Science-for-policy ecosystems through the eyes of professionals : a multi country survey analysis.
Date: 2024-11-22
Institutions: Joint Research Centre
Subjects: EU Member State, EU research policy, knowledge transfer, policymaking, research report, sample survey, scientific research

ISSN 1831-9424 

Science-for-policy ecosystems through the 
eyes of professionals 

A multi country survey analysis 

Scharfbillig, M., Krieger, K., Melchor Fernandez, L., 
Almeida, M., Mayer, M.S., Cannata, G. 

2024 

 EUR 40091 

 
 
  
This  document  is  a  publication  by  the  Joint  Research  Centre  (JRC),  the  European  Commission’s  science  and  knowledge 
service. It aims to provide evidence-based scientific support to the European policymaking process. The contents of this 
publication do not necessarily reflect the position or opinion of the European Commission. Neither the European Commission 
nor any person acting on behalf of the Commission is responsible for the use that might be made of this publication. For 
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presentation of material on the maps do not imply the expression of any opinion whatsoever on the part of the European 
Union concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation 
of its frontiers or boundaries. 

Contact information  
Name: Mario Scharfbillig 
Email: JRC-E4P-ECOSYSTEM@ec.europa.eu 

EU Science Hub 
https://joint-research-centre.ec.europa.eu 

JRC139213 

EUR 40091 

PDF  

ISBN 978-92-68-21386-5   ISSN 1831-9424   doi:10.2760/7490500  

KJ-01-24-104-EN-N 

Luxembourg: Publications Office of the European Union, 2024  

© European Union, 2024  

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How to cite this report: European Commission, Joint Research Centre, Scharfbillig, M., Krieger, K., Melchor Fernandez, L., Almeida, M., Mayer, 
M.S. and Cannata, G., Science-for-policy ecosystems through the eyes of professionals, Publications Office of the European Union, Luxembourg, 
2024, https://data.europa.eu/doi/10.2760/7490500, JRC139213. 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Contents 

Abstract ....................................................................................................................................................................................................................................................................... 2 

Executive summary .......................................................................................................................................................................................................................................... 3 

1.  Introduction..................................................................................................................................................................................................................................................... 5 

2.  Methodology .................................................................................................................................................................................................................................................. 9 

3.  Results and discussion ...................................................................................................................................................................................................................... 12 

3.1.  Shared problems related to the quality of science for policy in Member States ....................................................... 12 

3.1.1. 

Sample description ............................................................................................................................................................................................... 12 

3.1.2. 

Lack of meeting opportunities and ecosystem fragmentation .................................................................................. 13 

3.1.3. 

Patterns in professionals’ perceptions based on correlation analysis ................................................................ 15 

3.1.4.  Multiple challenges across science for policy ecosystems: embracing a holistic perspective ..... 17 

3.2.  Variation in professional groups’ perceptions of problems ............................................................................................................. 18 

3.3.  Variation in perceptions of problems by country: a six-country comparison.................................................................. 22 

4.  Conclusions and outlook ................................................................................................................................................................................................................. 27 

References ............................................................................................................................................................................................................................................................. 29 

List of abbreviations .................................................................................................................................................................................................................................... 33 

List of figures ..................................................................................................................................................................................................................................................... 34 

List of tables ........................................................................................................................................................................................................................................................ 35 

Annexes .................................................................................................................................................................................................................................................................... 36 

Annex 1. Questionnaire ..................................................................................................................................................................................................................... 36 

Annex 2. Further analyses ............................................................................................................................................................................................................. 39 

 1 

 
 
 
 
 
 
 
 
 
Abstract 

This Joint Research Centre science for policy (S4P) report explores the perceived challenges for establishing and maintaining 
a well-functioning science–policy interface in the EU. To gather this information, a survey was conducted with around 500 
S4P professionals from 22 EU Member States. Respondents to the survey identified a fragmented S4P ecosystem and lack 
of meeting opportunities as the main challenges for effective collaboration between policymakers and scientists. There is a 
general readiness to provide and utilise scientific knowledge, but the lack of a systematic approach to bring both sides 
together seems to hinder this process. The results point to substantive agreement across professional groups (knowledge 
producers, users and brokers) on the need for improvements, in particular concerning better skills, knowledge translation 
capacities  and  institutional  support,  to  enhance  S4P  ecosystems.  The  limited  sample  size  of  the  survey  and  the  non-
probabilistic sampling strategy employed means that the data do not show a fully representative view of European S4P 
professionals’ perspectives. Yet, they provide an entry point for exploring and guiding future perspectives of European S4P 
ecosystems. The report’s findings provide valuable insights for national and EU policy discussions on enhancing the use of 
science in policymaking, which can concretely help guide efforts to support S4P ecosystem-building activities, enhancing the 
translation capacities of scientists and knowledge brokers, and increasing the skills and competences of policymakers. The 
report also contributes to the European Commission’s recent initiatives to strengthen the connections between policymaking 
and scientific communities, as seen in the emerging research and public administration policies. 

Acknowledgements 

The authors would like to thank the numerous participants in the survey as well as attendees of the series of workshops 
entitled ‘Connecting and strengthening science for policy ecosystems across the EU’ delivered by the Joint Research Centre 
since 2020. 

The authors also wish to thank Agnieszka Gadzina-Kolodziejska, Lene Topp, Laura Smillie, Julian Keimer and David Mair in 
the Science for Democracy and Evidence-Informed Policymaking Unit for their support and intellectual input in many regular 
discussions around evidence-informed policymaking, as well as two anonymous reviewers from the JRC Editorial Review 
Board. 

Authors 

Mario Scharfbillig, PhD 

Kristian Krieger, PhD 

Lorenzo Melchor, PhD 

Mara  Almeida, PhD 

Marie Sophie Mayer 

Giuseppe Cannata 

 2 

 
 
 
 
 
Executive summary 

Policy context 

Policymaking  is  a  formidable  task.  Accurately  describing  and  effectively  tackling  the  ‘wicked’  and  complex 
problems the world is currently facing, such as climate change, biodiversity loss, global pandemics, societal 
polarisation and the challenge of artificial intelligence, requires unprecedented levels of scientific knowledge 
and expertise. 

The demand for a better use of science for policy (S4P) is widely recognised by Europe’s citizens. Almost 7 out 
of  10  Europeans –  according  to  a  Special  Eurobarometer  survey  from  2021 –  agree  that  scientists  should 
intervene in political debates to ensure that policies are based on scientific evidence (European Commission: 
Directorate-General  for  Communication,  2021).  This  demand  is  reflected  in  evolving  policy  frameworks  and 
institutional  configurations  at  the  EU  level  that  shape  the  production,  transmission,  absorption  and  use  of 
scientific knowledge for policymaking. 

Recent  efforts  in  this  regard  include  the  revamping  of  the  ‘Better  Regulation’  agenda,  which  defines  the 
overarching framework for EU policymaking (European Commission 2023a). In a communication introducing an 
update of the Better Regulation guidelines and toolbox, the Commission identified scientific evidence as ‘vital 
to  establishing  an  accurate  description  of  the  problem,  a  real  understanding  of  causality  and  therefore 
intervention logic; and to evaluate impact’ (European Commission, 2021a). 

Likewise, a Commission Staff Working Document (SWD), developing a vision on ‘public administration for the 
present and the future’, states that ‘a systematic consideration of scientific knowledge enables governments 
and public administrations, for example, to define and analyse policy challenges from multiple perspectives […], 
and  develop  a  set  of  policy  options  based  on  multi-disciplinary  scientific  input  […].  To  ensure  that  scientific 
knowledge  informs  public  policies  and  services,  robust  structures,  procedures,  and  competences  need  to  be 
further developed and connected at all levels of public administrations and policymaking […] and to provide 
training opportunities in data literacy to policymakers’ (European Commission, 2021c). 

This evolution on the knowledge-user  side is also reflected in the  policies shaping knowledge  production. In 
December 2020, the Council of the European Union adopted its conclusions on the relaunch of the European 
Research Area (ERA), stating that Research and Innovation (R & I) activities are an ‘essential input to address 
societal challenges and constituting a cornerstone of value- and evidence-based policymaking and thus of our 
European democracies’ (Council of the European Union, 2020). This emerging policy on knowledge valorisation 
includes the uptake of scientific knowledge in policymaking. In parallel, the European Commission called on EU 
Member  States,  policymakers  and  other  relevant  stakeholders  to  ‘strengthen  structures,  processes,  and 
practices in the use of research results and scientific knowledge for designing and implementing public policy’ 
(European Commission, 2022a). This is also reflected in the Public Administration Skills Agenda launched by the 
Commission communication on ‘Enhancing the European Administrative Space (ComPAct)’, which emphasises 
the need to build more resilient, attractive, transparent and high-performing public administrations in Member 
States, including through developing tools and skills to make use of scientific knowledge and evidence (European 
Commission, 2023b). Finally, bringing demand and supply sides together and complementing them by a special 
interest  in  ‘boundary-spanning’  organisations,  the  Commission  has  published  a  SWD  on  supporting  and 
connecting policymaking in the Member States with scientific research (European Commission, 2022b), which 
builds also on the preliminary insights from the survey discussed in depth in this report. 

All  this  work  is  part  of  a  wider  European  discussion  on  how  to  make  better  use  of  scientific  knowledge  in 
policymaking. These discussions have recently been taken up in Council conclusions on strengthening the role 
and impact of R & I, which emphasise ‘that all fields of science, including social sciences and humanities, by 
producing evidence-based knowledge, should play a more significant role in the policymaking process for the 
identification of political challenges, the analysis of the state of the art, the framing of the solutions. (Council 
of the European Union, 2023). 

This Joint Research Centre (JRC) science for policy (S4P) report builds atop of these initiatives, providing relevant 
evidence  to  inform  ongoing  policy  discussions,  at  both  the  national  and  European  levels,  on  the  challenges 

 3 

related to establishing and maintaining a well-functioning interface and building a European S4P ecosystem ( 1). 
It does so by surveying policymakers, scientists and knowledge brokers from several Member States in the EU 
with experience at the S4P interface, asking them what they perceive as the main challenges in building a better 
functioning S4P ecosystem. Results from this survey, while only partially representative of the wide range of 
institutions  and  organisations  involved  in  the  emerging  European  S4P  ecosystem,  are  discussed  and 
contextualised to provide an initial assessment of the qualities of these ecosystems. Despite the limited reach 
of the survey conducted, the report paves the way for more systematic efforts to map the S4P ecosystems 
within and across the EU to better understand their qualities and related challenges. 

Main findings 

Around 500 S4P professionals from 22 Member States responded to the JRC survey on the qualities of science 
for  policy  ecosystems,  which  aimed  to  identify  needs  and  gaps  preventing  the  effective  functioning  of  the 
science–policy interface. These professionals belong to knowledge-producer, knowledge-user and knowledge-
bridging  organisations,  thus  rendering  this  survey  a  unique  source  of  evidence  that  takes  into  account  the 
multiple perspectives involved in S4P activities in Member States. Building on these data and ongoing work at 
the JRC, this report offers an exploratory analysis of the qualities of S4P ecosystems and of existing challenges 
at the science–policy interface, through the eyes of S4P professionals. 

Overall, the professionals surveyed agree on the existence of crucial challenges in S4P ecosystems, reflected 
in widely shared perceptions that certain ‘qualities of science for policy systems’ are lacking. The most important 
issue for S4P professionals is lack of meeting opportunities between producers and users and a fragmented 
S4P ecosystem. There is a readiness on all sides to provide and utilise scientific knowledge, which seems to be 
hampered by a lack of a systematic approach to bringing both sides together. 

Closely  behind  the  fragmented  ecosystem  and  lack  of  meeting  opportunities  comes  the  perceptions  that 
policymakers face political constraints in what they can take on board, that policymakers lack skills for science 
uptake and, on the other hand, that science is often not fit for purpose. System-building activities should be 
supported  by  work  on  the  translation  abilities  of  scientists  or  knowledge  brokers,  as  well  as  the  absorptive 
capacity and skills of policymakers. 

