Why Are We Not Boycotting Academia.edu?
I don’t personally find academia.edu’s basic business model to be as inherently “parasitic” as the main participants in the above forum. Though I’m wary of the new proposition on academia.edu of peer reviewing for free, (although to have one’s work peer-reviewed is not free) I’m actually wary of the notion of peer reviewing at all. The reasons for that I’ll touch on below. In terms of the general model of the site, though, the notion of a boycott seems tangential to the issues.
If one wants to disrupt a business model such as that of academia.edu, the best way to do so is to accomplish the same thing but give away the resulting metadata without charge. Boycotting is largely self-defeating to that aim, and self defeating in a number of other ways, given that academia.edu is more widely known and read, and in many cases more widely respected, than most open access journals.
This last point, that academia.edu is in many cases more widely respected, arises partly from the association of most open access journals to a particular institution. While in some fields this may not be an issue, in those that are likely to have significant institutional bias, such as philosophy, it becomes very problematic. This bias is natural, since using the philosophy example, professors whose interest is focused on analytic philosophy are unlikely to hire a Deleuzian for the next job opening. Nevertheless it is problematic to a reader.
The other reason it is more widely respected in many quarters is a basic problem with the peer review notion itself, which is that those in a given field who have been in the field long enough to gain the necessary respect to become a peer reviewer by definition have self-interest in maintaining assumptions in the field on which their own work is based against anything that might undermine those assumptions, in essence, against any research that could in any real way be considered “new” rather than a simple continuation of the old.
This specifically affects the business model of academia.edu, since most private R&D organizations are specifically looking for the “really new”, and not continuations of old assumptions and ideas based on them. The problem can be seen in the following couple of examples:
- while neuroscientists are currently pondering the possibility that quantum phenomenon may be at work in allowing the mind/brain to accomplish what it does, AI technologists have long since given up even imitating in a small way the abilities of the mind/brain using electronics (themselves much faster than the neuroscientific electro-chemical models) without using quantum phenomena to speed up long running analytical processes that the human mind/brain accomplishes almost instantaneously
- there was a running joke among telecom technologists about biologists arguing whether strong emergence and self organization was at all possible, and doing so over 4G internet connections. The basis of the joke is that 4G cellular is largely the same technically as 3G, the major difference is that the 4G algorithms produce emergent phenomena to do with routing, that then self-organize into more efficient routing paths than any direct algorithm could come up with.
The assumption underlying the article and it’s contention that a “parasitic” relationship exists is not due to the relationship being inherently parasitic, but due to specific recent political trends that give private organizations advantages versus public organizations. Companies that invest heavily in R&D contribute to the public system, including public schools, in numerous ways. Occasionally directly, but more often indirectly through taxes on profits and income taxes on those that work there. Cuts to R&D budgets in public schools have no direct connection to increases or drops in tax income from private R&D heavy companies. The companies that get away via loopholes in paying taxes are a separate issue from the ideology that public schools should be privatized to stop them taking money from the public/private purse, even though quite often the same political parties either support both or oppose both.
That the current trend is supported by many R&D heavy companies goes back to the problem of peer review as part of a larger problem with modern scientific method itself from the perspective of private R&D, and thus the reason for it being largely replaced by “knowledge work”. Modern scientific method (and its enforcement via peer review) tends to do similar experiments under similar conditions (say with one parameter changed), this allows both the idea that, although technically it’s not an exactly repeated experiment, it accomplishes the equivalent while also allowing one or two parameter changes to be tested. Simultaneously the careful isolation of the experiment from its surroundings might help isolate specific effects from a scientific POV, but from a private research POV means the experimental results say very little about any real world use of what is being tested.
The problem with this from the perspective of private R&D is that it isn’t very useful, and it is very expensive. It’s far more useful from the private sphere’s perspective to discover things that have relatively predictable effects under the widest range of conditions possible, and to see what side effect occur in the least isolated situation possible, but modern scientific method does precisely the opposite, and to accomplish it using scientific method results in the cost in both monetary terms and in time terms being deadly. Particularly the latter is problematic – no matter how wealthy a private enterprise is, if it is consistently last to market with innovations, it won’t remain wealthy very long.
Analysing trends etc. can be extremely useful not only to for-profit R&D companies, but perhaps even more so to researchers themselves and to those who spend time thinking about the results of various research (research itself tends to be self-propelling, so researchers have a tendency to go on to the next research project without spending a lot of time thinking about the implications and relevance of results. Perhaps the greatest irony of modern science is that as soon as something is verified and added to our shared knowledge, it becomes largely an unexamined part of our shared belief-system. We spend vast amounts of time increasing this shared knowledge yet very little pondering or critiquing it, in fact most researchers avoid either to the greatest degree possible.
A limited amount of data can be gleaned by individual contributors to academia.edu (mainly only to do with their own audience) but plenty of generalizable data can be gleaned by analysing the site as a whole, without requiring any privileged access.
Publication of such data would undermine the business model of academia.edu to some degree, since of the information R&D companies might want, a significant portion could be obtained freely. But sale of the data only available from academia.edu itself would still likely leave the company with sufficient income to continue, while the freely available data would be useful to those who contribute to academia.edu and similar sites with new research, and to those who analyse and think about those contributions without a profit motive.