Comps readings this week
Lessig's Code 2.0
Good stuff here if he does go a little far with ideas of cyberspace sovereignty and citizenship. With that said, his views are actually pretty balanced, even if they're not frequently represented that way. In case anyone was keeping track - it's actually 18 chapters, not 15.
Lee, S., & Bozeman, B. (2005). The Impact of Research Collaboration on Scientific Productivity. Social Studies of Science
, 35(5), 673-702.
I'm kind of on the fence about this one. They used a few large surveys of scientists and engineers from all different backgrounds, compared with analysis of their CVs, their journal articles as found in Web of Science, some interviews... talk about triangulation! There's this standard thing that increasing collaboration increases productivity (as measured by peer-reviewed publications in science). As an aside, they cite Lotka (1926), yay! But there are a million potentially confounding factors and interactions from various things like:
- researcher status, rank, age
- researcher gender
- if researcher is a foreign national/non-native speaker
- researcher job satisfaction
- researcher perception of discrimination
- collaboration motives like mentoring/service, quality/social capital, or finding someone with complementary skills
So this point of this article is to take this massive pile of data and to build a couple of big models, and see which terms are significant. Another thing you need to know is that they look at the straight number of articles, and then they look at a fractional number - each article divided by the number of authors.
A problem with this article is that the regression formulas aren't explicitly stated, and it's not OLS, so I'm a bit confused about how they do things. Also, they talk about lots of things that weren't even close to significant, and they accept Chronbach alphas as low as .32! (wow, my prof gave me a hard time at .64, should be > .70). Probably still sound, though. The end is actually sort of not what you'd expect - for the fractional model, no real correlation once everything is taken into account. There is a decent correlation for the normal model... Hardly anything was significant - really only the number of grants (and not even the batting average for grants).
Watts, D. J. (2004). The new science of networks. Annual Review of Sociology
, 30(1), 243-270. DOI:10.1146/annurev.soc.30.020404.104342
Decent review of the more recent network stuff that's been heavily influenced by advances by physicists and mathematicians as well as widely available computing power. Discusses small world networks, scale-free networks, and a couple different approaches in epidemiology and social contagion. Not precisely what I needed - duh, this guy assumes his readers know the social theory, and is bringing them up to speed on math and applications. Note venue. Of course. I need the social theory, which I'm weak on*, and can pick up additional math as necessary later on. So not the thing for me, but still a decent article.
Bohlin, I. (2004). Communication Regimes in Competition: The Current Transition in Scholarly Communication Seen through the Lens of the Sociology of Technology. Social Studies of Science
, 34(3), 365-391. DOI: 10.1177/0306312704041522
I have to say that the SCOT
bit was just thrown in for the editor's sake - there's not the strong hand of theory involved in this. In any case, this article ties together many of the lines of reading I've been doing and makes some interesting and useful points. It's not empirical at all - really sort of a research paper like you'd do in a doctoral seminar. He compares scholarly publishing and its traditional functions with self-archiving in both e-/pre-print servers/repositories and the author's web page. For functions, he goes with quality control, distribution, and archiving (Compare to Borgman). He considers priority and allocating credit to be part of those three. He then goes through the development of AriXiv and its predecessors including Preprints in Particles and Fields
. In the case of HEP
, in particular, and also other areas represented on AriXiv, the distribution function is much more important than the quality control function and traditional journals fall down on the speed of distribution. Also, the costs of journals can be prohibitive, so the distribution is limited. These scientists do, however, continue to publish in traditional venues to be competitive for grants and promotions. Indeed, >70% of articles on ArXiv end up as journal pubs and another 20% end up as conference papers (he cites like 4 studies showing this).
Here's an interesting part: why does self-archiving work in some areas and not others?
1) existing culture of exchanging pre-prints (like in HEP)
2) expectations and policies of journals in the field wrt prior publication. Compare UK biomed journals (BMJ, Lancet) with American (NEJM, JAMA), compare ACS to any sane publisher...
3) acceptance rates for journals in the field (ah-ha!)
