I am interested in the nature of inter- and transdisciplinary research, which often involves some notion of “generalism”. There are different ways to further conceptualize generalism in this context.
First, a bit of terminology that I will rely on throughout this post: I call bodies of knowledge where insights are being drawn from “source domains”. The body of knowledge that is being informed bythis approach is called the “target domain”.
Directionality of generalism
We can distinguish between SFI-style generalism from FHI-style generalism? (h/t particlemania for first formulating this idea)
In the case of SFI-style generalism, the source domain is fixed and they have a portfolio of target domains that may gain value from “export”.
In the case of FHI-style generalism, the target domain is fixed and the approach is to build a portfolio of diverse source expertise.
In the case of SFI, their source domain is the study of complex systems, which they apply to topics as varied as life and intelligence, cities, economics and institutions, opinion formation, etc.
In the case of FHI, the target domain is fixed, although more vaguely than it might be, via the problem of civilization-scale consequentialism and source domains include philosophy, international relations, machine learning and more.
Full vs partial generalism
Partial generalism: Any one actor should focus on one (or a similarly small number of) source domains to draw from.
Arguments:
Ability: Any one actor can only be well-positioned to work with a small number of source domains because doing this work well requires expertise with the source domain. Expertise takes time to develop, so naturally, the number of source domains a single person will be able to draw upon (with adequate epistemic rigor) is limited.
Increasing returns to depth: The deeper an actor’s expertise in two fields they are translating between, the higher the expected value of their work. This can apply to individual researchers as well as to a team/organization doing generalist researchers.
Full generalism: As long as you fix your target domain, an actor can and should venture into many source domains.
Arguments:
Ability: An actor can do high-quality research while drawing from a (relatively) large number of source domains, some of which they only learn about as they discover them. This “ability” could come from several sources:
The researchers’ inherent cognitive abilities
The structure (i.e. lack of depth) of the field (sometimes a field might be sufficiently shallow in its structure that the assumption that someone can get adequately oriented within this field is justified)
Error correction mechanisms within the intellectual community being sufficiently fit (which means that, even if an individual starts out by getting some important things wrong, error correction mechanisms guarantee that these mistakes will be readily discovered and corrected for).
Increasing returns to scope: The richer (in intellectual diversity) an actor’s expertise, the juicier the insights. Again, this argument could apply to an individual or groups of individuals working closely together.
Note that you can achieve full generalism at an organizational level while having a team of individuals that all engage in partial generalism.
Types of generalism
[Cross-posted from here]
I am interested in the nature of inter- and transdisciplinary research, which often involves some notion of “generalism”. There are different ways to further conceptualize generalism in this context.
First, a bit of terminology that I will rely on throughout this post: I call bodies of knowledge where insights are being drawn from “source domains”. The body of knowledge that is being informed by this approach is called the “target domain”.
Directionality of generalism
We can distinguish between SFI-style generalism from FHI-style generalism? (h/t particlemania for first formulating this idea)
In the case of SFI-style generalism, the source domain is fixed and they have a portfolio of target domains that may gain value from “export”.
In the case of FHI-style generalism, the target domain is fixed and the approach is to build a portfolio of diverse source expertise.
In the case of SFI, their source domain is the study of complex systems, which they apply to topics as varied as life and intelligence, cities, economics and institutions, opinion formation, etc.
In the case of FHI, the target domain is fixed, although more vaguely than it might be, via the problem of civilization-scale consequentialism and source domains include philosophy, international relations, machine learning and more.
Full vs partial generalism
Partial generalism: Any one actor should focus on one (or a similarly small number of) source domains to draw from.
Arguments:
Ability: Any one actor can only be well-positioned to work with a small number of source domains because doing this work well requires expertise with the source domain. Expertise takes time to develop, so naturally, the number of source domains a single person will be able to draw upon (with adequate epistemic rigor) is limited.
Increasing returns to depth: The deeper an actor’s expertise in two fields they are translating between, the higher the expected value of their work. This can apply to individual researchers as well as to a team/organization doing generalist researchers.
Full generalism: As long as you fix your target domain, an actor can and should venture into many source domains.
Arguments:
Ability: An actor can do high-quality research while drawing from a (relatively) large number of source domains, some of which they only learn about as they discover them. This “ability” could come from several sources:
The researchers’ inherent cognitive abilities
The structure (i.e. lack of depth) of the field (sometimes a field might be sufficiently shallow in its structure that the assumption that someone can get adequately oriented within this field is justified)
Error correction mechanisms within the intellectual community being sufficiently fit (which means that, even if an individual starts out by getting some important things wrong, error correction mechanisms guarantee that these mistakes will be readily discovered and corrected for).
Increasing returns to scope: The richer (in intellectual diversity) an actor’s expertise, the juicier the insights. Again, this argument could apply to an individual or groups of individuals working closely together.
Note that you can achieve full generalism at an organizational level while having a team of individuals that all engage in partial generalism.