Info

  • What this is:
    • This radar chart displays STI policy related graduate programme's coverage of educational content.
    • The charts are based on our study to identify core components taught in various institutes in the world.
    • The calculation was done using topic modelling analysis.
  • How to read this chart:
    • Blue line in the chart indicates average scores of components of topics in our samples. Yellow line in the chart shows components of topics by each programme. The components sum up to 1 over all topics.
  • Who we are:
    • We are the research team to develop core contetns of SciREX educational programme. This team is consisted of members from SciREX Center of National Graduate Institute of Policy Studies (GRIPS), Center for Research and Development Strategy (CRDS) of Japan Science and Technology Agency (JST) and National Institute of Science and Technology Policy (NISTEP), Japan.

Data source

  • The present study includes the syllabi information from 24 STI policy related education programmes of 10 countries.
  • All of the targeted programmes were graduate level (Master’s or doctoral courses) but non-degree programmes were also included: 6 programmes at 6 Japanese universities, 8 US programmes, 2 programmes each from the UK and Turkey, and one programme each from the Netherlands, South Africa, Canada, Belgium, Italy, and the Russian Federation.
  • Apart from five programmes for which information was collected through an exchange of emails after last year’s STI 2017 presentation, information was gathered from programme websites.
  • The targeted programmes were selected through a website survey; for US programmes, we refered to the ‘Engaging Scientists & Engineers in Policy (ESEP) Coalition’ for each programme.

Limitations

Due to incompleteness in data and methodology as follows, results should be interpreted with cautions.
  • Data coverage and quality
    • Data coverage is limited. In general, topic models require contents from more than several thousand documents. Limited data might indicate biased results.
    • The amount of information publicly available differs significantly among programmes.
    • Lack of universal standard for writing syllabi may result in university-,program-, and teacher-specific bias.
    • Collected data might be incomplete for data-cleansing and could not ensure sufficient analytical accuracy.
  • Methodology
    • Subjectivity in defing the number of topics and its names.
    • Machine classification sometimes leads to quite unnatural and erroneous results from common sense.

Topic

The below tables shows the top 20 words and the probability distribution of words to topics.
Science and Society Law and Ethics Technology Adoption Technology and Management
No Topic 1 Topic 2 Topic 3 Topic 4
science issue market management
technology law technological business
social environment role risk
society international introduction project
communication include work strategy
scientific current state issue
relationship legal process process
knowledge future case company
think human change strategic
addition space debate organization
field global topic area
require explore production focus
question conflict issue idea
various life development source
critical concern approach industry
module topic firm control
study activity organization practice
concrete regulatory network knowledge
discipline non identify development
scientist modern technical creativity
Intellectual Assets Energy and Environment Development and STI Innovation and Policy
No Topic 5 Topic 6 Topic 7 Topic 8
application environmental development innovation
design change economic knowledge
property energy social technology
intellectual problem different policy
right climate country concept
community focus global evaluation
registration perspective level develop
international examine regional public
procedure discuss governance university
examination sustainable develop trend
trademark infrastructure protection design
trade explore world program
industrial resource special transfer
patent sector build institution
report behavior effect base
formal approach benefit sti
file affect poverty private
aim water attention institutional
evaluation natural national measure
search plan economy national
Policy Science Research Design Quantitative Methodology Qualitative Methodology
No Topic 9 Topic 10 Topic 11 Topic 12
policy research analysis student
public lecture method class
understand learn student develop
health plan theory information
make study data discussion
political basic model seminar
process field include presentation
issue problem topic paper
decision case apply need
government economics provide study
intervention base technique write
politics conduct aim skill
approach practice cover read
impact theory exercise present
evidence time various relevant
evaluate ethics analyze group
influence acquire quantitative major
able range example final
follow relate practical experience
goal negotiation introduce review

Acknowledgements

The research team would like to thank the individuals and organisations who generously shared their time, experience, and materials for this project. The work has been supported by the Science for RE-designing Science, Technology, and Innovation Policy (SciREX) Programme in Japan. The views and opinions expressed here are solely those of the authors and do not represent in any way those of the institutions to which they are affiliated.

References

  • A. Okamura, S. Hayashi, H. Koshiba and Y. Nishimura: "Mapping the educational content of the science of science, technology and innovation policy: an international comparison", Proc. 23rd International Conference on Science and Technology Indicators(STI2018), Leiden, The Nehterlands (2018) Download

Contact

  • E-mail: scirexcorecontent [at] grips.ac.jp