2. Topic outline
• Theoretical considerations:
• Two communities of science studies: quantitative and qualitative
• Scientific knowledge production as a site to bridge these communities
• The overall design of my dissertation research
• RQ: translating the concept of packaging into quantitative terms
3. The two communities of science studies
Quantitative
• Bibliometrics,
Scientometrics, Science of
science, Quantitative
science studies…
Qualitative
• STS, History of science,
Philosophy of science…
4. The two communities:
Mertonian vs. Latourian
• Quantitative science studies is still
largely based on a normative
assumption of scientific publication
and citation: to cite is to credit.
• Different citation theories have
been developed but are far from
fully accepted.
• Advanced data science methods
have made new research directions
possible that are less reliant upon
citation data.
• Qualitative science studies on
scientific knowledge production
has gone through a few theoretical
“turns” since the late 1970s.
• Material turn (Hicks, 2010)
• Rhetorical turn (Billig, 2015)
• How scientific knowledge is
produced through material and
language practice (“laboratory
studies”) became an important site
in the overall STS scholarship.
5. Design of my dissertation research
• Goal:
• Bridge the two science studies communities in the site of textual inscription
of laboratory practice
• Objective
• Identify two types of scientific objects related to scientific knowledge
production process, i.e. research methods and scientific software, from full-
text publications by using machine learning and natural language processing
methods on a large scientific corpus
• Evaluate quantitative relationship among representation and distribution of
objects and the conditions of knowledge production informed by qualitative
and quantitative conceptual frameworks
• Offer products to promote “literature as informant” research (Kelty, 2009)
6. Operationalization of research method and
scientific software entities
• All examined objects are named and functionally meaningful objects
that can be identified from scientific publications.
• Named: the object should be represented in the text as a name, rather than
just a description.
• Functionally meaningful: the object should have functions in the scientific
research, based on the descriptions in the research articles.
• No other rules will be used to select research objects.
7. Question: Is it possible to identify packages of
scientific works from research articles?
• Scientific works are packaged (blackboxed) into standardized research
objects in order to increase the do-ability of research problems
(Fujimura, 1987).
• Theory-method packages --> bandwagon effect (Fujimura, 1988)
• Software as package (Kling and Scacchi, 1979)
• RQ: how to translate the idea of package into quantitative
parameters?
• Is it possible to identify method-software packages within scientific texts?
• Can we connect such textual patterns to other conditions of science?
8. Reference
• Billig, M. (2015). Rhetoric of social psychology. In Deconstructing social
psychology (pp. 59–72). Psychology Press.
• Fujimura, J. H. (1987). Constructing Do-able Problems in Cancer Research:
Articulating Alignment. Social Studies of Science, 17(2), 257–293.
• Fujimura, J. H. (1988). The molecular biological bandwagon in cancer research:
{Where} social worlds meet. Social Problems, 35(3), 261–283. Retrieved from
http://socpro.oxfordjournals.org/content/35/3/261.abstract
• Hicks, D. (2010). The material-cultural turn. The Oxford Handbook of Material
Culture Studies, 25–98.
• Kelty, C. (2009). Ten thousand journal articles later: ethnography of" The
literature" in science. Empiria. Revista de Metodología de Ciencias Sociales, (18),
173–192.
• Kling, R., & Scacchi, W. (1979). Recurrent dilemmas of computer use in complex
organizations. In Proc. 1979 Nat’l Computer Conf (pp. 107–116).
Editor's Notes
Representation: how research objects are referenced in scientific texts, such as name mentions, citations, and textual contexts related to these marks.
Distribution: the frequencies of an object at the level of papers and more aggregated levels.
Kling and Scacchi (1979), such objects are consisting not only of hardware and software, but also skills, data, beliefs about computing, and supports received from other pieces of infrastructures.