In  addition,  when  zooming  in  on  professional  sectors,  whether  knowledge-producer,  knowledge-user  or 
knowledge-brokering organisations, the responses to our survey remained largely consistent, showing general 
consensus  among  respondents  about  the  need  for  a  better  S4P  ecosystem.  Nevertheless,  there  are  some 
statistically significant differences among the professional types, notably with knowledge-broker professionals 
having the most critical perspective of the functioning of the S4P ecosystem. At the country level, discrepancies 
between professionals’ responses were larger, but given the small sample sizes more evidence would be needed 
to  support  this  conclusion.  Due  to  the  specific  circumstances  under  which  the  survey  was  carried  out,  the 
distribution  of  national  affiliations  in  the  sample  is  somewhat  unbalanced,  with  a  strong  prevalence  of 
respondents from a few countries, inviting some caution in interpreting cross-country pattens. 

Related and future Joint Research Centre work 

This report contributes to a better understanding of S4P professionals’ perceptions of needs and challenges in 
terms of the normative foundations and institutional underpinnings of S4P ecosystems, as well as the skills and 
competences needed and the mechanisms for better connecting actors and organisations in both research and 
public administrations. These results have informed the European Commission’s actions on S4P, such as  its 
production of a SWD on supporting and connecting policymaking in the Member States with scientific research 
(European  Commission,  2022b).  They  also  attest  the  relevance  of  JRC’s  work  on  evidence-informed 
policymaking, both at the EU level and in Member States, and can inform further actions to strengthen national 
ecosystems.  At  the  same  time,  the  report  paves  the  way  for  further  research  and  actions  in  relation  to 
consolidating the European S4P ecosystem. 

(1) 

As defined in Commission staff working document – Supporting and connecting policymaking in the Member States with scientific 
research (SWD(2022) 346 final), an S4P ecosystem is a complex of organisational structures and entities, processes and networks 
that  interact  to  support  the  mobilisation,  acquisition,  synthesis,  translation,  presentation  for  use  and  application  of  scientific 
knowledge in policymaking processes. 

 4 

 
1.  Introduction 

Today’s policy problems are complex and multifaceted, with far-reaching implications across various sectors 
and  policy  fields.  Issues  such  as  the  global  COVID-19  pandemic,  climate  and  environmental  emergencies, 
advances  in  artificial  intelligence  and  other  technologies,  and  the  global  expansion  of  divisive  social  media 
platforms – and with it increased societal polarisation – all have profound implications across many sectors, 
policy  fields,  and  socioeconomic,  professional  and  demographic  groups.  To  respond  to  these  challenges 
effectively,  governments  and  public  administrations  need  to  mobilise  significant  analytical  and  knowledge 
resources. 

However, much of the knowledge and analytical capacity is situated outside administrations. In fact, scholars 
have observed a declining analytical capacity of public administrations and an increasing trend towards the 
externalisation of science advice provision, associated with different factors, including public sector reforms 
and  reduced  budgets,  attempts  by  politicians  to  impose  greater  control  over  bureaucracies  by  diversifying 
knowledge inputs, and the emergence of ‘wicked’ problems that have undermined the perceived capacities of 
internal advisory systems to provide solutions (Craft and Howlett, 2013). 

While  relevant  knowledge  can  be  found  in  many  organisations  and  professions  (e.g.  industry  bodies,  non-
government  advocacy  organisations,  professional  associations,  learned  societies),  a  special  role  has  been 
assigned in policy debates (European Commission, 2021a, b, c) and academic research (Pielke, 2007; Gluckman, 
2014; Cairney, 2016; Parkhurst, 2017) to high-quality scientific knowledge. 

Scientific  knowledge  is  understood  as  all  knowledge  (data,  information,  etc.)  that  is  available  and  has  been 
tested through the use of scientific methods. Its production involves gathering knowledge from all disciplines 
of sciences (including social sciences and humanities), obtained through a process based on methodological 
rigour, agreed rules of enquiry, systematic search for evidence and continuous review and debate; in fact, claims 
are  subject  to  peer  review  before  being  made  publicly  available  and  open  for  scrutiny  and  processes  of 
verification or falsification. Although methods for gathering knowledge should be systematic and valid across 
contexts, they can also be case specific and context dependent (SAPEA, 2019). Looking at the EU Member States, 
the capacity to produce scientific knowledge is impressive. In the EU, there are almost 1.9 million researchers, 
and the EU’s share of global scientific publications was 21 % in 2020, including a large share of the top 1 % 
highly cited scientific publications. 

Dealing  with  wicked  problems,  which  are  by  definition  hard  to  fully  analyse  and  where  scientific  evidence 
provides only limited insights into the many dimensions involved, requires even more careful consideration of 
the evidentiary basis that informs and supports policymaking. Scientific evidence in this context could be better 
seen as speaking to, rather than a substitute for, controversies in society about the right way of policymaking 
(Daviter, 2019). Therefore, there is a need for better interactions between scientists and policymakers, allowing 
for the contestation, updating and enhancing of evidence-informed policymaking to go beyond the linear model 
of knowledge uptake. 

Given this capacity of scientific communities, the increasing demand for analytical and scientific expertise by 
policymakers and the need for interaction on complex policy challenges, it is important to examine if and if so 
how  effectively  policymakers  can  make  use  of  science  in  policymaking  processes,  and  what  the  potential 
challenges are at the science–policy interface. 

Potential challenges have been presented from different conceptual perspectives. 

of 

technocracy 

—  From  the  normative  democracy  theory  perspective,  there  are  concerns  about  the  democratic 
accountability 
the 
(Habermas,  1973;  Bertsou 
scientisation/depoliticisation  of  politics  (Weingart,  1999;  Christensen  and  Lægried,  2022),  conflict  of 
interests  in  the  use(s)  of  science,  and  stealth  advocacy  issues  and  their  potential  impact  on  regulatory 
affairs (Jasanoff, 1990; Pielke, 2007). Furthermore, studies embracing this perspective have emphasised 
a lack of deliberative democratic systems in place that ensure sufficient openness and diversity of scientific 
and non-scientific views for informing policymaking processes (Parkinson and Mannsbridge, 2012; Moore, 
2018). 

Caramani,  2020), 

and 

—  From a problem-driven perspective, many complex societal problems are ‘wicked’ issues, where values 
and facts are often entangled, science about their causes and potential solutions uncertain, and political 
stakes large. This limits the capacity of science in its traditional form to be useful and calls for post-normal 
science, which is based on the transdisciplinarity and democratisation of science (Funtowicz and Ravetz, 
1993; Renn, 2021). The issue can also be seen through a lens of problem structuredness and (political) 
distance between the scientific evidence generation and the overarching problem, such that the need for 

 5 

partitioning  of  a  policy  problem  in  solvable  smaller  problems  is  itself  a  political  action  (Peters,  2017; 
Turnbull and Hoppe, 2019). 

—  From  an  institutionalist  perspective,  scholars  point  to  the  existence  of  ‘two  communities’  (Caplan, 
1979) –  the  scientific  and  policymaking  communities –  which  tend  to  operate  with  different  ‘cultures’, 
incentives, processes and objectives. This divergence in logic of operation would also explain fundamental 
misunderstandings  of  policymaking  among  those  operating/analysing  at  the  science–policy  interface, 
including  simplified  assumptions  from  the  scientific  community  around  cognitive  and  institutional 
processes  involved  in  policymaking  (Oliver  and  Cairney,  2019;  Strand,  2022).  Likewise,  public 
administrations  also  need  an  evidence-based  culture,  calling  for  administrations  that  are  open  to  the 
evaluation of, experimentation with and use of scientific knowledge, as well as data-driven policymaking, 
all of which could improve the forward-looking policymaking behaviour of administrations in areas where 
scientific  knowledge  is  scarce  or  undetermined  (Global  Commission  on  Evidence  to  Address  Societal 
Challenges, 2022). 

Several  of  the  challenges  at  the  science–policy  interface,  considered  on  a  more  conceptual  level,  can  be 
assumed to manifest themselves along interconnected dimensions. Building on existing literature and insights 
from hands-on exchanges with science for policy (S4P) professionals, this report analyses four main dimensions 
or ‘qualities’ of S4P ecosystems. 

1)  Productive  interactions.  Does  the  S4P  ecosystem  have  the  qualities  needed  to  deliver  the  right 

inputs for S4P? 

Challenges in this area concern the logistics of the engagement between the knowledge producers and 
users (Budtz Pedersen and Hvidtfeldt, 2021; Budtz Pedersen, 2023). Relevant questions in this regard 
are centred around whether research needs are formulated clearly and whether science can deliver on 
policymakers’ demands of knowledge for policy. 

2) 

Individual  competences.  Does  the  S4P  ecosystem  have  the  qualities  needed  to  ensure  that 
policymakers and scientists have (or can develop) the right competences (knowledge, skills, attitudes)? 

The key challenges in this area involve core competences of individuals at the science–policy interface. 
Do scientists produce information on time and in the right format? Is scientific knowledge presented in 
a  manner  useful  for  policy  use?  Are  policymakers  asking  relevant  questions  to  scientists?  Are 
policymakers consulting a sufficiently broad/diverse knowledge body as well as stakeholders? 

3) 

Institutions  and  resources.  Does  the  S4P  ecosystem  have  the  qualities  needed  to  provide 
institutional and resource support? 

As S4P requires a deeper engagement between knowledge producers and users, for S4P activities to 
respond  to  problems  that  are  increasingly  less  structured,  more  wicked  or  happening  at  a  further 
distance from decision-making, a crucial challenge concerns the existence of an enabling institutional 
set-up (Budtz Pedersen, 2014; SAPEA,  2019). Such institutional structures need to be  supported by 
adequate resources, allowing policymakers, scientists and knowledge brokers to interact sufficiently 
well. 

4)  Normative foundations. Does the S4P ecosystem have the qualities needed to promote advice that 

recognises and promotes the democratic policymaking processes? 

Recognising the complexity of today’s problems requires more than the coordination of a plurality of 
actors, knowledge bodies and processes. From this perspective, key questions concern the rules and 
principles underlying science–policy interactions, as well as the issue of trust within S4P ecosystems. 
This  touches  on  aspects  of  sectoral  specificities  that  may  interfere  with  (or  strengthen)  such 
interactions  (e.g.  the  ‘politics’  on  the  policy  side,  questions  of  independence  and  incentives  on  the 
science  side),  trust  and  mutual  appreciation  between  the  communities,  and  each  community’s 
familiarity with the other (Douglas, 2009). 

These four dimensions focus on the idea that the scientific and the policymaking communities are respectively 
providing and using evidence directly. While interactions at the science–policy interface are often conceived in 
terms  of  these  two  broad  communities,  recent  research  points  towards  an  important  third  type  of  actor, 
variously  defined  as  knowledge  brokers,  intermediary  organisations  or  boundary  spanners.  Productive 
interactions  can  be  mostly  addressed  together  with  the  improving  competences  dimension  within  each 
community  (Schwendinger  et  al.,  2022).  Addressing  institutions  and  resource  challenges,  however,  concerns 
building  institutional  bridges  between  key  players  (Gluckman  et  al.,  2021),  creating  boundary  organisations 

 6 

(Guston,  2001)  and  professionalising  ‘boundary  spanners’  or  ‘honest  brokers’  (Pielke,  2007;  Bednarek  et  al., 
2018;  Neal  et  al.,  2022).  The  issue  of  normative  foundations,  instead,  calls  for  a  broader  reflection  on  the 
underlying values and rationale for evidence-informed policymaking. Acting on normative foundations requires 
developing an approach to the good governance of evidence use (Parkhurst, 2017), which should always be 
seen as embedded in democracy, requiring contestation not only from within, on the technocratic side, but also 
from  an  ethical  and  values  perspective  (Douglas,  2009;  Scharfbillig  et  al.,  2021).  All  these  elements  can 
facilitate common understanding, mutual learning and co-creation for research projects, to cover policy needs 
or evidence gaps and make policymaking processes more responsive to citizens’ needs and more resilient to 
the effects of fake news and misinformation (Smillie and Scharfbillig, 2024). 

