The Changing Landscape of Knowledge Production Staa Milojevi

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The Changing Landscape of Knowledge Production Staša Milojević Center for Complex Networks and Systems

The Changing Landscape of Knowledge Production Staša Milojević Center for Complex Networks and Systems Research School of Informatics, Computing and Engineering Indiana University Bloomington

Changing landscape of knowledge production Science has experienced dramatic changes in knowledge production exemplified

Changing landscape of knowledge production Science has experienced dramatic changes in knowledge production exemplified by: -larger number of practitioners -increased pressures on productivity -shift toward “team science” -interdisciplinarity

Growth of publications Entire Web of Science Td = 24 yr Td = 9

Growth of publications Entire Web of Science Td = 24 yr Td = 9 yr Td = 26 yr Td = 13 yr

Exponential growth of scientific literature = Exponential growth of knowledge?

Exponential growth of scientific literature = Exponential growth of knowledge?

Exponential growth of scientific literature = Exponential growth of knowledge

Exponential growth of scientific literature = Exponential growth of knowledge

Big-data method for measuring the cognitive extent of scientific literature • Obtain concepts from

Big-data method for measuring the cognitive extent of scientific literature • Obtain concepts from parsing titles into phrases • Idea: count the number of unique phrases in unit quotas of ~3000 articles • 3000 articles which contain fewer unique phrases (X) have a smaller cognitive content than 3000 articles with more unique phrases (Y) • Large measurement quota is needed to reduce the stochasticity of the titles Milojević, S. (2015). Journal of Informetrics 9, 962

Cognitive extent Growth of Science Fortunato, S. , Bergstrom, C. T. , Börner, K.

Cognitive extent Growth of Science Fortunato, S. , Bergstrom, C. T. , Börner, K. , Evans, J. A. , Helbing, D. , Milojević, S. , Petersen, A. M. , Radicchi, F. , Sinatra, R. , Uzzi, B. , Vespignani, A. , Waltman, L. , Wang, D. , & Barabási, A-L. (2018). Science, 359(6379).

Interdisciplinarity

Interdisciplinarity

Operationalizing Interdisciplinarity We develop a measure of knowledge interdisciplinarity: the extent to which the

Operationalizing Interdisciplinarity We develop a measure of knowledge interdisciplinarity: the extent to which the field/author/paper draws on knowledge from distinct fields. Determine, for each Wo. S paper, its main area + contributions from other broad fields. Based on the analysis of references. Interdisciplinarity = % of references from other fields Milojević, S. , Radicchi, F. , & Walsh, J. P. (in preparation)

Level of interdisciplinarity in 13 broad fields Milojević, S. , Radicchi, F. , &

Level of interdisciplinarity in 13 broad fields Milojević, S. , Radicchi, F. , & Walsh, J. P. (in preparation)

Distribution of interdisciplinarity levels in 13 broad fields Milojević, S. , Radicchi, F. ,

Distribution of interdisciplinarity levels in 13 broad fields Milojević, S. , Radicchi, F. , & Walsh, J. P. (in preparation)

Changes in interdisciplinarity over time Entire Wo. S T S A F Milojević, S.

Changes in interdisciplinarity over time Entire Wo. S T S A F Milojević, S. , Radicchi, F. , & Walsh, J. P. (in preparation)

Changes in interdisciplinarity over time Since 1960 Milojević, S. , Radicchi, F. , &

Changes in interdisciplinarity over time Since 1960 Milojević, S. , Radicchi, F. , & Walsh, J. P. (in preparation)

Science as a team effort

Science as a team effort

Science as a team effort

Science as a team effort

Science is a team effort

Science is a team effort

Team size distribution and its evolution • Many studies focused only on the mean

Team size distribution and its evolution • Many studies focused only on the mean or the median sizes of teams, implicitly assuming that the character of the distribution of team sizes does not change • When distributions were looked into, the focus was only on power-law tails of large teams in recent times

Modern science: the rise of collaboration The increasing level of knowledge production by large

Modern science: the rise of collaboration The increasing level of knowledge production by large science teams Astronomy 1960 s: Individual authors (90%) and small teams 2000 s: Individual authors (<10%) Mean team size ~7 Previously only high-energy physics and biomedical; now most experimental fields have a “Big Science” component Poisson distribution Tail of power-law distribution

Change in the character of team size distribution Astronomy Team formation essentially a Poisson

Change in the character of team size distribution Astronomy Team formation essentially a Poisson process, which somehow transformed Milojević, S. (2014). PNAS, 111(11), 3984

Team sizes across disciplines LINES = threecomponent functional fits (physics) Astronomy, ar. Xiv (physics)

Team sizes across disciplines LINES = threecomponent functional fits (physics) Astronomy, ar. Xiv (physics) – prominent power-law tail Ecology, psychology – weaker power-law tail Mathematics – no power-law tail Milojević, S. (2014). PNAS, 111(11), 3984

How did large teams emerge?

