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Author(s): Niko Soininen, Christopher M. Raymond, Hanna Tuomisto, Laura Ruotsalainen, 
Henrik Thorén, Andra-Ioana Horcea-Milcu, Milutin Stojanovic, Sanna Lehtinen, 
Rachel Mazac, Carlos Lamuela, Noora Korpelainen, Annukka Vainio, Reetta 
Toivanen, Timon McPhearson & Michiru Nagatsu 
 

Title: Bridge over troubled water: managing compatibility and conflict among thought 
collectives in sustainability science 

Year: 2022 

Version: Published version 

Copyright:   The Author(s) 2022 

Rights: CC BY 4.0 

Rights url: http://creativecommons.org/licenses/by/4.0/ 

 

Please cite the original version: 

Soininen, N., Raymond, C.M., Tuomisto, H. et al. Bridge over troubled water: managing 
compatibility and conflict among thought collectives in sustainability science. Sustain Sci 17, 27–44 
(2022). https://doi.org/10.1007/s11625-021-01068-w 



Vol.:(0123456789)1 3

Sustainability Science (2022) 17:27–44 
https://doi.org/10.1007/s11625-021-01068-w

ORIGINAL ARTICLE

Bridge over troubled water: managing compatibility and conflict 
among thought collectives in sustainability science

Niko Soininen1,14   · Christopher M. Raymond2,3,4,10,15 · Hanna Tuomisto3,10,16 · Laura Ruotsalainen5,10 · 
Henrik Thorén6 · Andra‑Ioana Horcea‑Milcu7 · Milutin Stojanovic8,10 · Sanna Lehtinen9,10 · Rachel Mazac4,10 · 
Carlos Lamuela10 · Noora Korpelainen10,11 · Annukka Vainio10,12 · Reetta Toivanen10,19 · Timon McPhearson13,17,18 · 
Michiru Nagatsu8,10

Received: 19 February 2021 / Accepted: 11 November 2021 / Published online: 1 December 2021 
© The Author(s) 2021

Abstract
Sustainability transformations call forth new forms and systems of knowledge across society. However, few tools and processes 
exist for promoting dialogue among different interests and normative stances in knowledge co-creation. In this article, we build 
on the notion of thought collectives to argue that understanding and moderating normative tensions are necessary if sustainability 
science is to provide successful solutions. Drawing on an analysis of the normative tensions between rival high-tech and low-
tech thought collectives in the mobility and food production sectors, we discuss three strategic approaches: applying common 
evaluative frameworks, building contextual convergence and embracing complexity. We argue that these strategies indicate a 
need to distinguish different kinds of reflexivity in managing tensions among thought collectives. As a practical conclusion, 
we establish sets of reflexive questions to help sustainability scientists deploy the knowledge management strategies discussed.

Handled by Osamu Saito, Institute for Global Environmental 
strategies, Japan.

 *	 Niko Soininen 
	 niko.soininen@uef.fi

1	 Center for Climate Change, Energy and Environmental Law, 
Department of Law, University of Eastern Finland, Joensuu, 
Finland

2	 Ecosystems and Environment Research Program, Faculty 
of Biological and Environmental Sciences, Helsinki Institute 
of Sustainability Science (HELSUS), University of Helsinki, 
Helsinki, Finland

3	 Department of Economics and Management, Faculty 
of Agriculture and Forestry, Helsinki Institute 
of Sustainability Science (HELSUS), University of Helsinki, 
Helsinki, Finland

4	 Department of Agricultural Sciences, Faculty of Agriculture 
and Forestry, Helsinki Institute of Sustainability Science 
(HELSUS), University of Helsinki, Helsinki, Finland

5	 Department of Computer Science and Helsinki Institute 
of Sustainability Science (HELSUS), University of Helsinki, 
Helsinki, Finland

6	 Department of Philosophy, Lund University, Lund, Sweden
7	 Hungarian Department of Biology and Ecology, 

Babes-Bolyai University, Cluj‑Napoca, Romania
8	 Practical Philosophy, Faculty of Social Sciences and Helsinki 

Institute of Sustainability Science (HELSUS), University 
of Helsinki, Helsinki, Finland