Right, so, I remember in Merton and Zuckerman how they discussed the (at the time) 70% acceptance in physics and 20% acceptance in some areas of the humanities.... there's newer research that in some fields it's closer to 90% acceptance and others it might be below 20%. The reasons for this vary - agreement between authors and publishers about what constitutes good work, page length, institutional internal review required before submission to the journal (HEP), etc. This makes perfect sense (and I did read the Walsh and Bayma paper that this comes from but didn't connect the two): you don't really want to see something if a) you can't cite it and you might never be able to cite it b) it will undergo serious revision before it ever makes the light of day and c) the delay before it's citable might be like 2 years.
Another interesting thing that might end up as the focus for a submission to the SSSS conference (if I can get into gear!) is this blurring of the distinctions between informal and formal scholarly communication. If the functions of formal scholarly communication are as mentioned above and they were used to make information seeking more efficient... Let's look at distribution - wider and quicker via self-archiving, but more efficient and more precise using a research database with human indexing. Putting stuff up on a blog or on twitter or friendfeed or a wiki is much faster - but information retrieval is at best imprecise, what with semantic markup seldom used. I suppose if you are well embedded in the appropriate network - IOW you are "friends" with people with the right interests - this becomes less important... Archiving. We did recently have this discussion on friendfeed. These conversations are definitely more archived and less ephemeral than hallway conversations (which is interesting, too), but are not as stable as the journals - particularly those in CLOCKSS or PORTICO , or whatever. As for quality control: trust is built on the web differently than in formal publications.... hm.
Callon, M., Courtial, J. P., & Laville, F. (1991). Co-word analysis as a tool for describing the network of interactions between basic and technological research: The case of polymer chemistry. Scientometrics
, 22(1), 155-205. DOI:10.1007/BF02019280
*not* recommended. I think it's sketchy, to be frank. What is there isn't well described, and some of the choices were made due to computing issues (I presume) that no longer exist. The whole basis they use for building part of their collection is *uncited* and not easily findable using WoS or Google Scholar. I might pick up something from H. White whom I trust in this area to get this uneasiness out of my system. Goes to show when I pick something vs. my committee :)
Wellman, B., Salaff, J., Dimitrova, D., Garton, L., Gulia, M., & Haythornthwaite, C. (1996). Computer Networks as Social Networks: Collaborative Work, Telework, and Virtual Community. Annual Review of Sociology
, 22, 213-238
Note date, then read this quote:
The popular media is filled with accounts of life in cyberspace... much like earlier travellers'tales of journeys into exotic unexplored lands. Public discourse is (a) Manichean, seeing CSSNs as either thoroughly good or evil, (b) breathlessly present-oriented, writing as if CSSNs had been invented yesterday and not in the 1970s, (c) parochial, assuming that life on-line has no connection to life off-line, and (d) unscholarly, ignoring research into CSSNs as well as a century's research into the nature of community, work, and social organization. (p. 214)
Does this sound like blog discussions 2004-2007 (and at the colloquium I attended Friday)? Nothin' new under the sun. Anyway - this is a great road map of the research from about 1985 or so to its writing in 1996. I wouldn't recommend this for anyone but the most dedicated (or maybe with historic interest) as it is completely dated. (the Walsh & Bayma stuff cited is still very relevant, though, as are some of the other works cited.
talking about dated...
Shapiro, A. L. (1999). The control revolution: How the internet is putting individuals in charge and changing the world we know
. New York: Public Affairs.
This is unfortunately OBE
. I recommend Code v.2, as it covers mostly the same topics and has been updated. I read the first 8 chapters so far (about a third) and
- control is more than countries: it comes from ISPs; other providers like libraries, schools, work
- outdated evidenced by statements such as "as schools and libraries become wired"
- overly glossy everything is beautiful talk like you'd have during the dot com bubble
- glorious disintermediation - now we know that there are some things worth paying for: a real broker, a Realtor(tm), a librarian
- we know know that running the country, the state, the x by poll doesn't work
- it's not a choice of command line green on black vs. glorious windows...
He does have an interesting point about over personalization - but the obvious stuff like customizing e-mails isn't quite as troubling to me as the search results...*(As an aside, seems like one of the most important functions of a doctoral program in the social sciences is to teach researchers various theories and how to use them as a tool to understand how society works... my program did not do this, but it straddles science, including CS, so that's definitely not done there... my colleagues in the COMM school and in SOCY had like 3 heavy duty "theory" courses, at least... students coming after me in my program have precisely zero and this is not something that you can really do entirely on your own or with informal mentoring - or at least, it's difficult for me because that's how I'm doing it).