Secrecy in Industry and Academic Science

W. Hong and J. P Walsh, “For Money or Glory?: Commercialization, Competition and Secrecy in the Entrepreneurial University” (2008).


We've talked about the various incentives or lack thereof for scientists to share pre- and post-publication data and knowledge, both in terms of the workload and the secrecy/competition factor. This article from Sociological Quarterly is interesting to that discussion as it examines secrecy in academic science with regards to two primary variables: its relations to industry science and the general level of competitiveness.

The study is based off two surveys: one conducted in 1966 by Warren Hagstrom, who surveyed a national random sample of 1,947 academic scientists in six fields (mathematics, experimental physics, theoretical physics, experimental biology, other biology, and chemistry), the other conducted in 1998 with a national random sample of 399 scientists from four fields (experimental biology, mathematics, physics, and sociology).

The authors use the 30+ years between the surveys to try and demonstrate a long-term change in the level of secrecy practiced in academic science. The surveys are appended to the article, but the authors sum up their content best:

The two surveys measure secrecy by asking how safe scientists feel in discussing their current research with others doing similar work. The surveys also include a measure of scientific competition, asking respondents how concerned they are about being anticipated in their current research. The later survey also includes measures of patenting, industry funding, industry collaboration, gender, institution type, seniority, and publication productivity.

Finally, the authors restrict their analysis to three fields: mathematics, physics and experimental biology.

Their results are unsurprising in some aspects (though not all) but very interesting regardless. Broadly they find that secrecy has increased among academic scientists, but that there has been an overemphasis on the effects of commercialization (collaboration, funding and so on from industry science) over a general rise in the competitiveness of science. The authors note competition is endemic to both realms of science and that as competition for priority (the first to discover, patent, publish, etc.) increases, antisocial behavior rises. This can be as benign as forgetting to answer data requests to deliberate concealment of knowledge to data fabrication. As one frequently cited author (Robert K. Merton) summarizes, "The culture of science is, in this measure, pathogenic."

The authors found a slightly positive relationship between academic endeavors with industry funding and the level of secrecy. Interesting here too is a negative relationship between industry collaboration and secrecy. In this case ties with the commercial or industrial sector benefitted openness and data sharing. The authors also note that the field of experimental biology has seen the sharpest rise in secrecy, likely because of the commercial and public pressure for marketable products and a corresponding heavy involvement by the industry scientists and companies.

In resolving this problem the authors suggest a shift to a more secure funding stream along with a much reduced emphasis on immediate or short-term results. Of course such a change is not easy; the authors note that the open, communal knowledge-sharing principles of science is presently couched in a capitalist environment that values nondisclosure of knowledge to gain lead time to priority discoveries, products and patents. It's important to note that the authors don't believe there has been a change in the scientific model. Individuals still value sharing and openness but the constraints on sharing (priority, rewards, funding, advancement) have intensified to a degree that has become problematic.

So how can we reduce the competitiveness of academic science? So much work it seems is contingent on funding and the individual scientist. Ever-increasing competitiveness is not conducive to data curation, in fact I think it directly opposes it (as well as good science). The long scope of this study (1966-1998) has left me pretty worried.