Challenges and opportunities in research evaluation: toward a better evaluation environment
1. Challenges and opportunities in research
evaluation: Toward a better evaluation
environment
Sergio Benedetto
Consiglio Direttivo ANVUR
sergio.benedetto@anvur.org
Barcelona, May 18, 2015
3. 3
Research evaluation
Ex ante Ex post
before research takes place, to assess its
potential relevance, the prospects of
success and the cost appropriateness
after research has been concluded, to
assess its results in terms of scientific
quality and impact
Comparative Individual
aimed at defining a ranking of
individuals, research groups or
HEIs, often within a
homogeneous area of research
comparing qualification against
a threshold to promote or not
individuals, research groups
4. National research assessments
• What? …..Evaluated objects…
• Why? …..Goals…
• How?....Evaluation methodologies…
• When?....Continuity, frequency…
• With what consequences?..... On institutions, on
researchers, on society…
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6. • The volume of the scientific outcomes
• Their quality
• Their scientific impact
• Their impacts on the economy, society and/or culture
• More in general, the so-called “third mission” of HEIs, i.e. their
involvement with society at large
Objects of research evaluation
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8. To inform HEI government bodies and other stakeholders about
the status of national research
To help Ministry of Education and Research (or other national
bodies) distributing resources to HEIs
To help HEI government bodies taking strategic decisions to
improve the quality and effectiveness of research and in internal
resource (positions, funds) assignment
Goals of comparative research evaluation
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12. RAE-REF in UK: 1986, 1989, 1992, 1996, 2001, 2008, 2014
VTR-VQR in Italy: 2006, 2013, 2017 (?)
ERA in Australia: 2010, 2012, 2015
The period of research evaluation
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3 43 5 7 6
7 4
2 3
14. No measuring technique leaves the measured object
unaffected, so:
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• What are the intended consequences?
• Evaluation leads to an improvement in the quality of research (UK: Adams
& Gurney, 2010, Australia: Butler, 2003)
• Evaluation modifies dissemination channels, e.g., it makes the journal
article published in highly ranked journals the main publication outlet (Rin,
2009)
• Resources distribution to HEI based on assessment outcomes (UK, Italy,…)
• Improved HEIs infrastructure and archival repositories
• Enhanced “quality” recruitment
• Strategic positioning and more consistent policies
• Trust from society
15. No measuring technique leaves the measured object
unaffected, so:
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• What could be the risks and unintended consequences?
• Worse publication practices: excessive segmentation of the
research results, clinging to the mainstream, safe disciplinary
research, citation stacking , coercive citation, ...)
• Research freedom limitation: too much emphasis on
accountability
• Underestimating the teaching activity (J. Warner, 1998)
• Misuse of assessment outcomes: evaluating individuals, apply
national-level criteria automatically to local issues
• …
16. • Collecting data and objects:
– Local (often incompatible) repositories
– Copyright issues
• Cleaning data:
– Human errors in uploading
– Names ambiguity
– Duplicated records
• Connecting data to “owners”:
– Researchers, institutions
• Transferring data and objects to evaluators (panels, peer reviewers,…)
– IP protection, “big data” issues
Research evaluation: The challenges
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17. • What to evaluate and how to evaluate strictly depend on
• Size: Individuals, research groups, departments, institutions
• Scientific field: Hard and life sciences, social sciences and humanities
• Goal:
– Performance-based HEIs funding (to enhance average or excellence
performance?)