9	 Aalto University, School of Arts, Design and Architecture, 
Helsinki, Finland

10	 Helsinki Institute of Sustainability Science (HELSUS), 
University of Helsinki, Helsinki, Finland

11	 Faculty of Arts, Helsinki Institute of Sustainability Science 
(HELSUS), University of Helsinki, Helsinki, Finland

12	 Department of Forest Sciences, Helsinki Institute 
of Sustainability Science (HELSUS), University of Helsinki, 
Helsinki, Finland

13	 The New School, Urban Systems Lab, New York City, NY, 
USA

14	 UEF//Water, University of Eastern Finland, Kuopio, Finland
15	 Department of Landscape Architecture, Planning 

and Management, Swedish University of Agricultural 
Sciences, Uppsala, Sweden

16	 Natural Resources Institute Finland, Helsinki, Finland
17	 Cary Institute of Ecosystem Studies, New York City, NY, 

USA
18	 Stockholm Resilience Centre, Stockholm University, 

Stockholm, Sweden
19	 Faculty of Arts, Department of Cultures, University 

of Helsinki, Helsinki, Finland

http://orcid.org/0000-0003-0941-0594
http://crossmark.crossref.org/dialog/?doi=10.1007/s11625-021-01068-w&domain=pdf


28	 Sustainability Science (2022) 17:27–44

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Keywords  Thought collective · Sustainability science · 
Research management · Reflexivity · Mobility · Food 
production

Introduction

Systemic and rapid shifts towards sustainability across diverse 
sectors of society require new forms and systems of knowl-
edge that span structures, practices, cultures and values (Fazey 
et al. 2020). Developments in sustainability science increas-
ingly emphasise new collaborative practices, such as partici-
patory action, citizen science as well as co-creative and trans-
formational research (e.g., Bonney et al. 2014; Norström et al. 
2020). At local scales, we see the benefits of such collabora-
tion. For example, active urban experimentations, including 
City Labs, provide milieus for knowledge co-creation and 
testing of new sustainability solutions (e.g., Frantzeskaki and 
Kabisch 2016; Frantzeskaki et al. 2018). However, visions of 
desirable transformations and how to achieve them diverge 
considerably among different social groups, making it difficult 
to scale sustainability solutions. For example, groups empha-
sising technology-led transformation can differ in their views 
from those espousing market-, state- or citizen-led transfor-
mation (Scoones 2016) or those advocating nature-based 
solutions (Turnhout et al. 2020). Such systemic challenges 
are generally addressed by bridge-building between natural 
and social sciences (interdisciplinarity) or between academia 
and society (transdisciplinarity) (Kuhn 1962; Funtowicz and 
Ravetz 1993; Brewer 1999; Klein 2010; Wiek et al. 2012; 
Lang et al. 2012; Bernstein 2015; Osborne 2015).

Yet, discussions of inter- and transdisciplinarity often miss 
the point that values and practical orientations do not neatly 
coincide with any existing disciplinary or sectoral divisions. 
More recent action-oriented and co-productive approaches in 
sustainability science (e.g., Caniglia et al. 2021; Fazey et al. 
2020) emphasise a balance between pluralism and integration 
of different kinds of knowledge or ways of knowing, includ-
ing traditional ecological knowledges; however, they do not 
offer strategies for managing diverging visions of sustainabil-
ity (Turnhout et al. 2020). To directly address the challenge 
of bridging divergent perspectives, we deploy the concept of 
a thought collective (Fleck 1979 [1935]), defined as a group 
of individuals bound together by shared epistemic and non-
epistemic claims about truth (see Sect. 2 for further details).

On a coarse scale, sustainability science can be characterised 
as a thought collective that typically takes a systems perspective 
on sustainability challenges to discern patterns and articulate 
scientifically sound and societally viable solutions (Kläy et al. 
2015). However, on a finer scale, differing thought collectives 
emerge—ones that favour certain sustainability solutions over 
others and often represent different views on the benefits and 
costs of such solutions. Taking examples from the food sector, 

at one end of the spectrum we may find high-tech thought col-
lectives that rely heavily on new technologies and leapfrogging 
development (e.g., cellular agriculture and genetically modi-
fied organisms (GMO); at the other end, we may find low-tech 
collectives resorting to less technology-driven and more tra-
ditional approaches to sustainability (e.g., traditional farming 
practices) (see Sect. 2). Collectives at both ends of the spectrum 
are committed to sustainability as an overarching normative 
goal but view the costs and benefits of their preferred sustain-
ability solutions, and the pathways towards them, differently. 
This raises important questions: Where does this plurality origi-
nate? Is it a problem for sustainability? If so, what strategies 
can be deployed to deal with it? Finally, what kind of practices 
are needed to make sense of the normative tensions between 
thought collectives and their preferred sustainability solutions?