Some scholars have assessed the qualities of the science–policy interface by analysing either the supply side 
of evidence or scientific advice (Howlett, 2019) or the demand side (Manwaring, 2019). However, few studies 
have explored the views/perceptions or experiences of those working on both sides and across the boundaries 
of the S4P ecosystem or policy advisory systems to discern the qualities they have and challenges they face. 
Existing analyses of the interplay between academics and policymakers in Belgium and Germany (Pattyn et al., 
2022) and the United Kingdom (Talbot and Talbot, 2014) underline the value of new institutional arrangements 
and increasing trends of the pluralisation, professionalisation and politicisation of policy advice. As these cases 
show,  there  is  much  to  learn  from  involving  both  sides  simultaneously,  rather  than  analysing  the  sides  in 
isolation. 

Furthermore, S4P practices and capacity involve a wide range of organisations that produce and use relevant 
services and outputs, including generating, requesting, synthesising, translating, transmitting, communicating, 
absorbing and using scientific knowledge for policymaking, as well as training and engaging the professional 
communities  involved/operating  at  the  science–policy  interface  (Spruijt  et  al.,  2014;  Gluckman  et  al.,  2021; 
Oliver, 2022) (Figure 1). 

Figure 1. Actors in the S4P ecosystem 

Source: Budtz Pedersen (2023). 

This  report  builds  on  the  S4P  capacity-building  initiatives  carried  out  by  the  Joint  Research  Centre  (JRC) ( 2), 
which included a number of interactive workshops, with the participation of high-level actors from the scientific 

(2) 

https://europa.eu/!rKdpjd.  

 7 

 
 
and  administrative  sides  in  several  countries (3)  and  the  publication  of  discussion  papers  mapping  the  S4P 
ecosystems in some of the participating countries, including Denmark (Budtz Pedersen and Hvidtfeldt, 2021), 
Greece (Ladi et al., 2022), France (Maxim, 2022), Portugal (Simões, 2022), and Spain (Cañibano and Real-Dato, 
2024). 

As part of these initiatives, the JRC conducted a survey based on an open call for participation, with almost 500 
professionals working at the science–policy interface responding from 22 Member States. This report describes 
the main findings of the survey and offers a timely contribution to the ongoing debate on the science–policy 
interface, exploring the perspectives of professionals on both the demand and supply sides in relation to the 
qualities, needs and challenges of different S4P ecosystems across Europe. While the sample set from each 
country  may  not  be  large  enough  to  be  representative,  meaning  that  a  cautious  approach  to  cross-country 
comparison is needed, perspectives from the supply, demand and brokerage sides can be compared with greater 
confidence. 

Questions  were  formulated  to  identify  the  views/perceptions  of  respondents  on  issues  related  to  the  S4P 
ecosystem that could be improved. To analyse the answers obtained, three approaches were used. 

1.  Describe common/shared problems. Explore descriptive patterns across the entire group of respondents 

to identify patterns of agreement on common/shared problems at the science–policy interface. 

2.  Compare perception among professionals. Compare perceptions between knowledge users, knowledge 

producers and other intermediary knowledge organisations (knowledge brokers) in their responses. 

3.  Compare  countries.  Compare  countries  to  identify  patterns  and  variations  in  problem  perceptions  to 
better inform capacity-building work and explore linkages between perceptions of problems and country-
specific settings of science and policy institutions. Note, however, that these results should be interpreted 
with caution due to the small number of responses per country. 

The report’s contribution is relevant at both the theoretical and practical levels. First, the report provides an 
initial assessment of S4P ecosystems, connecting the dots between the different actors’ perspectives on both 
the  supply  and  demand  sides,  as  well  as  the  perspectives  of  knowledge  brokers,  and  exploring  their 
interpretations of the main challenges and weaknesses of national S4P ecosystems. These data complement 
the quantitative indicators of S4P capacity (e.g. the OECD’s Better Regulation iReg indicators, human resource 
data of public administrations, and Eurostat research and development (R & D) statistics on the employment of 
R & D  staff)  through  mobilising  the  collective  intelligence  of  professionals  working  at  the  science–policy 
interface. Second, the analysis of the survey provides insights that may help prioritise investments and reform 
efforts,  in  particular  by  enabling  them  to  be  tailored  to  the  needs  of  the  science–policy  professionals  of 
individual countries and sectors. The initial assessment  presented in the  report  may also offer guidance for 
further research in this area. 

(3) 

A total of 15 workshops were held between September 2020 and September 2023, nine of which focused on the analysis of national 
S4P ecosystems, with the six remaining dealing with cross-cutting issues at the science–policy interface, such as legislative science 
advice,  governmental  science  advice,  the  role  of  universities  and  funding  sources.  More  information  is  available  online 
(https://europa.eu/!jW9NXq). 

 8 

 
2.  Methodology 

This  S4P  report  builds  on  the  analysis  of  an  online  survey  distributed  via  an  open  call  by  the  JRC (4)  to 
professionals  at  the  science–policy  interface  during  the  organisation  of  several,  including  country-specific, 
workshops ( 5).  This  call  was  widely  disseminated  on  social  media  via  institutional  channel  profiles  (mostly 
LinkedIn and Twitter). The answers were collected for 17 months, from January 2021 to May 2022. 

The  survey  (https://europa.eu/!GdHRK6)  was  organised  in  two  parts.  The  first  part  (‘About  you’)  included 
questions regarding nationality and professional activity. The second part (‘About the qualities of science for 
policy/advice  ecosystems’)  contained  20  statements  to  which  respondents  had  to  indicate  their  level  of 
agreement on a 1–5 Likert scale (strongly disagree (1), somewhat disagree (2), neither agree nor disagree (3), 
somewhat agree (4) and strongly agree (5)). Statements were linked to the four analytical dimensions previously 
mentioned:  productive  interactions,  individual  competences,  institutions  and  resources,  and  normative 
foundations (Table 1). 

For  the  purpose  of  empirical  analysis  and  to  better  identify  common  shared  problems  or  needs  across  the 
dataset, the statements that were phrased in positive terms (e.g. ‘Scientific knowledge is synthesised, translated 
and formatted in a way in the ecosystem that policymakers can use it easily’) were reverse coded to identify 
needs and gaps. 

(4) 
(5) 

General information (https://europa.eu/!RpBb4W) and the survey form (https://europa.eu/!GdHRK6) can be found online.  
Country-specific  workshops  were  held  for  Belgium,  Denmark,  Estonia,  Greece,  France,  Latvia,  Lithuania  and  Portugal.  More 
information is available online (https://europa.eu/!jW9NXq). Another workshop was held for Spain in 2023 as part of this series but 
the survey was no longer open for responses. 

 9 

 
Table 1. Survey dimensions and short versions and full-text versions of survey statements 

Dimension 

Short version 

Full-text statement 

Productive 
interactions 

Not the right question 

Science not timely 

Scientists receive questions from policymakers and knowledge brokers framed in such a way that they can provide useful evidence-informed 
inputs (rev) 
Scientific knowledge is often not available at the right moment in time to be useful for policymakers 

Science not fit for purp 

Scientific knowledge is synthesised, translated and formatted in a way in the ecosystem that policymakers can use it easily (rev) 

Individual 
competences 

PMs lack skill 

Policymakers have the skills to broadly understand and critically appraise scientific evidence and arguments (rev) 

PMs cannot differentiate 

Policymakers recognise the difference between scientific knowledge and stakeholder opinions and other forms of analyses (rev) 

Institutions 
and resources 

Normative 
foundations  

PMs not diversified 
demand 
PMs do not appreciate 

PMs lack ecosys knowl 

SCs are not appreciated 

Policymakers seek out broad and diverse scientific knowledge, not only a single expert/study, to inform their policy deliberations and design 
(rev) 
Most policymakers appreciate the unique value of scientific knowledge for policymaking (rev) 

Policymakers  know  which  scientific  institutions  and  knowledge  brokers  in  your  country  can  provide  evidence  and  analytical  capacities  to 
address their questions (rev) 
Scientists can expect recognition, rewards and/or support for science for policy/advice work by their employers, funders and peers (rev) 

Lack meeting opp 

Scientists and policymakers lack regular and well-supported opportunities to meet and exchange ideas 

Lack funding 

Lack of funding for science for policy / science advice structures and activities is the main obstacle to evidence-informed policymaking 

Ecosystem is fragmented 

Difficulty new entry 

The science for policy / science advice ecosystem is fragmented: in general organisations rarely coordinate their activities and are often not 
aware of each other’s activities 
It is very difficult for newly interested organisations and individuals to join science for policy / science advice processes and existing structures 

SCs lack org 

Scientific organisations have set up dedicated organisational structures and processes to share scientific evidence with policymakers (rev) 

No mutual trust 

Policymakers do not trust scientists (and vice versa) 

Roles & process not clear 

Lack transparency 

PMs are constrained 

PMs use to justify 

Roles  and  processes  within  the  science  for  policy /  science  advice  ecosystem  are  clearly  formalised  (clear  mandates,  institutionalised 
mechanism, etc.) (rev) 
Processes of production and use of scientific knowledge are not transparent to the public in the science for policy / advice ecosystem 

Policymakers are strongly constrained in their ability to take science knowledge on board and often need to prioritise other considerations 
(balancing regional interests, etc.) instead 
Policymakers tend to use scientific knowledge to justify (ex post) their decisions rather than inform them (ex ante) 

SCs not independent 

When participating in policymaking, scientific experts remain independent from the influences of policymakers (rev) 

PM, 

NB: 
Source: Own elaboration.  

policymaker; 

rev, 

statements 

that 

have 

been 

rephrased 

at 

the 

time 

of 

data 

analysis 

to 

reflect 

needs 

or 

challenges; 

SC, 

scientist. 

 10 

We  asked  participants  to  select  their  professional  occupation,  and  we  regrouped  responses  into  three  main 
groups,  based  on  participants’  roles  in  terms  of  knowledge  exchange,  that  is,  as  knowledge  producers, 
knowledge  users  or  knowledge  brokers  (Table 2).  These  three  labels  were  assigned  ex  post  based  on 
respondents’  professional  occupations  and,  thus,  do  not  correspond  to  participants’  self-identification  as 
producers, users or brokers, which might have been different, in some cases, depending on the national contexts 
(i.e. the role of academies of science can, in some cases, be more akin to that of knowledge producers than 
knowledge brokers). However, such categories are consistent with existing literature (Duncan et al., 2020; Budtz 
Pedersen  et  al.,  2023)  and  allow  us  to  explore  the  different  perceptions  of  the  qualities  and  needs  of  S4P 
ecosystems. Respondents fulfilling many roles had the option to select several answers, but for the purpose of 
data analysis their first answer was the only one considered. 

Table 2. Respondents by professional group 

Knowledge producers  

Knowledge users  

Knowledge brokers  

Primarily involved in producing 
scientific knowledge 

Primarily involved in using 
scientific knowledge 

Universities and higher 
education institutions; public 
research performing institutions  

Government/public 
administrations at the national 
level; government/public 
administrations at the 
subnational level; 
government/public 
administrations at the EU or 
international level; parliaments 

Primarily providing services to 
transmit and translate scientific 
knowledge for policymaking 

Academies of science; think tanks; 
business organisations; not-for-
profit civil society organisations; 
other  

Source: Own elaboration. 

Respondents were asked to select their nationality and which countries they were referring to when answering 
questions regarding the S4P ecosystem. For the country comparisons, only countries that had received more 
than 30 responses each were included in the analysis. These were Denmark, Greece, Spain, France, Lithuania 
and Portugal. 

Several limitations need to be accounted for in the sampling strategy. First, the sample size is not representative 
but self-selected by interest to engage with the EU on questions around S4P. Therefore, participants were more 
likely to be interested in the topic of S4P, more likely to be interested in international affairs and from certain 
countries (the survey was available in only English) and more likely to be interested in workshops on bridging 
the  gap  between  science  and  policy,  and  thus  already  likely  to  consider  scientific  advice  valuable  for 
policymaking  (which  may  be  more  selective  for  policymakers  than  scientists).  Second,  the  sample  was  still 
relatively  small,  especially  for  the  country-specific  analysis  and  comparisons,  such  that  group  comparisons 
should be assessed with consideration being given to the small number of observations per category. Third, our 
clear-cut separation between professional occupations in terms of supply and demand may have resulted in 
the  mis-categorisation  of  some  profiles  (e.g.  knowledge  producers  working  inside  government /  public 
administration  bodies  being  categorised  as  knowledge  users)  and  the  conflation  of  knowledge-broker 
organisations  in  the  categories  of  either  knowledge  producers  or  users,  due  to  the  country-specific 
characteristics of S4P ecosystems. Finally, several participants have long-term experience at the S4P interface 
and  have  possibly  changed  their  role  in  their  career  over  time;  thus,  their  answers  identifying  their  current 
organisation may be misleading. 