– Improve HEI-industry collaboration
– Incentivize social impact of research
– …
Research evaluation: The challenges
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18. • Input indicators measure resources, human, physical and financial, devoted to research
– Typical examples are the number of (academic) staff employed or revenues such as
competitive, project funding for research
• Process indicators measure how research is conducted, including its management and
evaluation
– A typical example is the total of human resources employed by university departments,
offices or affiliated agencies to support and fulfill technology transfer activities
• Output indicators measure the quantity of research products
– Typical examples are the number of papers published or the number of PhDs delivered
• Outcome indicators relate to a level of performance, or achievement, for instance the
contribution research makes to the advancement of scientific‐scholarly knowledge
• Impact and benefits refers to the contribution of research outcomes for society, culture, the
environment and/or the economy
Research evaluation: Indicators
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19. The quality of a publication is an elusive attribute
Research evaluation: Outcome indicators
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Measured through proxies
Quantitative: Bibliometric indicators Qualitative: Peers’ opinion
20. The bibliometric evaluation
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Based on measurable indicators of publication impact:
• The “quality” (the peer review ex-ante process, the acceptance ratio,…) and the
number of citations of the journal (Impact Factor, Eigen Factor, Source normalized
impact per paper (SNIP) , …)
• The number of citations of the article
• The number of citations of the author (h index and related indicators)
• Alternative scholarly impact metrics (altmetrics), which cover other aspects of the
impact of a work, such as
– how many data and knowledge bases refer to it
– article views
– artcile downloads
– mentions in social media and news media
21. (a) Normative theory of citations
- Citation as recognition of scientific value (Smith, 1981, Merton, 1988)
(b) Constructivist social theory of citations
- Citation as act of academic deference
- Citation as attempt at persuading (Gilbert, 1977)
- Assertive citation (Moed and Garfield, 2004)
- Citation as simple discourse articulation (Crossick, 2007)
The citational behaviour
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“The main point which emerges is that citations stand at the intersection between two systems:
a rhetorical (conceptual, cognitive) system, through which scientists try to persuade each other
of their knowledge claims; and a reward (recognition, reputation) system, through which credit
for achievements is allocated” (Cozzens, 1989)
22. • The reliability of bibliometric indicators tends to decrease with the size of samples
they are applied to (institutions, department, research groups, individuals)
• Never confuse the impact of journals with the impact of articles they publish
(skewness of citations distribution)
• Use of a plurality of indicators (e.g., at journal level: IF, Article influence,
Eigenfactor, SJR, SNIP, …) reduces risks of manipulation: self-citation, citation
stacking,…
• Always normalize within a coherent, uniform scientific area wrt traditions of
publishing and citing
The bibliometric evaluation
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23. Pros
• Efficient
• Fast
• Economic
• Not intrusive
• Objective
• Helps in identifying the origin and impact of scientific theories
Cons
• Different citational behaviours among disciplines and publication type (books vs articles)
• Self citations
• Data bases transparency and pitfalls
• Differences between OA and non-OA journals
• Language of publication
The bibliometric evaluation
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24. • The “quality” of a publication cannot be assessed through
quantitative measures, just like the beauty of human beings or
artworks
• Can we assess the beauty of Leonardo’s Gioconda from the number
of tickets sold at Louvre or from the average time spent by visitors in
front of the painting?
• These are the arguments of those affirming the supremacy of peer
review against bibliometrics
The bibliometric evaluation
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25. • Is the peer review the solution?
• Citing Richard Horton, editor of Lancet
“The mistake, of course, is to have thought that peer review was any more than a crude
means of discovering the acceptability—not the validity—of a new finding. Editors
and scientists alike insist on the pivotal importance of peer review. We portray peer
review to the public as a quasi-sacred process that helps to make science our most
objective truth teller. But we know that the system of peer review is biased,
unjust, unaccountable, incomplete, easily fixed, often insulting, usually
ignorant, occasionally foolish, and frequently wrong”
The peer review evaluation
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26. • In several scientific areas a significant correlation has been found between
bibliometric indicators and peer review evaluations
• Italian VTE 2001-2003
- 9 areas of hard science and economics: High correlation (Franceschet, 2009)
• Italian VQR 2004-2010
– Hard and life science and economics: Higher correlation between bibliometrics and
peer review thank between the two peer reviews of the same article (Benedetto, 2013)
• Research Assessment Exercise (RAE) 1992 (UK)
- Genetics, anatomy, archeology: High correlation (Holmes & Oppenheim, 2001)
• Research Assessment Exercise (RAE) 2001 (UK)
- Psicology - Correlazione equal to 0.86 (Smith and Eysenck, 2002)
Bibliometrics and peer review
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27. Bibliometric indicators, based on indexing international journals, mainly written in
English, and on extracting citational indicators, are not reliable in SSH
Challenges in research evaluation in SSH
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How about peer review?
Publications characteristics make peer review even more difficult and less
reliable in SSH:
• Research outcomes difficult to be made objective and comparable
• Belonging bias (different schools of thought, …)
• Reduced number of potential peers (niche disciplines, marginal publication
language,…)
28. Journal classifications in SSH:
• Who does it?
• How is it done?
• How many classes?
• For what?