The formation of thought collectives has arguably 
increased fruitful interaction between scientific disciplines 
on the one hand, and between science and society on the 
other, as such collectives question the taken-for-granted 
assumptions within disciplines. However, the manage-
ment of normative tensions between thought collectives 
has attracted rather less scholarly attention. Researchers 
typically aim to identify the philosophical, structural and 
conceptual differences between collectives (e.g., Cahill and 
Humphrys 2019), and in some cases ask why the differences 
exist and what purposes they serve (Pohl and Wuelser 2019). 
However, to date few tools and processes have emerged for 
promoting dialogue and more discerning discussion across 
thought collectives having very different normative stances 
on sustainability solutions (Lahsen and Turnhout 2021). 
While different views are important for academic debate and 
scientific progress, in many cases views become entrenched, 
forcing decision-makers to choose sides when it comes to 
appropriate future directions for central sustainability chal-
lenges. Further polarisation of communities also risks unrav-
elling the social capital (networks and trust) underpinning 
solutions-oriented sustainability science in the future. We 
argue that sustainability science’s success in providing solu-
tions for society depends on its capacity to understand and 
moderate normative tensions among thought collectives and 
to take seriously different embedded worldviews, values and 
methods. We propose methodological strategies for manag-
ing tensions across thought collectives in sustainability sci-
ence and discuss how different strategies are underpinned by 
distinct types of reflexivity. Our analysis makes clear what 
we should be reflexive about as well as why and how we 
should be reflexive, responding to the recent calls for moving 
beyond engaging merely in ‘more reflexivity’ (Böstrom et al. 
2017; Montana et al. 2020) in the environmental sciences.

We build our argument around examples of two rival—
albeit simplified—thought collectives with preferred solu-
tions for tackling sustainability challenges in each of two 
sectors, mobility and food production. The rival collectives 



29Sustainability Science (2022) 17:27–44	

1 3

in each case can be characterised as ‘high-tech’ and ‘low-
tech’. Being high-tech means loosely leapfrogging devel-
opment to sustainability by technological means (e.g., 
autonomous vehicles in mobility and cellular agriculture 
and GMOs in food production), whereas low-tech means 
improving planning and management to realise this goal 
(e.g., integrated and densified urban planning in mobility 
and traditional farming practices, such as organic farming, 
in food production) (cf. Alexander and Yacoumis 2018). It 
should be noted already at this point that the designations 
high-tech and low-tech are points on a continuum, rather 
than categories in a strict dichotomy. Moreover, to make the 
normative assumptions behind different thought collectives 
clear, we present a somewhat sharper distinction between the 
collectives than can be empirically observed.

Section  2 begins by introducing and motivating our 
choice of a thought collective as an analytical unit. It then 
goes on to describe the sustainability challenge, the high- 
and low-tech thought collectives emerging to tackle it and 
the collectives’ respective strengths and weaknesses in the 
mobility and food sectors (2.1–2.2). In Sect. 3, we systema-
tise three knowledge-system management strategies for mak-
ing sense of and moderating the value-laden debates about 
sustainability (3.1–3.3). We continue in Sect. 4 by discussing 
the type of reflexivity the adoption of each strategy requires 
(4.1–4.3) and conclude by discussing a way forward for 
achieving more reflexive sustainability science.

Thought collectives, sustainability solutions 
and normative tensions

The concept of a thought collective (Fleck 1979 [1935]) 
refers to a group of individuals who share the practice of 
exchanging and developing of ideas. The members of a 
thought collective come to share a thought style—a way of 
thinking and reasoning grounded in some set of epistemic 
and non-epistemic values—that serves to set the collective’s 
priorities as regards the kinds of problems that are impor-
tant and how these can and should be solved. A thought 
collective is formed through close interactions and shared 
experiences of practitioners and scientists, but once formed 
it acts on its members to constrain and direct their values 
and cognition (see Hacking 2002 on styles of reasoning).

