You can form a cartel. Or you can ignore it all together.
If you want to understand the modern academy, it wouldn’t hurt to start at “impact factor.”
Every year, the company Thomson Reuters assigns every academic journal an “impact factor.” Impact factors measure, roughly, how often papers published in one journal are cited by other journals. It is an ecological measurement, in other words. You’d recognize the names of journals with the highest impact factors — Nature, Science, etc. — but the world of scholarly journals is enormous, and there’s crowding at the bottom.
Two stories today illustrate the problems with impact factors, and the difficulty of measuring knowledge through any metric.
First, Nature News revealed that a Brazilian citation cartel had been outed by Thomson Reuters. That’s right: a citation cartel.
The Brazilian government measures graduate schools based on the impact factor of the journals that those schools’ students publish in. Brazilian journals, many of which are newer, have low impact factors, so Brazilian graduate students often publish in journals abroad. This makes them and their graduate program look better, but it means the commercial benefit of Brazilian scholarship flows, in part, to non-Brazilian companies.
So editors at a set of Brazilian journals began linking to each others’ journals... a lot. The flurry of cross-citation made every journal appear more influential, and succeeded in raising the journals’ impact factor in 2011. For a moment, the scheme worked.
Society's techno-social systems are becoming ever faster and more computer-orientated. However, far from simply generating faster versions of existing behaviour, we show that this speed-up can generate a new behavioural regime as humans lose the ability to intervene in real time. Analyzing millisecond-scale data for the world's largest and most powerful techno-social system, the global financial market, we uncover an abrupt transition to a new all-machine phase characterized by large numbers of subsecond extreme events. The proliferation of these subsecond events shows an intriguing correlation with the onset of the system-wide financial collapse in 2008. Our findings are consistent with an emerging ecology of competitive machines featuring ‘crowds’ of predatory algorithms, and highlight the need for a new scientific theory of subsecond financial phenomena.
Abrupt rise of new machine ecology beyond human response time Neil Johnson Guannan Zhao Eric Hunsader Hong Qi Nicholas Johnson Jing Meng Brian Tivnan
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