• Four examples:
– The ranking of Australian Research Council (2008)
– The ranking of European Science Foundation (ERIH project,
2007-2008)
– The ranking of AERES (2008)
– The ranking of ANVUR within the National Research Habilitation
Challenges in research evaluation in SSH
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29. A tsunami of criticisms…
• UK historians: “crude and oversimplified”
• A set of journals classified in th best class A requested to be
cancelled from the ESF-ERIH lists
• Petition to AERES to withdraw the lists: “non transparent criteria”
• The ARC classification of ARC became an electoral issue in
Australia, and the new government declared it over
• Increased degree of acceptance after initial resistance in Italy
Journal classification in SSH
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30. • Journal classification in SSH as a rough quantisation of the continuous ranking
induced by impact factor in hard and life sciences
• Journal IF is based on average number of citations received by published articles
in a period of time (2 or 5 years): it generates a continuous ranking of journals
within a homogenous scientific area
• Journal classification in SSH has a similar objective, but needs different
classification criteria, mainly of qualitative nature, and is limited to a small number
of classes (typically 2-3): it is a bridge between peer review and bibliometrics
• Since the number of citations is missing, journal classification cannot fully replace
peer review
Journal classification in SSH
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31. • Different kind of research outputs beyond journal articles:
– Books
– Book chapters
– Translations
– Notes to court rulings (for law disciplines)
– Exhibitions and their catalogues
– Architectural designs
– Archeological excavations
– Artistic performance
– …
Challenges in research evaluation in SSH
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32. Books evaluation
• Explore the feasibility of publishers classification (Spain)
• Use of indicators such as:
– Reviews on international journals
– Characteristics of the publishing series:
• Existence of an editorial board
• Transparent review procedures governing the decision to publish
• International diffusion of the publisher nooks
• …
Challenges in research evaluation in SSH
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33. • Avoid global rankings of institutions based on a single score
aggregating many different indicators
• Use a multidimensional approach based on five steps1:
– Define the purpose and audience of the research assessment
– Involve institutions to be evaluated in step 1
– Identify the appropriate indicators
– Perform the assessment
– Identify the range of actions and decisions to be taken after assessment
1. Assessing Europe’s university-based research, Final Report of the Expert Group on Assessment of University-based
Research, 2010, http://ec.europa.eu/research/science-society/document_library/pdf_06/assessing-europe-university-
based-research_en.pdf
Toward an ideal evaluation environment
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34. • A crucial first step is the availability of a national data base of researchers with
the list of their publications and other relevant information (research contracts,
awards, editorial responsibilities,…)
• An excellent example is the “Plataforma Lattes” in Brasil (http://lattes.cnpq.br)
• A bad example is the “Anagrafe nazionale della ricerca (ANPRePS) in Italy,
prescribed by a law in 2009 and never implemented
• The publications metadata records should be linked to the pdf of the
publications (taking into account copyright issues when relevant)
Toward an ideal evaluation environment
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35. • All researchers should be uniquely identifiable through a single identifier,
linking the researcher to his/her publications and other information
• Use of ORCID identifier is one viable solution:
Non-profit organisation supported by members (majority of hem non-profit
organisations)
Free to individuals
Growing adoption: Sweden, Finland, Denmark, Norway, UK, Spain,
Portugal, Australia
• Italy launched recently the I.R.ID.E project, aiming at providing an ORCID
identifier to 80% of researchers by the end of 2016
Toward an ideal evaluation environment
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36. • Local assessment in Institutions should be performed more frequently (yearly?) to
provide bridge between national assessments (4-5 years period)
• Local assessment must consider a wider range of context variables:
– The critical mass of research groups
– The strategic promotion of some areas
– The opening of new research frontiers, e.g., interdisciplinary
• National and local research assessments must be coordinated, to present
researchers with a coherent set of goals and incentives
Toward an ideal evaluation environment
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37. • Research assessments must include an indicator of the performance variation with
time, so as to reward improvement even when the absolute performance is still
poor
• This implies a certain degree of persistence of indicators
• The evaluation of research outputs should use an informed peer review
methodology, where the panel in charge acquires information from:
Biliometrics
Expert peers
…
to make the final decision
Toward an ideal evaluation environment
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38. • To be effective, research assessment must be a shared experience in goals and
methodologies between evaluators and evaluated
• Evaluation criteria must be known a priori
• The evaluation results should not be applied to different contexts wrt the initial ones
Outcomes evaluations addressed to institutional performance should never be used to
assess individuals
• Performance-based funding should not erode the institution survival quota
• Assessment methodology should not underestimate the inter (multi) disciplinary
research
A few final hints
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39. If you cannot measure it, you cannot improve it. Lord Kelvin
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Not everything that can be counted counts, and not everything
that counts can be counted. William B. Cameron, Informal
Sociology: “A Casual Introduction to Sociological Thinking” (1963)