In addition to allowing analysis of collectives that cut across 
disciplines and sectors, Fleck’s framework has at least two 
other benefits. First, it is analytically and descriptively useful 
in highlighting that the rival perspectives we contrast in Sect. 2 
are not mere bundles of solutions; rather, they are positions of 
groups of people who hold particular (implicit and explicit) 
normative stances on how problems should be framed and 
structured and how different technologies can and should be 
applied and mainstreamed/scaled. Kuhn’s better-known notion 

of a paradigm, though acknowledging the collective and social 
nature of cognition to some extent, focuses more on theoreti-
cal commitments as the glue of a collective. The concept is 
less relevant to solution-oriented sustainability science than to 
his original episodes in mature sciences such as physics and 
chemistry. Second, Fleck’s approach is also practically useful, 
because its focus on practices and experiences as the ground-
ing of thought collectives implies the possibility of negotiating 
values and practices across collectives. The envisioned integra-
tion does not require theoretical unification or a paradigm shift, 
but instead suggests practice-focused knowledge-management 
strategies such as those we outline in Sect. 3.1

Multiple thought collectives with different views on sus-
tainability challenges and ways of overcoming them have 
been discussed in the sustainability science literature. One 
can cite those collectives drawing on the intrinsic values 
of nature as an ethical basis for conserving natural entities 
in contrast to those emphasising an instrumental approach 
(Justus et al. 2009; Mace 2014; Taylor et al. 2020) or a 
more pluralistic approach (Zafra-Calvo et al. 2020; Pascual 
et al. 2021). Other collectives again emphasise the practi-
cal stream of social innovation in sustainable energy tran-
sitions, in which new social innovation projects comple-
ment more traditional technological and efficiency-driven 
innovation. Contrasting with these are the collectives in the 
critical stream which maintain that social innovation is not 
simply an add-on to technological innovation (Wittmayer 
et al. 2020). In what follows, we draw upon examples of 
thought collectives in the mobility and food sectors, these 
being areas in which we have expertise. Our analysis serves 
to shine a spotlight on the normative tensions associated 
with the management of tangible sustainability challenges.

Rival thought collectives in urban mobility: 
autonomous vehicles vs. integrated and densified 
spatial planning

Transport is an important area in the context of sustain-
ability transformations because of its environmental, social 
and economic impacts. At present, 1.35 million people are 
killed and 10 million injured in car accidents every year 
globally (World Health Organization 2018). Traffic is the 
leading cause of death among 5- to 29-year-olds. Accord-
ing to the latest report of the Intergovernmental Panel on 
Climate Change (IPCC), transportation also accounts for 

1  Another prominent analytical category in science and technology 
studies is the sociotechnical imaginary, a collective vision and policy 
framework for achieving a good future through technology develop-
ment (Jasanoff and Kim 2015; Longhurst and Chilvers 2019). Differ-
ent thought collectives may share the same imaginary in this sense, 
and yet diverge on how best to realise the vision because of their dis-
tinct thought styles. Focusing on thought collectives is thus a useful 
heuristic in developing strategies for managing such divergence.



30	 Sustainability Science (2022) 17:27–44

1 3

23 per cent of total energy-related CO2 emissions globally 
(7.0 GtCO2eq, IPCC 2018). In this light, it is not surpris-
ing that the Sustainable Development Goals (SDG) for road 
safety aim at halving the number of global deaths and inju-
ries (SDG 3) and providing safe, affordable, accessible and 
sustainable transport systems for all (SDG 11).

Thought collectives that have emerged to provide solutions 
to these sustainability challenges of urban mobility diverge in 
composition and in their solutions along the high-tech–low-
tech continuum (Timms et al. 2014). On the high-tech side, 
the thought collective developing cars (e.g., car-shaped auton-
omous vehicles) is building upon automobility rationalities 
and car cultures. Car cultures and consumption entail more 
than rational choices; they embody social patterns with aes-
thetic and affective elements (Sheller 2004). There are even 
rival thought collectives within the high-tech collective, which 
comprises governmental and city planning representatives 
who envisage a future with shared autonomous vehicles and 
autonomous public transport (Fraedrich et al. 2019).

