By mapping the way patents cite each other, network scientists have been able to study how different technologies rely on each other and how new technologies emerge.
This could be because Chinese science is poor or because researchers in America, Europe and Japan have an historical bias towards citing each other.
Advocates of such efforts say that references are a pillar of scholarly work and that being able to understand how articles cite each other shouldn't require an expensive subscription to a database.
"There needs," he says, "to be a critical mass of women intellectuals who will cite each other, refer to each other - that's what happens with men". One might also note that a female "public" intellectual is rarely regarded with the same deference as her male counterpart.
This means, as Helga Konrad, former special representative for the Organisation for Security and Co-operation in Europe on human trafficking, put it to me that everybody ends up 'cutting and pasting', citing each other's publications in a merry-go-round that doesn't actually centre on genuine empirical data.
In a scathing 2015 article, he complained that the "Canadian" trio of computer scientists hailed in Silicon Valley as the superstars of AI – Geoffrey Hinton (Google), Yann Lecun (Facebook) and Yoshua Bengio (IBM) – "heavily cite each other", but "fail to credit the pioneers of the field".
"We started out with patents and medical documents, and we would look at how different companies were citing each other, how inventors were working together and how scientists co-authoring medical literature were co-authoring papers together," said Alexander Shapiro, the chief executive of TouchGraph, which is not owned by Facebook.
"We don't cite each other, and we don't trust each others' descriptions of protein crystallization," he said.