 11 

 
 
3.  Results and discussion 

The  report  analyses  the  responses  obtained  from  a  survey  on  the  qualities  of  and  challenges  for  S4P 
ecosystems, with responses being from scientists, policymakers and other practitioners (e.g. knowledge brokers) 
working  at  the  science–policy  interface.  The  analysis  identifies  shared  problems  across  the  whole  sample 
(Section 3.1), variation in perceptions according to professional group (Section 3.2) and variation in perceptions 
in those countries with more than 30 responses (Section 3.3). 

The results highlight how professionals working at the science–policy interface interpret the qualities of S4P 
ecosystems  and  the  challenges  that  need  to  be  addressed  to  improve  evidence-informed  policymaking.  In 
particular, our data suggest that S4P ecosystems are largely perceived as being fragmented and that better 
coordination between scientists and policymakers, in terms of opportunities and mechanisms for exchanging 
ideas and favouring cooperation and coordination, is essential. The exploratory findings highlight the need to 
explore  all  dimensions  of  science  advice  but  mostly  the  need  to  go  beyond  the  most  direct  ‘productive 
interactions’  of  timely  and  appropriate  questions  and  look  more  in  depth  at  the  institutions,  normative 
foundations and competences, which have received less attention than other aspects of science advice in the 
literature. 

3.1.  Shared problems related to the quality of science for policy in Member States 

3.1.1.  Sample description 

A total of 498 respondents were surveyed. The majority (317 respondents, equivalent to 64.7 % of the total 
sample) were concentrated in six countries, namely Portugal (103, 20.7 %), France (75, 15.1 %), Greece (41, 
8.2 %),  Denmark  (34,  6.8 %),  Spain  (33,  6.6 %)  and  Lithuania  (31,  6.2 %).  The  remaining  respondents  were 
grouped under ‘EU Other’ (181, 36.3 %) ( 6). Their distribution across countries and professional groups is shown 
in Figure 2 and Table 3. 

Table 3. Summary of respondents by country and professional group 

Knowledge 
producer, n (%) 

Knowledge 
user, n (%) 

Knowledge 
broker, n (%) 

NA, n (%) 

Total 

Denmark 

19 (55.9) 

8 (23.5) 

5 (14.7) 

France 

Greece 

36 (48.0) 

32 (42.7) 

6 (8.0) 

12 (29.3) 

19 (46.3) 

10 (24.4) 

Lithuania 

16 (51.6) 

13 (41.9) 

2 (6.5) 

2 (5.9) 

1 (1.3) 

0 (0) 

0 (0) 

Portugal 

53 (51.5) 

31 (30.1) 

15 (14.6) 

4 (3.9) 

Spain 

14 (42.4) 

11 (33.3) 

8 (24.2) 

0 (0) 

EU other 

78 (43.1) 

58 (32.0) 

42 (23.2) 

3 (1.7) 

Total 

228 (45.8) 

172 (34.5) 

88 (19.7) 

10 (2.0) 

34 

75 

41 

31 

103 

33 

181 

498 

NB: Percentages of responses by type and country. NA, no response to the question about type of knowledge organisation. Countries are 
sorted in (English) alphabetical order. Source: Own elaboration.  

(6) 

Bulgaria,  Czechia,  Germany,  Estonia,  Ireland,  Croatia,  Italy,  Cyprus,  Latvia,  Hungary,  Austria,  Poland,  Slovenia,  Slovakia,  Finland, 
Sweden. 

 12 

 
 
 
 
Concerning knowledge organisation type, 228 (45.8 %) respondents attributed themselves to different types of 
knowledge-producing  organisations  (universities,  research  institutions),  172  (34.5 %)  to  different  types  of 
knowledge-using organisations (public administrations at all levels of governance) and 88 (19.7 %) to other 
types of knowledge organisations (think tanks, academies of science, business organisations, non-governmental 
organisations and others) (Table 3). Finally, 10 (2 %) respondents did not answer the question. 

The distributions of professional groups across countries were mostly comparable. As seen in Figure 2, Denmark 
had the largest share of knowledge producers, followed by Lithuania, Portugal and France, while Greece had 
the lowest share of knowledge producers but the largest shares of both knowledge users and other types of 
knowledge professionals. 

Figure 2. Overview of respondents by country and professional type 

NB: Countries are sorted in (English) alphabetical order. Sample size = 498. NA, no response to the question about the type of knowledge 
organisation. Source: Produced by the authors.  

3.1.2.  Lack of meeting opportunities and ecosystem fragmentation 

First, we provide an overview of the issues identified by survey participants. Figure 3 presents the aggregate 
responses  to  the  challenge  statements  by  each  of  the  four  dimensions.  Overall,  there  is  large  variation  in 
responses to the questions for each of the four dimensions, except for the productive interactions dimension, 
where answers are more similar. 

The percentages of respondents agreeing with individual statements were highest for statements about the 
lack of meeting opportunities and the fragmentation of the ecosystem as part of the institutions and resources 
dimension.  Around  7  out  of  every  10  respondents  (strongly)  agreed  with  the  statements  about  the  lack  of 
regular  and  well-supported  opportunities  to  meet  and  exchange  ideas  between  scientists  and  policymakers 
(71.3 %)  and  the  S4P  ecosystem  being  fragmented  and  suffering  from  limited  coordination  of  actors  and 
activities (70.1 %). This result corroborates existing research in terms of the relevance of both institutional and 
personal, informal contacts for scientific knowledge circulation and uptake from policymakers (Oliver and de 
Vocht, 2017; Haynes et al., 2018). In addition, the S4P ecosystems are also not considered easily accessible for 
newcomers (62.1 %). 

 13 

 
 
 
 
It is worth noting that respondents answered the survey sometimes after having attended a workshop on the 
S4P ecosystems (see Chapter 2), which will most likely have had an influence on the responses. For example, 
at some workshops, draft discussion papers were shared indicating that, among other things, S4P ecosystem 
fragmentation is an issue (Maxim, 2022; Simões, 2022). Nonetheless, our results are consistent with previous 
research  and  systematic  reviews  emphasising  how  the  absence  of  personal  contact  between  scientists  and 
policymakers is the main barrier to the use of research by policymakers (Choi et al., 2005; Oliver et al., 2014; 
Capano  and  Malandrino,  2022).  Therefore,  despite  a  potential  impact  of  workshop  attendance  on  some 
responses, existing research  seems to support our findings about the lack of meeting  opportunities and the 
fragmentation of S4P ecosystems as key challenges for implementing successful S4P practices. A further crucial 
issue on which more than half (51.4 %) of the respondents agree is the absence of dedicated organisational 
structures and processes for sharing scientific evidence with policymakers. While still considered a potential 
hindrance for establishing better science–policy interfaces, the lack of financial support for S4P is, in contrast, 
perceived  as  less  central  than  other  challenges  in  the  institutions  and  resources  dimension  (with  47.2 %  of 
respondents agreeing and 25.3 % disagreeing with the statement). 

The lowest levels of agreement among respondents were with two statements often at the heart of discussions 
about  the  role  of  expertise  in  policymaking,  namely  that  scientists  engaging  in  S4P  may  jeopardise  their 
independence  (131/498,  26.3 %)  and  that  there  is  no  mutual  trust  between  scientists  and  policymakers 
(176/498, 35.3 %). When it comes to providing policy advice, scientific independence has been established as 
a  core  principle  (Gluckman,  2014;  OECD,  2015;  SAPEA,  2019).  Respondents  do  not  largely  perceive  it  as  a 
fundamental problem between scientists and policymakers in the current S4P ecosystem, possibly indicating 
that  the  set-up  is  perceived  to  be  sufficient  to  ensure  independence.  Respondents  seem  to  vary  in  their 
perspectives on whether there is a lack of mutual trust in the system, with few (no majority) either agreeing or 
disagreeing, and very few having extreme views on this issue. Issues related to these two statements are often 
at  the  heart  of  discussions  about  the  role  of  expertise  in  policymaking  (Christensen  and  Lægried,  2022; 
Gundersen and Holst, 2022). When it comes to policy advice, both the issue of the independence of scientists 
and the level of trust at the science–policy interface are considered crucial qualities for the functioning of S4P 
ecosystems  and  their  democratic  credentials  (Schroeder,  2021).  Hence,  the  fact  that  a  non-negligible 
percentage of respondents acknowledged the limited independence of scientific experts and the lack of mutual 
trust between scientists and policymakers, along with the large number of respondents who had a neutral view 
on the statement, invites careful consideration of the results from policy and normative perspectives. 

Statements  on  other  normative  foundational  challenges  receive  stronger  agreement,  such  as  policymakers 
being constrained in their use of evidence (63.5 %) and using science to justify decisions ex post (58.5 %), and 
a lack of transparency (57.5 %), with a majority of respondents (strongly) agreeing with each. This shows that 
despite trust and independence are seen as given, the operational logic of policymaking still seems to interfere 
with the uptake of science, constraining policymakers’ capacity to consider and use evidence. This perception of 
such  a  disconnect  is  also  mirrored  in  respondents’  answers  concerning  knowledge  supply,  as  there  is  wide 
agreement  on  the  lack  of  recognition,  rewards  and/or  support  for  S4P  in  the  science  system,  as  mentioned 
above. 

The lack of particular competences of individuals and organisations affects the production, provision and use 
of appropriate scientific knowledge for policy. The responses to the survey point to the shared perceptions that, 
on the one hand, policymakers often lack the skills to ask the right questions (with 53.2 % (strongly) agreeing 
with the relevant statement) and appraise scientific evidence (with 62.3 % (strongly) agreeing), and the evidence 
base they request is not sufficiently diverse (with 57.9 % (strongly) agreeing), while, on the other hand, science 
advice  does not  seem to  be  sufficiently recognised, especially among peers, employers and funders (with a 
majority (56.1 %) agreeing). There is no substantial agreement concerning policymakers’ lack of knowledge of 
the  ecosystem  (39.3 %  agree  v  33.3 %  disagree)  or  the  ability  to  distinguish  scientific  knowledge  from 
stakeholder opinions (38.3 % agree v 35.7 % disagree). 

For the productive interactions dimension, the majority of respondents agreed that science is not fit for purpose 
and not timely and that policymakers do not ask the right questions for receiving useful science advice. Thus, 
while  other  statements  garner  stronger  support  than  statements  in  this  category,  overall,  the  interactions 
between policymakers and scientists, when they happen, are not seen as productive enough. 

 14 

Figure 3. Survey results across all respondents: levels of agreement with statements about what is needed 
for a better S4P ecosystem 

NB: Sample size = 498. The short versions of the statements are shown in the figure; see Table 1 for full statements. Statements have 
been sorted from the highest rate of agreement (strongly agree and agree, top) to the lowest (strongly disagree and disagree, bottom), 
by S4P ecosystem dimension. SC, scientist; PM, policymaker. Source: Own elaboration. 

When  considering  the  results  in  terms  of  the  four  S4P  dimensions  identified,  there  is  no  dimension  that 
dominates over the others in terms of respondents’ agreement with the associated statements. Statements 
related to systemic issues in the institutions and resources and normative foundations dimensions received the 
strongest  support,  yet  there  are  relevant  variations  in  responses  within  each  subset  of  statements,  which 
suggests  caution  in  inferring  clear  rankings  among  dimensions.  Indeed,  for  14  of  the  20  statements,  the 
percentage  of  respondents  agreeing  with  each  statement  was  greater  than  the  percentage  disagreeing, 
suggesting a shared perception among respondents of the need to strengthen the S4P ecosystem across all 
dimensions. 

