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"This might seem like a worthy aspiration. Many social scientists contend that science has a method, and if you want to be scientific, you should adopt it. The method requires you to devise a theoretical model, deduce a testable hypothesis from the model and then test the hypothesis against the world. If the hypothesis is confirmed, the theoretical model holds; if the hypothesis is not confirmed, the theoretical model does not hold. If your discipline does not operate by this method — known as hypothetico-deductivism — then in the minds of many, it’s not scientific."
"In their recently published book A Model Discipline: Political Science and the Logic of Representations (Oxford University Press), Clarke and Primo delve into the ramifications of this "physics envy" for political science. In their quest to emulate the hard sciences, Clarke and Primo write, political scientists have placed far too much emphasis on model testing, resulting in the widespread view "that theoretical models must be tested to be of value and that the ultimate goal of empirical analysis is theory testing."
A Model Discipline argues that the logic behind this stance is hopelessly flawed, while its impacts have been detrimental to political science in a variety of ways."
Web links from the book - Bryman: Social Research Methods: 3e
Web links
A series of annotated web links to social research websites, organized by chapter, enables you to extend your understanding by reading the latest perspectives on social research issues.
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To return to this blog’s recent exemplar of post-Marxist social history of science, Morris Berman’s account of the early years of the Royal Institution: his references to the “epistemology of modernization” and Peter Berger and Thomas Luckmann’s The Social Construction of Reality: A Treatise in the Sociology of Knowledge (1966) refer not to the acts of learning or constructing ideas, per se, but to the rationales that underlie a modern, industrial way of life. The argument in Berman’s book is that a “legal ideology of science” psychologically, culturally, and socially smooths over structural disjunctures in the logic of society, constraining political action, and precluding the possibility of a more logical and just polity.
By contrast, the “cultural history of knowledge” (as I will call history inspired by the “sociology of scientific knowledge” and related programs) adhered to the doctrine of symmetry, admitting no preference for one or another system of ideas, which allowed for a more “naturalistic” description of history. By handling systems of knowledge evenly, drawing on Thomas Kuhn, cultural history dismissed the possibility that any one system would win out by virtue of its innate obviousness. This point was supposed to make cultural history into a potent talisman against Whiggism.
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Cultural historians seem comfortable declaring that any old study hasn’t been done because some historiographical prejudice — whether professional, philosophical, or popular is usually left ambiguous — has prevented some new facet of “culture” from being seen. The liberty taken with the historiographical power to declare things invisible renders scholarship eternally path-breakingly heroic, but never synthetic, thus releasing it from any real scholarly responsibility, except to avoid committing a few basic taboos often afflicting more popular or philosophical historiographies.
It has been said (among others, by Shapin (paywall)) that cultural historians need to leave behind their “jargon” and to take their message to a broader audience. But it is exactly this jargon that makes the cultural history of knowledge, as it is currently practiced, sustainable. I would argue that the jargon does not allow scholars to communicate complicated and subtle ideas to each other (which would be the case with a true “hyperprofessionalism”). Rather, it seems to allow scholars to construct their thoughts in such an arcane way as to prove to themselves that they do not think about science like other people do. In fact, this is precisely why it is believed that the message needs to be better popularized.
"Dedoose is an amazing Web 2.0 application enabling researchers from all disciplines to conduct qualitative and mixed methods research at around $11/month. Designed by UCLA's Drs. Thomas Weisner and Eli Lieber to make mixed methods research intuitive, efficient, and effective."
"• Highlighting the depth and breadth of methodological expertise in the social sciences at the University of Manchester.
• Promoting and facilitating methodological excellence, innovation and inter-disciplinarity."
"STS works with a continental model of knowledge – thick description and, as Ezra points out, proliferation of concepts. Rather than hammer a variable home, they jump from interesting case to case. They revel in new phenomena. It’s very ecological – new empirical observations suggest new ways of combining concepts, creating a mangled web of theory. Of course, this is very anti-normal science. You end up with a cabinet of curiosities than a deep and precise knowledge of a specific issue."
" Very roughly: with the rise of anthropologically-inflected cultural history since the 1970s, the balance between structure and agency seems to have shifted from keywords related to the former (social, institutions, mentalités) to those related to the latter (individuals, agency, self-fashioning)."
"Let me now express my position more clearly and systemically: philosophy of science can seek to generate scientific knowledge in places where science itself fails to do so; I call this the complementary function of philosophy of science, as opposed to its descriptive and prescriptive functions. I propose taking the philosophy of science as a field which investigates scientific questions that are not addressed in current specialist science — questions that could be addressed by scientists, but are excluded due to the necessities of specialization."
"While traditional grants remain central in US federal support of academic scientists and engineers, the role of multidisciplinary NSF Centers is growing. Little is known about how funding through these Centers affects scientific output or (as is an NSF aim) increases academic collaboration with industry. This paper tests the use of CVs to examine how Center funding affects researchers’ publication rates and their obtaining industry grants. We find that CVs are indeed usable, but some ways of collecting them work much better than others, and that researchers who obtain Center grants are more likely to obtain grants from industry too, suggesting that this NSF aim is being met. We do not find that Centers improve publication rates. "
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