How did large teams emerge?

Model: Two (three) types of research teams • Small core teams based on Poisson

Model: Two (three) types of research teams • Small core teams based on Poisson process Contribution of team types according to the model: • In recent times there is an excess of twoauthor papers over single-author papers, especially from authors who have just started publishing. Requires slightly modified Poisson distribution • Large, extended teams that grow gradually on the principle of cumulative advantage based on productivity Milojević, S. (2014). PNAS, 111(11), 3984

Trends in team sizes and types in the last 50 years Apply functional decomposition

Trends in team sizes and types in the last 50 years Apply functional decomposition to five-year periods in astronomy to get contributions by different team types It is the extended teams that drive the exponential growth of average team size. Core teams grow, but only linearly (changing norms of how many people are needed to do “standard” science? ) Milojević, S. (2014). PNAS, 111(11), 3984 Fraction of papers due to extended teams nearly constant. Team science is not a new thing, but only recently extended teams got conspicuously large. Core teams remain the main production mode!

Different team types correspond to different modes of knowledge production Core teams dominate Extended

Different team types correspond to different modes of knowledge production Core teams dominate Extended teams dominate Milojević, S. (2014). PNAS, 111(11), 3984

Trends in team sizes and types in the last 50 years – case of

Trends in team sizes and types in the last 50 years – case of “non-collaborative” field Extended component has very small contribution and such teams are barely larger than core teams Milojević, S. (2014). PNAS, 111(11), 3984

Is the only role of small teams to seed big ones? • Which approach

Is the only role of small teams to seed big ones? • Which approach contributes more to modern science intellectually? • Are the efforts of smaller teams becoming intellectually obsolete?

Evolution of the cognitive extents – by teams of different sizes Milojević, S. (2015).

Evolution of the cognitive extents – by teams of different sizes Milojević, S. (2015). Journal of Informetrics 9, 962

Inverse correlation between research team size and the cognitive extent of scientific output 2005

Inverse correlation between research team size and the cognitive extent of scientific output 2005 -2010 Milojević, S. (2015). Journal of Informetrics 9, 962 In physics and astronomy, single authors, pairs of authors, and small teams cover the largest intellectual territory, the same size as the entire field. Larger teams cover significantly smaller cognitive territory. In biomedicine, the small teams (3 -5 authors) cover the largest domain, but as in astronomy and physics, the very large teams cover the smallest cognitive territory. Plus: Topics covered by large teams are not exclusive to them

Interdisciplinarity and team sizes interdisciplinarity of teams vs. that of single authors Milojević, S.

Interdisciplinarity and team sizes interdisciplinarity of teams vs. that of single authors Milojević, S. , Radicchi, F. , & Walsh, J. P. (in preparation)

How does the shifting landscape of science over the past half century affect the

How does the shifting landscape of science over the past half century affect the roles of researchers and their overall careers?

Scientific careers through an organizational studies lens - Larger team sizes followed by the

Scientific careers through an organizational studies lens - Larger team sizes followed by the increased division of labor and standardization are bringing fundamental changes to scientific work and therefore the scientific workforce - Transition from the science organization based on craft to the one based on bureaucratic industrial principles (Hagstrom, 1964; Hargens, 1975; Walsh & Lee, 2015) - The tensions between the research production and teaching functions that academic labs provide (e. g. , Hackett, 1990; Hagstrom, 1964; Pavlidis et al. , 2014; Stephan, 2012; Teitelbaum, 2014).

The rise of “supporting scientists” or permanent team members The fraction of authors who

The rise of “supporting scientists” or permanent team members The fraction of authors who never become a lead author has risen dramatically Adapted from Milojević, S. , Radicchi, F. , & Walsh, J. P. (2018). PNAS, 111(50), 12616 -12623.

The rise of “supporting scientists” or permanent team members … and this is not

The rise of “supporting scientists” or permanent team members … and this is not the result of the increase in the number of transient (singlepublication) authors – still around 1/2 today w/o transients Adapted from Milojević, S. , Radicchi, F. , & Walsh, J. P. (2018). PNAS, 111(50), 12616 -12623. Transients excluded from cohorts

Milojević, S. , Radicchi, F. , & Walsh, J. P. (2018). PNAS, 111(50), 12616

Milojević, S. , Radicchi, F. , & Walsh, J. P. (2018). PNAS, 111(50), 12616 -12623.

Thank you! Staša Milojević Center for Complex Networks and Systems Research School of Informatics,

Thank you! Staša Milojević Center for Complex Networks and Systems Research School of Informatics, Computing, and Engineering Indiana University Bloomington [email protected] edu Parts of this work were supported by National Science Foundation grant EAGER SMA-1645585. This work uses Web of Science data by Clarivate Analytics provided by the Indiana University Network Science Institute and the Cyberinfrastructure for Network Science Center at Indiana University.