Overall,  our  findings  are  in  line  with  several  existing  studies  on  relations  at  the  science–policy  interface. 
Respondents’ agreement on the fragmentation of S4P ecosystems and the lack of formal and informal channels 
for personal exchange corroborates recent research on institutional arrangements to bridge science and policy 
(De Donà and Linke, 2023) and multilevel ecosystems of evidence-informed decision-making (Schünemann et 
al., 2022). Furthermore, responses to the survey show how individual capacities and lack of skills on both the 
knowledge supply and demand sides are perceived as crucial obstacles to providing effective science advice, 
although there seems to be a stronger agreement on the dimensions of competences and normative approaches 
of  policymakers  towards  S4P  compared  to  issues  relating  to  the  science  side.  On  the  need  for  improved 
competences, our results support recent calls to improve the capacity of intermediaries and knowledge brokers 
to facilitate interactions and translation efforts across the S4P ecosystem (Cairney et al., 2023). 

3.1.3.  Patterns in professionals’ perceptions based on correlation analysis 

Having considered the four dimensions of the S4P system separately, correlation analysis reveals interesting 
patterns among the responses (Figure 4). First, almost all significant correlations are positive and there are only 

 15 

 
a few significant negative correlations of low magnitude ( 7). This result suggests that most the factors that 
could contribute to a better S4P system surveyed in this study are directly related according to the perceptions 
of professionals at the science–policy interface. 

The strongest correlation can be found between the statements ‘Scientists receive questions from policymakers 
and knowledge brokers framed in such a way that they can provide useful evidence-informed inputs’ (rev) and 
‘Scientific knowledge is synthesised, translated and formatted in a way in the ecosystem that policymakers can 
use it easily’ (rev) (corr = 0.54***). Hence, those respondents who agree that policymakers are not asking the 
right  questions  also  tend  to  think  that  the  scientific  knowledge  provided  is  not  fit  for  purpose.  Given  that 
agreement on  both these issues is not  significantly  correlated with any of the other statements, this result 
suggests  that,  while  acknowledging  translation  between  science  and  policy  as  a  key  challenge,  respondents 
diverge in terms of their perceptions of which specific institutional, competence or normative foundation should 
be improved. Such observations emphasise the need to better understand the opportunities and constraints in 
relation  to  interacting  at  the  science–policy  interface  and  building  competences  to  build  a  successful  S4P 
ecosystem. 

Furthermore,  there  are  some  significant  correlations  when  it  comes  to  S4P  and  policymaking  competences. 
Respondents  who  agree  with  the  statement  ‘‘Most  policymakers  appreciate  the  unique  value  of  scientific 
knowledge  for  policymaking’  also  tended  to  also  agree  with  the  statements  Policymakers  have  the  skills  to 
broadly understand and critically appraise scientific evidence and arguments (rev) (corr = 0.45**), Policymakers 
recognise the difference between scientific knowledge and stakeholder opinions and other forms of analyses 
(rev)    (corr = 0.45**),  Policymakers  seek  out  broad  and  diverse  scientific  knowledge,  not  only  a  single 
expert/study, to inform their policy deliberations and design (rev) (corr = 0.42*) and Policymakers do not trust 
scientists (and vice versa) (corr = 0.41*). These questions seem to build a cluster of answers that go together, 
which suggests a certain degree of mistrust in the abilities and behaviours of policymakers towards scientists. 
This cluster also contains other minor correlations between the statement Policymakers know which scientific 
institutions and knowledge brokers in your country can provide evidence and analytical capacities to address 
their  questions  (rev)  and  the  statements  Policymakers  have  the  skills  to  broadly  understand  and  critically 
appraise scientific evidence and arguments (rev) (corr = 0.39*). Finally, there are a few negative correlations, 
but of very low magnitude, between statements concerning the existing constraints for S4P on the science and 
policymaking sides. 

Overall,  the  correlation  analysis  reveals  that  the  questions  mostly  cover  the  same  ground  in  professionals’ 
perceptions, with patterns pointing notably to moderate positive correlations in almost all areas, rather than 
sharp  differences  pointing  to  weaknesses  on  either  the  policymaker  side  or  the  scientist  side.  Although  the 
perception of mistrust in policymakers’ use of evidence and skills towards science uptake points to a cluster, 
there  are  no  clusters  of  strong  disagreement  on  the  challenges  for  S4P  ecosystems.  Indeed,  respondents 
agreeing  on  policymakers’  lack  of  S4P  competences  also  largely  agree  on  the  need  for  change  in  terms  of 
scientific knowledge translation and synthesis. The statements on asking the right questions and the scientific 
translation, in this respect, seem to be an interesting indicator of the perceived need to address both sides of 
S4P ecosystems, through improving S4P competences and providing opportunities to better connect knowledge 
suppliers and users. 

(7) 

In discussing correlation patterns, significance levels are indicated, as per convention, with asterisks: * for a 10 % significance level, 
** for a 5 % significance level and *** for a 1 % significance level. 

 16 

 
Figure 4. Correlation patterns in S4P survey results 

* 10 % significance level. ** 5 % significance level. *** 1 % significance level. NB: The short versions of the statements are shown in the 
figure; see Table 1 for full statements. Colours represent the strength of correlations, with shades of blue representing positive 
correlations and shades of red negative correlations. Sample size = 498. SC, scientist; PM, policymaker. Source: Own elaboration. 

3.1.4.  Multiple  challenges  across  science  for  policy  ecosystems:  embracing  a  holistic 

perspective 

The analysis of the responses across the entire sample set suggests that challenges for S4P ecosystems touch 
on all four dimensions, with varying levels of agreement within and across each dimension. The respondents’ 
perceptions  suggest  recognition  of  room  for  improvement  across  all  dimensions  (i.e.  the  need  for 
support/reforms  in  relation  to  system  services,  rules,  resources  and  information;  structures,  mindsets, 
knowledge and processes that support engagement and productive interactions between different actors; and 
knowledge, skills and services that reduce costs of transmitting and absorbing knowledge into policymaking). 

The statement with the highest level of agreement, about the challenge that scientists and policymakers lack 
regular  and  well-supported  opportunities  to  meet  and  exchange  ideas,  belonged  to  the  institutions  and 
resources  dimension  (71.3 %  agreement;  Figure 3).  This  is  a  particularly  relevant  finding,  as  it  corroborates 
existing research on the critical role of both formal and informal channels for science advice. Empirical studies 
tend to emphasise how policymakers often seek science advice via trusted interpersonal channels (Haynes et 
al., 2018), and informal and unplanned contacts, throughout the policy process, are facilitators for evidence 
uptake  (Oliver  and  de  Vocht,  2017),  enabling  or  interfering  with  engagements  and  productive  interactions 
between the scientific and policymaking communities. For instance, the culture and operational logic of these 

 17 

 
distinct  communities  may  prevent  engagement,  mutual  appreciation  and  the  use  of  institutional  channels 
provided by intermediary, bridging or boundary organisations and processes. 

Furthermore, the high level of agreement with many of the statements (agreement higher than 50 % for 14/20 
statements) gives rise to important questions around (the need for) shifts in research and practice / capacity 
building in the field of S4P. These results open new research avenues and corroborate recent efforts to embrace 
a holistic view in the analysis of S4P ecosystem challenges, including those around the need for more systematic 
interactions between science and policy professionals, which does not seem to be hindered by a lack of trust, 
independence or funding, but rather by a lack of opportunities to meet and have productive exchanges. While 
there is research that emphasises a specific dimension of science advice, such as studies on the individual S4P 
competences  of  policymakers  and  scientists  (OECD,  2015;  Schwendinger  et  al.,  2022)  or  on  practices  of 
boundary spanning, knowledge brokering and intermediary organisations’ research (Pielke, 2007; Spruijt et al., 
2014; Gluckman et al., 2021), the literature on S4P ecosystems is only now emerging (Boaz et al., 2019; Global 
Commission  on  Evidence  to  Address  Societal  Challenges,  2022;  Oliver,  2022).  Contributing  to  this  emerging 
literature,  this  report  calls  for  new  systematic  efforts  to  map  and  analyse  S4P  ecosystems  from  a  holistic 
perspective, looking at interconnections between actors, factors and the different dimensions of the science–
policy interface. 

Global societal challenges have become very difficult and complex to address, with the need not only to leverage 
scientific expertise from across multiple disciplines, but also to promote political discussions at the international 
level  to  agree  on  policies  that  can  be  later  implemented  across  governance  levels.  This  multidisciplinary 
scientific advice and interinstitutional coordination seems particularly important. It is the cause for discussions 
at the highest international level, such as that of the United Nations (Nature, 2022). Moreover, the norms and 
rules that underpin S4P ecosystems shape interactions and incentives at the (inter)organisational and individual 
levels. They may influence ‘who has the right to speak on expert matters; when and for which sorts of decisions 
evidence  will  be  invoked;  where  budgets  will  be  utilised  to  generate  new  evidence;  and,  ultimately,  whose 
interests are represented and promoted from the operation of the evidence advisory system’ (Parkhurst, 2017). 

Working and improving this level of interaction quality in an S4P ecosystem in Europe may yield the largest 
gains for better policymaking. In other words, based on the perceptions of the professionals at the science–
policy interface surveyed  here, while the  supply and demand side factors are  seen as relevant, the  clearing 
mechanisms between demand for scientific evidence and supply are perceived to be underdeveloped. 

3.2.  Variation in professional groups’ perceptions of problems 

The unique sample used for this survey allows us to test whether or not the perceptions of respondents on 
different sides of the S4P ecosystems differ significantly from each other. This is an interesting question, given 
that  existing  research  acknowledges  a  common  perceptual  issue  in  that  people  usually  find  fault  in  the 
counterpart arguments. In addition, identifying any agreements between groups could potentially provide us 
with insights into joint problem perceptions (or the lack thereof). 

As  aforementioned,  almost  half  (45.8 %)  of  respondents  belonged  to  knowledge-producing  organisations 
(universities,  research 
institutions,  etc.),  34.5 %  belonged  to  knowledge-using  organisations  (public 
administrations at all levels of governance), 19.7 % belonged to other types of knowledge organisations (think 
tanks, academies of science, business organisations, non-governmental organisations, etc.) and 2.0 % did not 
select a category or type. We did not consider this latter group in the analysis of specific answers to statements 
between the three professional groups, and thus analysed a set of 488 respondents. 

Testing for significant differences  between the  responses about challenges by both knowledge professional 
type and country, we performed a two-way multivariate analysis of variance (MANOVA) test, which delivered 
significant results (knowledge professional type, p = 0.043; country, p = 0.000). The interaction between type 
and country was not significant (p = 0.502). Thus, we performed a post hoc test for all combinations of countries 
and knowledge professional types, but not the interaction. Table 4 shows the combinations of tests, and the 
adjusted  significance  levels  based  on  Bonferroni  corrections.  After  adjusting  significance,  the  difference 
between knowledge brokers and knowledge producers is not significant, but the differences between the others 
(i.e. between knowledge brokers and knowledge users and between knowledge users and knowledge producers) 
are highly significant. For information on countries, see Section 3.3. 

 18 

 
Table 4. Pairwise t-tests for knowledge professional types  

G1 

G2 

p-value 

Bonferroni  
adj. p-value 

Knowledge broker 

Knowledge producer  0.017 

* 

0.105  ns 

Knowledge broker 

Knowledge user 

0.000 

**** 

0.000 

**** 

Knowledge producer 

Knowledge user 

0.000 

**** 

0.000 

**** 

* 10 % significance level. ** 5 % significance level. *** 1 % significance level. NB: Sample size = 488. Source: Own elaboration. 

Following the finding of significant differences between knowledge professional types, Figure 5 plots means by 
question and by type. In order to not inflate the number of hypotheses tested in this explorative part, and given 
that not all overall type comparisons are significant at this stage, we refrain from further pairwise statistical 
testing. Nevertheless, the graphical analysis reveals a number of apparent patterns. On average, the different 
types of knowledge actors in the ecosystem seem to have relatively similar responses for most questions, and 
only a few variations can be seen, even when there is a general significant difference between brokers, users 
and  producers  of  knowledge.  In  addition,  no  type  agrees  most  or  least  about  all  challenges,  showing  that 
variation  is  likely  to  represent  the  various  positions  in  the  ecosystem,  where  each  player  gathers  different 
experiences with the system. Nevertheless, some tendencies can be derived from the answers. It should also 
be noted that knowledge brokers, who function as a bridge between the producers and users of knowledge, are 
likely to be the most experienced in understanding both sides and therefore their perspectives are particularly 
relevant. 