The high-tech collectives
 At the high-tech end of the spectrum are collectives that rely on the 

emergence of a completely autonomous traffic ecosystem consist-
ing of autonomous public transportation, autonomous private cars 
and unmanned aerial vehicles (UAVs) that will make it possible 
to achieve the sustainability goals set for mobility. The rationale 
of high-tech collectives builds on safety, emission reduction and 
efficiency gains in using shared private vehicles (Milakis et al. 
2017). The collectives consist mostly of artificial intelligence (AI) 
and transportation specialists in academia and in industry

 According to the high-tech collectives, autonomous vehicles pro-
vide a smoother driving experience compared to human-operated 
cars, as they are connected to an intelligent traffic ecosystem 
where vehicles can adjust their speed to traffic lights, drive closer 
to each other and drive faster due to advanced communica-
tions between vehicles. Autonomous vehicles also have fewer 
accidents, as the majority of accidents globally (93%) are caused 
by human error (Singh 2015). As the frequency of accidents 
is reduced, vehicles can be made much lighter, improving fuel 
economy and reducing range issues that limit the use of electricity 
and other alternative fuels (Anderson et al. 2016). Autonomous 
vehicles can also improve work efficiency as commutes may 
be used for working in the vehicle. Autonomous driving could 
improve social equality by enabling independence and reduced 
social isolation for the blind, disabled and others who are not able 
to drive or easily use public transportation (Anderson et al. 2016). 
A dystopian version of high-tech solutions includes many more 
vehicles on the roads. If transport systems are more efficient in 
managing the available space for mobility, current road networks 
can carry a much higher number of cars than they do today. Total 
carbon emissions may end up increasing instead of declining 
(Wadud et al. 2016). Moreover, without taking careful regula-
tory actions in implementing the autonomous traffic ecosystem, 
autonomous vehicles would be used for continuing the dominance 
of individual personal cars and not for improving means of public 
transportation, resulting in inequality in mobility (Mladenovic 
and McPherson 2016; Sparrow and Howard 2020). Autonomous 
vehicles may also require costly, additional investments, such as 
significant 5G network coverage and capacity

The low-tech collectives
 At the low-tech end of the spectrum are thought collectives that 

rely mainly on re-prioritising the already existing transportation 
technologies and increasing their efficiency and connectedness. 
The low-tech collectives consist mainly of urban planning, 
transportation and mobility scholars and professionals, as well 
as urban activist groups. These collectives typically argue that 
more fundamental changes in urban design and planning are 
needed to reach SDGs 3 and 11 (Banister 2011; Sustar et al. 
2020). The low-tech view emphasises an overall shift in para-
digm from private-vehicle-centred planning to human-centred 
planning (Gehl 2010) in order to create socially and ecologically 
more just transportation cultures (Martens 2016; Sheller 2018)

 Besides prioritizing the development of public transportation 
networks, urban planning oriented low-tech collectives would 
tackle the sustainability challenges of mobility by integrating 
and densifying residential, commercial and leisure districts to 
decrease the need for mobility (Meurs and Haaijer 2001; Gallo 
and Marinelli 2020). Decreased number of vehicles on the road 
would contribute to sustainability also through a lower rate of 
accidents and decreased CO2 emissions (Hickman and Banister 
2014; Mladenovic et al. 2020). The low-tech dystopia is that the 
change in existing transportation and planning paradigms would 
be too slow for reaching the sustainability goals. Implementation 
of the low-tech future requires remarkable change in the attitudes 
and behaviour of people on the move. Even though owning a 
private car is a lifestyle choice to some degree (Zhang 2017), the 
low-tech solutions aim at challenging this identity-related per-
ception of the private vehicle by more accessible and integrated 
forms of public transportation network and by making alternative 
transport modes such as bicycling and walking more lucrative 
choices. Moreover, these choices are constrained by the existing 
infrastructure and urban planning and may require unrealistic 
levels of regulation and government coercion to become a reality, 
especially outside densely populated urban areas

Rival thought collectives in food production: cellular 
agriculture and GMOs vs. traditional farming 
practices

Food systems are one of the main drivers of environmental 
change, yet their contribution to human health and well-
being is crucial (Campbell et al. 2017; Tuomisto et al. 2017; 
Willet et al. 2019). The mounting evidence of the need for 
health- and environment-related changes in food production 
and nutrition practices (Popkin 2006; Johnston, Fanzo and 
Cogill 2014; Willett et al. 2019) has sparked calls to address 
the sustainability of the food system (Tilman and Clark 
2014; Springmann et al. 2016; Clark et al. 2019; Willett 
et al. 2019). As the global population increases and income 
levels rise, food demand will increase in turn, in particu-
lar demand for animal-derived foods (Myers et al. 2017). 
Increased demand for crops could require one billion addi-
tional hectares of land to be cleared and result in greenhouse 
gas (GHG) equivalent emissions exceeding three gigatons 
per year if land continues to be cleared in poor nations for 
agricultural expansion by rich nations (Tilman et al. 2011).



