mirror reflection of our trying to manage uncertainty by not-knowing the big-data algorithms for decision-making we increasingly rely upon.