On individual competences, knowledge brokers agree the most in relation to all challenges, showing that they 
strongly perceive there to  be a lack of competence on the policymaker side,  which  most statements in this 
dimension  relate  to.  There  are  some  differences,  particularly  between  users  and  brokers,  in  responses  to 
statements regarding policymakers’ lack of skills, inability to differentiate different inputs, lack of diversified 
inputs and lack of ecosystem  understanding. Only for the ‘Scientists can expect  recognition, rewards and/or 
support  for  science  for  policy/advice  work  by  their  employers,  funders  and  peers’  (rev)  are  all  groups  in 
agreement. Producers sit in between the two most ‘extreme’ views of the system and its challenges. Such a 
result  calls  for  a  more  careful  consideration  of  the  two-communities  idea,  since,  based  on  these  individual 
competences dimension, the dividing line appears to run through users and intermediaries, rather than between 
producers and users. 

For the institutions and resources dimension, the knowledge brokers group agrees with some statements less 
than the other groups do, although this group agrees significantly more with statements related to a lack of 
meeting opportunities, a lack of funding and difficulties faced by new ecosystem entries than the knowledge 
users  group.  In  contrast,  there  is  no  significant  difference  between  groups’  responses  to  statements  on 
ecosystem  fragmentation  and  the  lack  of  scientist  organisations.  For  the  normative  foundations  dimension, 
there are non-significant differences for most items, with the exception of a lack of mutual trust, where users 
and producers  disagree the  most, with  knowledge producers having agreed the most  that there is a lack of 
trust. Both producers and brokers agree significantly more strongly than users with the statement on the lack 
of transparency in knowledge use. 

Overall, knowledge-broker respondents had the highest level of agreement among the three groups for 70 % 
(14/20) of the statements. This may indicate that organisations operating in the intermediary space have a 
more widely shared perception of the challenges that characterise the S4P ecosystem. As knowledge brokers 
interact with both scientific and policymaking communities more regularly, they are likely to. Be more aware of 
the gaps and needs at the science–policy interface. This is only one possible interpretation, and the opposite 
could  be  true,  as  the  group  ‘travelling  both  worlds’  could  see  issues  as  less  problematic,  having  a  better 
understanding of the logic of policymaking and of science production. If that were the case, a conclusion could 
be that a better understanding on both sides would reduce tensions and perceptions of a lack of performance 
in the S4P ecosystem. In contrast, given that knowledge brokers seem to have the highest level of agreement 
with most of the statements on challenges, this should give rise to warning signs about the S4P ecosystem 
overall. 

 19 

 
 
 
 
 
  
Figure 5. Responses by professional type 

NB: Sample size = 488. The short versions of the statements are shown in the figure; see Table 1 for full statements. Dots represent 
means and lines represent 95 % confidence intervals. KN, knowledge; PM, policymaker; SC, scientist. Source: Own elaboration. 

In contrast, users of knowledge showed the lowest level of agreement for 70 % (14/20) of the statements. This 
result may be less of a surprise, as policymaking requires the inclusion of many different types of input, not 
just scientific, which may be of less concern for knowledge users than for knowledge brokers and producers. 
Nevertheless, the three statements that users had the highest level of agreement with were two that highlighted 
the shortcomings of producers (timeliness and fit for purpose) and one that described policymakers using the 
knowledge to justify their position ex post. The first two are in line with expectations, as receiving meaningful 
contributions in a timely fashion is often identified as a key issue for knowledge use by policymakers. The other 
highest score for users is instead prima facie surprising. In principle, we would have expected producers and 
brokers to have a stronger perception of policymakers’ instrumental evidence use. Instead, knowledge users 
seem  to  be  more  concerned  by  the  selective  uptake  of  science  than  their  counterparts.  This  result  may  be 
interpreted in light of the stronger awareness of knowledge users about practices of science use, due to their 

 20 

 
 
  
close  involvement  in  the  policymaking  and  decision-making  processes  or  because  they  are  more  often 
confronted with cherry-picked evidence that argues against their own decision. 

Knowledge  producers  most  often  seem  to  be  in  the  middle,  between  brokers  and  users,  in  terms  of  their 
agreement with statements related to the challenges surveyed in this study. In principle, given their greater 
distance from the practice of policymaking and the challenges they face in terms of policy impact, we could 
expect  knowledge  producers  to  be  the  most  vocal  group  in  advocating  for  change  in  the  S4P  ecosystem. 
However,  our  results  may  be  interpreted  in  light  of  the  fact  that  impact  on  policy  still  represents  only  one 
dimension – and often not a main one – of the work of knowledge producers, a circumstance that may explain 
why knowledge producers perceive these challenges as less pressing than knowledge brokers. 

Overall, it is important to remark that the gap in terms of perceptions of problems between the classic two 
communities and knowledge brokers was less pronounced than expected. This was even the case for questions 
in  which  professionals  from  one  community  were  asked  about  the  qualities  of  the  other,  such  as  in  the 
abovementioned case of selective use of scientific knowledge. However, knowledge brokers are typically the 
most critical about the functioning of the S4P ecosystem, with producers being in the middle and users agreeing 
less with statements about the challenges faced. 

Knowledge brokers being the most concerned about the S4P ecosystem may give rise to questions as to the 
capacities of intermediary organisations to connect the two communities effectively and their need for support 
and  better  integration  with  the  other  two  communities.  However,  with  the  ‘other  knowledge  organisations’ 
category being the least clearly defined organisational category in the survey design, this insight needs to be 
treated with caution. It also gives rise to the question of whether the perception of users was correct or had the 
most  internal  heterogeneity  because  of  other  factors  (policy  field,  closeness  to  policymaking  and  decision-
making, etc.), given that both producers and brokers were more concerned with these issues. Therefore, more 
research is required to answer these questions. 

Of users and producers, it seems that the latter had more negative perceptions concerning the knowledge and 
attitude of policymakers towards scientific evidence, including about the independence of scientists in providing 
science  advice.  In  general,  however,  the  divergence  between  producers  and  users  was  rather  modest.  The 
difference between users and producers may point to a certain imbalance between supply and demand at the 
science–policy  interface,  that  is,  that  producers  may  (be  able/willing  to)  supply  more  scientific  evidence  for 
policymaking than policymakers ask for and/or can process. This gives rise to questions about the political will 
and/or  capacity  to  support  S4P  and  the  desirability  for  scientists  to  play  a  greater  role  in  policymaking,  or, 
alternatively, scientists inflating the importance of scientific evidence in policymaking over alternative inputs. 
Studies on the governance of evidence-informed policymaking (Parkhurst, 2017; Strand, 2022) underscore how 
a better use of science is not just a matter of good evidence, but is closely related to managing and balancing 
technical  biases,  hence  ensuring  ‘scientific  fidelity’  and  so-called  issue  biases,  avoiding  an  overreliance  on 
science  and  the  overlooking  of  social  values  and  political  representativeness.  In  this  sense,  it  calls  for  the 
incorporation of principles of democratic representation in the S4P ecosystem (Krick et al., 2019). 

In  terms  of  identifying  the  main  challenges,  our  findings  address  research  on  the  demand  side  of  the  S4P 
interface, in terms of supporting the view that time constraints and ‘appropriateness’ of science advice are key 
to providing effective science advice, especially according to policymakers (Bielak et al., 2008; Masood et al., 
2020). Furthermore, a crucial challenge is the lack of trust between scientists and policymakers, in relation to 
which we observed an important asymmetry in terms of the perceptions of producers and users. While existing 
research tends to focus on policymakers’ trust in science advice and the conditions under which such advice is 
considered trustworthy (Schroeder, 2021; Gundersen and Holst, 2022), our results suggest a need to pay greater 
attention to the other side of the coin and gaps in perception, and how knowledge producers’ and brokers’ trust 
affects science advice. 

As for knowledge use, our findings address the extensive literature on the political use(s) of evidence (Daviter, 
2015;  Capano  and  Malandrino,  2022).  In  this  regard,  the  counterintuitive  apparent  self-criticism  of  users 
regarding the  selective use of evidence opens further avenues for research on  policymakers’  perceptions of 
their use of science and evidence, which is often studied from the perspective of knowledge producers. This is 
also connected to the idea that policymakers are constrained in taking science on board, which was among the 
top five statements in terms of agreement for all three professional groups, with a narrow margin of difference. 
The agreement on political and practical constraints in science uptake across all the participants hints towards 
a general awareness of the complexities of science advice, in contrast with naive views of the role of science 
in policymaking. 

 21 

3.3.  Variation in perceptions of problems by country: a six-country comparison 

S4P ecosystems vary between countries (Figure 6). Some countries rely on chief scientific government advisors 
(e.g.  Ireland,  Cyprus),  although  this  is  relatively  rare.  National  academies  performing  advisory  functions  or 
supporting the provision of science advice (e.g. in Germany and Sweden) are also not present in all countries. 
The literature on S4P ecosystems, from a comparative perspective, highlights how the science–policy interface 
reflects and evolves as  part  of historical, political and socioeconomic configurations and events  within each 
country and in interactions with other countries / international organisations. Jasanoff (1990), in this regard, 
has  highlighted  the  influence  of  different  ‘civic  epistemologies’  on  the  configurations  of  the  science–policy 
interface, while Vogel (1986) discusses the role of expertise in national regulatory styles. 

It is important to compare problem perceptions by country, first, to understand what institutional and political 
configurations  might  be  conducive  to  S4P  practices  (i.e.  statements  with  a  lower  level  of  agreement)  and, 
second, to be able to design country-specific capacity-building work in a way that addresses the specific problem 
constellations. 

Based on available responses, we included in our analyses the six countries for which we have received more 
than 30 responses each, as this number is often considered sufficiently large for analysing means (Kwak and 
Kim, 2017). These were Denmark, Greece, Spain, France, Lithuania and Portugal. We also included an ‘EU other’ 
category combining all other country responses from within the EU. The countries represent a diverse mix of 
geographical  and  institutional  configurations,  as  well  as  a  broad  range  of  administrative  and  scientific 
capacities. The limited number of responses necessitates a word of caution, and country-specific statements 
are likely to be more uncertain than the type-specific results. Further research (boosting response, triangulation 
with other methods) could corroborate these initial findings. 

Some steps in this regard are being undertaken under the umbrella of the JRC’s S4P ecosystems project (e.g. 
discussion papers on national S4P ecosystems in Denmark (Budtz Pedersen and Hvistfeldt, 2021), Greece (Ladi 
et al., 2022), Spain (Cañibano and Real-Dato, 2024), France (Maxim, 2022) Lithuania (Vilpišauskas, 2021) and 
Portugal  (Simões,  2022)).  However,  further  analytical  work,  including  specifically  from  a  cross-country 
comparative perspective, is needed. 

 22 

Figure 6. Responses by country 

NB: Sample size = 488. Dots represent means and lines represent 95 % confidence intervals. PM, policymaker; SC, scientist. Source: Own 
elaboration. 

Table  5  presents  the  results  of  pairwise  tests  of  differences  in  response  patterns  between  countries,  with 
significance  levels  adjusted  by  Bonferroni  correction  (including  the  type  tests  in  Table 4).  There  are  various 
differences  between  countries,  but  not  all  are  significant.  Denmark  is  the  only  country  that  is  significantly 
different from all other countries and the combined ‘EU other’ category. 

Table 5. Pairwise t-tests for countries 

Bonferroni 

Country 1 

Country 2 

p-value 

adj. p-value 

Denmark 
Denmark 
Denmark 
Denmark 

EU other 
France 
Greece 
Lithuania 

0.000 
0.000 
0.000 
0.000 

**** 
**** 
**** 
**** 

0.000  ****  
0.000  ****  
0.000  ****  
0.000  ****  

 23 

 
 
 
 
 
 
 
 
Denmark 
Denmark 
EU other 
EU other 
EU other 
EU other 
EU other 
France 
France 
France 
France 
Greece 
Greece 
Greece 
Lithuania 
Lithuania 
Portugal 

Portugal 
Spain 
Portugal 
Greece 
France 
Lithuania 
Spain 
Portugal 
Lithuania 
Greece 
Spain 
Spain 
Lithuania 
Portugal 
Portugal 
Spain 
Spain 

0.000 
0.000 
0.000 
0.010 
0.132 
0.014 
0.000 
0.000 
0.001 
0.001 
0.000 
0.134 
0.889 
0.958 
0.909 
0.204 
0.088 

**** 
**** 
*** 
* 
ns 
* 
**** 
**** 
** 
*** 
**** 
ns 
ns 
ns 
ns 
ns 
ns 

0.000  ****  
0.000  ****  
0.005  **  
0.219  ns  
1.000  ns  
0.300  ns  
0.001  ***  
0.000  ***  
0.029  *  
0.017  *  
0.000  ****  
1.000  ns  
1.000  ns  
1.000  ns  
1.000  ns  
1.000  ns  
1.000  ns 

NB: Sample size = 488. ns, non-significant. Source: Produced by the authors. 

Despite  the  fact  that  Member  States  have  different  degrees  of  institutionalisation  of  science  advice 
mechanisms  and  diverse  ecosystem  arrangements,  responses  to  the  survey  show  very  similar  patterns  in 
responses across the six countries. The only clear exception seems to be Denmark (n = 32), which stands out 
across almost all the dimensions considered. Comparing the average level of agreement over the whole sample 
of questions (with lower scores meaning that there is less agreement among respondents that an issue is a 
challenge), Denmark’s average stands at 37 %, while the remaining countries score between 51 % and 59 %. 
These  results  indicate  that  respondents  in  Denmark  considered  the  issues  covered  by  the  survey  less  of  a 
problem than respondents in the remaining five countries and the ‘EU other’ category. 

The  contrast  is  especially  stark  for  statements  such  as  ‘policymakers  do  not  appreciate  advice’,  ‘roles  and 
processes  are  not  clear’,  ‘there  is  no  mutual  trust’,  ‘the  ecosystem  is  fragmented’  and  ‘scientists  lack 
organisation’,  along  with  a  few  other  categories,  showing  the  stronger  perception  that  Denmark’s  S4P 
ecosystem seems to work rather well. The overall lower levels of agreement about challenges at the science–
policy  interface  are  consistent  with  recent  research  on  the  Danish  S4P  ecosystem  (see  Budtz  Pedersen  and 
Hvidfeldt,  2021).  Still,  respondents  in  Denmark  agree  that  it  is  difficult  for  scientists  to  engage  with 
policymakers  (in  our  survey,  the  lack  of  meeting  opportunities  was  the  statement  with  the  highest  level  of 
agreement,  with 62 % of the Danish  respondents agreeing or  strongly agreeing with it). The other two top-
ranked statements (with the highest percentage of ‘agree’ or ‘strongly agree’ responses) were those concerning 
policymakers’ constraints in evidence uptake (56 %) and barriers to accessing the ecosystem (53 %). 

A  few  additional  observations  stand  out.  For  instance,  Greek  respondents  were  more  concerned  than 
respondents  from  other  countries  about  policymakers’  lack  of  ecosystem  knowledge  (63 %),  with  levels  of 
agreement  with  this  statement  being  far  higher  in  Greece  than  in  other  countries  surveyed  (17 percentage 
points higher than the country with the next highest level of agreement). This response landscape suggests that 
respondents specifically in Greece perceive a need to improve the receptiveness of public administration and a 
need for a better overview and mapping of the S4P system, in line with existing research on the Greek S4P 
ecosystem (Ladi et al., 2022). 

France, in line with the ‘EU other’  category, shows the lowest agreement with statements about the lack of 
organisational structures and processes for sharing scientific evidence. Unlike policymakers in Spain, which is 
at the upper end of the scale when it comes to productive relations, French policymakers are seen as most 
constrained.  Among  the  countries  considered,  France  seems  to  show  a  stronger  focus  on  the  limits  and 
challenges on the knowledge users’ side than on the scientist organisation side. For instance, respondents in 
France largely agree on the presence of constraints in the use of science for policymakers (77 %, with the next 
country 13 percentage points lower). Furthermore, a key concern in France was the issue of autonomy of science 

 24 

 
vis-à-vis  political  power,  which  recent  research  acknowledges  to  be  a  crucial  element  in  the  national  S4P 
ecosystem (Maxim et al., 2022). In contrast, French respondents (and respondents from other Member States) 
agreed less with the statement about scientists lacking organisation. 

In order to situate our results somewhat in the wider context, we compare the responses to the survey with a 
selection of measures of Member States’ administrative and scientific capacities from multiple sources (see 
Table 6). Due to the limited nature of each of the measures, and a general lack of better alternatives for a 
science  for  policy  performance  directly  (Niestroy  2022),  conclusions  based  on  these  findings  need  to  be 
interpreted with caution. 

For instance, the gap that we observed in the survey results between Denmark and other Member States is also 
reflected in their  comparative performance on  measures  of administrative and scientific capacities, such as 
strategic planning, governance, expert advice or publication and knowledge production measures. In all these 
areas, Denmark ranks first among our selection of countries. In a system that seems particularly well designed 
for the uptake of scientific knowledge in policymaking, concerns of S4P professionals are markedly different 
and their concerns about challenges for the S4P ecosystem are fewer than elsewhere. Nevertheless, there are 
some issues on which more than half of the respondents agree, in particular the lack of meeting opportunities, 
which was a shared concern across countries. 

France’s performance in administrative capacities and scientific capacities is mixed. While in multiple cases it 
ranks second (ex post policy evaluation, high educated population shares and high R & D expenditures), it is in 
last place when it comes to effective and legitimate consultation with non-governmental experts. This latter 
point  seems  consistent  with  French  respondents’  concerns,  which  also  deviate  from  the  average  of  other 
countries in our survey, about policymakers’ constraints in terms of making use of science in policy decisions 
and about the lack of transparency and skills on the policymaker side. These results corroborate the observed 
perception in France that the S4P ecosystem faces more pressing challenges on the demand side than on the 
supply side. 

With the exception of these  two notable observations, it  seems  surprising that, despite relatively consistent 
differences  in  ranking  between  countries,  respondents  see  the  problems  and  challenges  in  their  country  in 
similar ways. While this substantial alignment of views across countries can be considered a relevant result in 
itself, the comparison with administrative and science capacity data also gives rise to a crucial question about 
the parameters of respondents’ assessments. Indeed, the fact that S4P professionals across Member States 
agree on most of the challenges facing their countries’ S4P ecosystems could possibly be due to their lack of 
clear benchmarks for international comparison. Having such benchmarks would allow them to consider their 
experiences in a wider context. However, the results could also suggest that, despite S4P performances that 
vary  among  the  counties  investigated,  the  fundamental  issues  for  an  effective  ecosystem  are  the  same 
everywhere and not sufficiently addressed with current solutions. 

 25 

Table 6. Ranking of Member States by administrative and scientific international comparisons 

Administrative capacity measures 
(a) 

EU 
average 

Denmark 

Greece 

France 

Lithuania 

Portugal 

Spain 

Strategic planning capacity (Bertelsmann Stiftung – 2016) 

Societal consultation (Bertelsmann – 2016) 

Government performance indicator (composite Eupack) 

Non-government expert advice (Bertelsmann SGI) 

Regulatory  impact  assessments  (primary  laws –  transparency, 
oversight, etc., OECD) 

Ex post policy evaluation (OECD) 

Interministerial coordination (Bertelsmann – SGI) 

QoG impartiality of PA 

Scientific capacity measures 
(source: EU innovation scoreboard) (b) 

New STEM doctorates per 1 000 inhabitants 

Percentage population having tertiary education aged 25–34 years 

Percentage  population  aged  25–64 years  participating  in  lifelong 
learning  

International scientific co-publications per million population 

Scientific publications among the top 10 % most cited publications 
worldwide  as  percentage  of  total  scientific  publications  of  the 
country 

R & D expenditure in the public sector (percentage of GDP) 

Employment in knowledge-intensive activities (percentage of total 
employment) 

NA 

NA 

NA 

NA 

NA 

NA 

NA 

NA 

EU 
average 

3 

6 

3 

3 

2 

3 

3 

1 

1 

6 

6 

 4 

3 

2 

2 

4 

5 

4 

3 

First 
quintile 

Fifth 
quintile 

Third 
quintile 

Fourth 
quintile 

Third 
quintile 

Fourth 
quintile 

1 

4 

1 

1 

1 

2 

5 

6 

6 

6 

5 

2 

2 

3 

2 

4 

1 

3 

4 

3 

5 

6 

4 

5 

5 

2 

3 

5 

2 

4 

Denmark 

Greece 

France 

Lithuania 

Portugal 

Spain 

2 

4 

1 

1 

1 

1 

1 

6 

5 

6 

6 

4 

5 

5 

4 

2 

2 

5 

5 

2 

2 

7 

1 

5 

7 

7 

7 

7 

5 

7 

4 

2 

3 

4 

6 

1 

3 

3 

4 

6 

6 

4 

(a) https://ec.europa.eu/social/main.jsp?pubId=8072&langId=en&catId=738&furtherPubs=yes&. 
(b) https://ec.europa.eu/docsroom/documents/45971. 
NB: Eupack, European public administration country knowledge; GDP, gross domestic product; QoG, quality of government; NA, not available; PA. Public Administration; SGI, Sustainable Governance Indicator; STEM, 
science, technology, engineering and mathematics. 
Source: Own elaboration based on information from the Eupack project and EU innovation scoreboard.

 26 

 
4.  Conclusions and outlook 

An important challenge for emerging S4P ecosystems is ensuring that ‘decision-makers have access to the best 
available  science  when  they  need  it,  in  a  format  they  can  use,  and  which  is  trusted  by  citizens’  (European 
Commission, 2022b). In this report, we explored how these challenges are perceived by those who are at the 
forefront of evidence-informed policymaking, whether on the side of knowledge supply or demand, or bridging 
the gap between the two. 

We  can  draw  several  lessons  from  this  exploratory  analysis  of  the  qualities  of  S4P  ecosystems  in  Europe. 
Overall, S4P professionals across the countries surveyed agree on the importance of institutional issues, which 
seem to matter the most. While the small sample size of the survey does not allow for strong inference on 
broader patterns at the EU level, this result calls for further analysis of and attention to be paid to the contextual 
conditions that enable effective exchanges at the science–policy interface. It seems not to be the lack of funding 
or  resources  that  hinders  effective  S4P  in  the  EU,  but  rather  putting  people  in  contact  with  each  other  and 
bridging the divide between the two communities. 

Closely behind the high level of agreement with statements about ecosystem fragmentation and the lack of 
meeting opportunities comes agreement with the facts that policymakers are constrained in what they can take 
on board and have limited competences and skills in S4P, and that science is often not ‘fit for purpose’. This 
indicates that work on the ability of scientists or knowledge brokers to translate science as well as on their 
absorptive capacity and skills is necessary. 

Despite some challenges being perceived as more pressing, however, the high levels of agreement observed 
for most of the items in the survey suggest wide consensus on the need for change in S4P ecosystems, with 
respondents’ choice for ‘agree’ or ‘strongly agree’ being, on average, 53 % over the 20 statements. This result, 
thus, can be interpreted as a call for change when echoed by all sides and across countries. In particular, our 
findings point towards a rather surprising alignment of views across Member States, with no stark differences 
between respondents across the EU (except perhaps Denmark). This result, however, should be considered with 
caution due to the unbalanced distribution of respondents across Member States, with an over-representation 
of respondents from some countries. Nonetheless, in terms of the four dimensions described, we did not identify 
any clear hierarchy in terms of needs. Within each dimension, there were varying levels of agreement. What 
emerges from this exploratory analysis is that change is needed across most of the dimensions, while some 
individual factors may matter less, as mentioned above. Overall, the survey offers an initial mapping of the 
main areas of intervention for further developing S4P ecosystems and lays the foundation for future research 
across the four dimensions. 

Considering  the  professional  affiliations  of  the  respondents,  there  are  role-specific  views  on  some  of  the 
problems, but there is also no stark difference. Knowledge brokers are the most critical in terms of agreement 
on the challenges that S4P ecosystems face. As experts on the matter, for whom S4P is a day-to-day job, this 
should be seen as a warning. More work on these intermediaries’ perspective is thus needed. Existing literature 
on the relationship between science and policy has long relied on the idea of two communities that use different 
operational  logic,  values  and  languages  (Caplan,  1979;  Pal,  1990).  Our  results,  with  knowledge  brokers  and 
users being often at the extremes in terms of levels of agreement with the statements and with knowledge 
producers being in a middle position, suggest, however, that these two communities may be less divergent than 
often theorised, at least when it comes to problem perception. 

In this regard, the JRC has been leading the way in trying to bridge the two communities and break down the 
science–policy binary separation, thus opening new avenues for research in terms of knowledge co-creation, 
policy  impact  and  citizen  engagement  (Šucha  and  Sienkiewicz,  2020).  In  Europe,  as  elsewhere,  science  is 
increasingly  under  ‘justification  pressure’  to  prove  its  societal  value,  while  policy  is  faced  with  complex 
challenges that can only be tackled with scientific knowledge, while also integrating considerations and analyses 
that are inclusive of experiential evidence. This, it seems to emerge from our survey, is the area towards which 
future research  could be  geared, to  understand  how to  build and  consolidate S4P ecosystems not only that 
bridge science and policy, but where the science–policy interface is co-produced (Maas et al., 2022). 

Other  than  no  strong  role-specific  differences,  we  did  not  find  any  significant  oppositional  patterns  in  the 
responses  that  could  have  shown  a  strongly  different  perception  between  scientists  and  policymakers.  The 
highest correlation was observed between responses to the statements about policymakers not asking the right 

27 

questions and science not being fit for purpose, suggesting that these two challenges go hand in hand from 
S4P professionals’ perspective. 

In terms of respondents’ agreement on specific issues, a somewhat surprising result concerned the self-critical 
perspective of knowledge users on policymakers’ constraints in taking science on board. While it is possible to 
interpret this result as a critique directed towards other knowledge users’ practices, rather than a self-critical 
stance, it is nonetheless a relevant finding. It suggests that policymakers, and knowledge users in general, are 
aware  of  these  constraints –  even  more  so  than  other  actors  in  S4P  ecosystems –  and  indicates  a  possible 
avenue for research and interventions that take into due account the political dimension of S4P and evidence-
informed policymaking, in line with recent work conducted by the JRC (Raykovska et al., 2019). 

Finally,  despite  the  limitations  mentioned  elsewhere,  our  comparative  country-level  results  offer  some 
meaningful considerations for further research. Indeed, country-wise, we found surprising homogeneity in the 
responses.  While  Denmark  stands  out  as  the  sole  exception,  with  lower  levels  of  agreement  with  most 
statements, across the other countries we observed substantial alignment in terms of challenge perceptions. 
This might be interpreted as a sign that, even though national contexts have a key role in influencing the specific 
qualities of Member States’ S4P ecosystems, most of the challenges – and perceptions of them – are likely to 
be shared across countries. Hence, these results call for further research from a comparative perspective across 
Member States, and encourage transnational and EU-wide actions to be taken to tackle the challenges discussed 
in this report, as there might well be a somewhat common solution to shared problems. 

An important caveat to all the results is that the evidence is based on a convenience sample, self-selected by 
interest to engage with the EU on questions around S4P, and is therefore not representative of all scientists, 
policymakers  and  knowledge  brokers.  In  addition,  the  sample  is  small,  especially  for  the  country-specific 
analysis  and  comparisons.  Such  a  limitation,  which  is  due  to  the  specific  circumstances  of  the  survey 
administration – which was conceived in the context of a broader initiative on S4P ecosystems – does not allow 
for generalisation at the European level. However, these preliminary results make clear the value of and need 
for additional evidence and further research to explore the perceptions of S4P professionals on a larger scale. 

The JRC will follow up on this research with further analyses at the country level, examining the country-specific 
S4P ecosystems with a dedicated technical support instrument funded by the European Commission (8). 

(8) 

https://knowledge4policy.ec.europa.eu/evidence-informed-policy-making/topic/reforms-science-policy-7-member-states_en. 

28 

 
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32 

 
List of abbreviations 

ERA 

JRC 

European Research Area 

Joint Research Centre 

OECD  Organisation for Economic Co-operation and Development 

R & D 

research and development 

R & I 

research and innovation 

S4P 

science for policy 

SWD 

Staff Working Document 

33 

 
List of figures 

Figure 1. Actors in the S4P ecosystem ........................................................................................................................................................7 

Figure 2. Overview of respondents by country and professional type ....................................................................... 13 

Figure 3. Survey results across all respondents: levels of agreement with statements about what 
is needed for a better S4P ecosystem ..................................................................................................................................................... 15 

Figure 4. Correlation patterns in S4P survey results ................................................................................................................. 17 

Figure 5. Responses by professional type............................................................................................................................................. 20 

Figure 6. Responses by country ...................................................................................................................................................................... 23 

34 

 
List of tables 

Table 1. Survey dimensions and short versions and full-text versions of survey statements ............. 10 

Table 2. Respondents by professional group...................................................................................................................................... 11 

Table 3. Summary of respondents by country and professional group ...................................................................... 12 

Table 4. Pairwise t-tests for knowledge professional types ............................................................................................... 19 

Table 5. Pairwise t-tests for countries .................................................................................................................................................... 23 

Table 6. Ranking of Member States by administrative and scientific international comparisons .... 26 

35 

 
Annexes 

Annex 1. Questionnaire 

Survey: Science for policy / science advice ecosystems in Europe – qualities 

Qualities of science for policy / science advice ecosystems in Europe 

The  European  Commission’s  Joint  Research  Centre  is  currently  organising  the  project  ‘Strengthening  and 

connecting eco-systems of science for policy across Europe’. 

The objectives of the project are to: 

1)  better understand science for policy / science advice ecosystems across Europe; 
2)  build a community of professionals who are involved in these ecosystems in the EU-27 and beyond; 
3)  facilitate  capacity-building  projects  that  strengthen  the  institutional  capacity  for  evidence-informed 

policymaking in Europe. 

To  achieve  these  objectives,  the  JRC  organises  interactive  online  workshops  and  runs  surveys  with/for 
professionals working at the science–policy interface. 

We would like to kindly ask you to complete the below survey containing 20 short statements about 
the qualities of the science for policy ecosystem you are most familiar with to agree or disagree 
with. 

Results  from  workshop  discussions  and  surveys  are  regularly  shared  with  those  interested.  The  data  are 
completely anonymised and will be used to inform debates in the workshops and JRC reports on science for 
policy and science advice institutions and processes. 

We would like to thank you very much in advance for kindly contributing to this project by completing our 
survey. 

In the case of questions, please do not hesitate to contact JRC-E4P-ECOSYSTEM@ec.europa.eu. 

A. About you 

Question 1.1.  What  is  your  nationality?  (This  is  used  to  identify  which  country  your  responses  apply  to.  If 
different, indicate under question 1.2.) (Selection Member States.) 

Question. If you responded non-EU, please provide your nationality here: 

Question 1.2. If different from the country whose nationality you hold, which science for policy / science advice 
ecosystem do your responses apply to? (Country; sector; international.) 

Question 2. In which professional sector are you working? 

Question. If other, please specify. 

Question 3. What is your job title? 

Question 4. Have you participated in one or more of the JRC ‘Science for Policy Eco-systems’ workshops? Yes/no. 

B. About the qualities of science for policy / science advice ecosystems 

To what extent do you agree with the following statements about the qualities of the science for 
policy / science advice ecosystem?  
5 = Strongly agree 
4 = Somewhat agree 
3 = Neither agree nor disagree 
2 = Somewhat disagree 
1 = Strongly disagree. 

36 

 
 
 
 
Answers should relate to the situation in your country (or the system you are most familiar with, 
as indicated in 1.2 above). 

NB:  
Science for policy / science advice ecosystems refer to those institutions and processes that are involved in 
producing, synthesising, translating, integrating and using scientific knowledge in policymaking. 

Policymakers include civil servants and elected politicians in governments and parliaments. 

Knowledge brokerage are processes and institutions that help connect the distinct systems of policymaking 
and science by facilitating information exchanges and collaboration (e.g. via knowledge synthesis, moderating 
co-creation processes, organising interdisciplinary cooperation).  

System view (six statements) 

Question 1.  The  science  for  policy /  science  advice  ecosystem  is  fragmented:  in  general  organisations  rarely 
coordinate their activities and are often not aware of each other’s activities. 

Question 2. Roles and processes within the science for policy / science advice ecosystem are clearly formalised 
(clear mandates, institutionalised mechanism, etc.). 

Question 3. Policymakers do not trust scientists (and vice versa). 

Question 4.  It  is  very  difficult  for  newly  interested  organisations  and  individuals  to  join  science  for  policy / 
science advice processes and existing structures. 

Question 5. Processes of production and use of scientific knowledge are not transparent to the public in the 
science for policy / advice ecosystem. 

Question 6. Lack of funding for science for policy / science advice structures and activities is the main obstacle 
to evidence-informed policymaking. 

The user side: policymaking (seven statements) 

Question 1. Policymakers recognise the difference between scientific knowledge and stakeholder opinions and 
other forms of analyses. 

Question 2. Policymakers tend to use scientific knowledge to justify (ex post) their decisions rather than inform 
them (ex ante). 

Question 3. Policymakers have the skills to broadly understand and critically appraise scientific evidence and 
arguments. 

Question 4. Policymakers know which scientific institutions and knowledge brokers in your country can provide 
evidence and analytical capacities to address their questions. 

Question 5. Policymakers  seek out  broad and  diverse scientific knowledge,  not only a  single expert/study, to 
inform their policy deliberations and design. 

Question 6. Policymakers are strongly constrained in their ability to take science knowledge on board and often 
need to prioritise other considerations (balancing regional interests, etc.) instead. 

Question 7. Most policymakers appreciate the unique value of scientific knowledge for policymaking. 

The knowledge supply side (four statements) 

Question 1. Scientists can expect recognition, rewards and/or support for science for policy / advice work by their 
employers, funders, and peers. 

Question 2. Scientific knowledge is often not available at the right moment in time to be useful for policymakers. 

Question 3. When participating in policymaking, scientific experts remain independent from the influences of 
policymakers. 

Question 4.  Scientific  organisations  have  set  up  dedicated  organisational  structures  and  processes  to  share 
scientific evidence with policymakers. 

37 

 
 
 
At the science–policy interface: knowledge brokerage (three statements) 

Question 1. Scientists and policymakers lack regular and well-supported opportunities to meet and exchange 
ideas. 

Question 2.  Scientific  knowledge  is  synthesised,  translated  and  formatted  in  a  way  in  the  ecosystem  that 
policymakers can use it easily. 

Question 3. Scientists receive questions from policymakers and knowledge brokers framed in such a way that 
they can provide useful evidence-informed inputs. 

Space for additional comments (one statement) 

Question 1. Please feel free to any comments as regards to strengths and weaknesses of the ecosystem 
you have commented on that were not covered by the previous statements. 

C. Next steps 

If you are interested in regular updates on the results, as well as workshops planned in the JRC online workshop 
series, please drop us an email JRC-E4P-ECOSYSTEM@ec.europa.eu or register for the project here. 

Registration is only necessary if you have not registered for the workshop series before. 

38 

 
 
 
 
Annex 2. Further analyses 

Figure A1. Specific answers by professional groups: knowledge producers (A), knowledge users (B) and other types of knowledge group (C) 

A 

39 

 
 
 
B 

40 

 
 
C 

NB: Sample size = 488, adjusted for only those respondents assigned to each of these three professional groups. The short versions of the statements are shown in the figure panels; see Table 1 for full 
statements. PM, policymaker; SC, scientist. Source: Own elaboration.

41 

 
 
 
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