31Sustainability Science (2022) 17:27–44	

1 3

Food is directly or indirectly linked to all SDGs, most 
closely to those conceived to reduce malnutrition (SDG 2), 
improve health and well-being (SDG 3), promote responsi-
ble consumption and production (SDG 12), combat climate 
change (SDG 13), conserve marine resources (SDG 14) and 
promote the sustainable use of terrestrial ecosystems (SDG 
15). It is widely agreed that the transformation of food sys-
tems to achieve the SDGs requires efforts on the part of 
all actors in the food systems at different levels, with these 
including major changes in policies, technologies and prac-
tices (FAO 2018).

Thought collectives have disagreements regarding the 
means to achieve the shared goals. Previous studies have 
shown that in the context of agri-food technologies the main 
considerations have been (un)naturalness, trust in natural 
sciences, risk management, ethics, the uncertainty of long-
term effects, and wider societal impacts (Marcu et al. (2015). 
Low-tech collectives propose reducing agricultural crop 
demand through sustainable dietary practices and chang-
ing the way food is produced through various sustainable 
food production practices (e.g., Agroecological Symbiosis) 
that could reduce land clearing, water use and associated 
species extinctions (Tilman and Clark 2014; Koppelmäki 
et al. 2019).

In contrast, novel, high-tech food production technologies 
(e.g., cultured meat, microbial proteins, cultured plant cells) 
may provide food for future diets while meeting multiple 
sustainability goals, such as lower environmental impacts, 
meeting essential nutritional needs for broader populations 
and providing viable alternatives to current animal-based 
foods (Tuomisto 2019). When compared to current animal-
source foods, these novel, high-tech foods can have signifi-
cant environmental benefits and ensure the nutritional ade-
quacy of diets (Parodi et al. 2018). Foods produced through 
cellular agriculture can have a complete array of essential 
nutrients (e.g., protein, calcium, B12, Omega-3) and are 
more water- and land-efficient, making them viable alterna-
tives to animal-source foods (Parodi et al. 2018). The two 
rival thought collectives in food systems have been theorised 
as possible post-Anthropocene futures for sustainable food 
systems (Mazac and Tuomisto 2020).

Diagnosing the tensions

Spelling out the differences between the two thought col-
lectives in urban mobility and in food production, respec-
tively, offers an interesting perspective on broader questions 
of sustainability science: when we see thought collectives 
diverging on sustainability solutions, what are we seeing? 
In this section we identify four different sources of norma-
tive disconnect between the thought collectives: 1. risk and 
uncertainty; 2. efficiency; 3. agency and power. and 4. ethics 

and justice. Each tension is described in a separate paragraph 
and the four are summarised in Table 1.

Mobility sector

In the case of risks and uncertainties in the urban mobility 
sector, representatives of the high-tech thought collectives 
usually have knowledge of and familiarity with the technolo-
gies related to autonomous vehicles (Penmetsa et al. 2019). 
However, they generally do not have enough knowledge of 
the changing societal conditions. The knowledge of low-
tech thought collectives is often based on the current trans-
portation system and its deficiencies rather than emerging 
future technologies (Mladenović 2019). Due to their differ-
ing worldviews, thought collectives supportive of “smart” 
and “sustainable” solutions view risk and uncertainties dif-
ferently when compared with low-tech collectives (Lyons 
2018).

Regarding efficiency, the high-tech thought collectives 
think that autonomous vehicles will bring benefits, as 
humans can use their time more effectively by working while 
in the vehicles (Fagnant and Kockelman 2014). However, 
one of the concerns of the low-tech thought collectives here 
is that this belief overlooks the effect of motion sickness 
and considers only white-collar labour (Fagnant and Kockel-
man 2015). The rival thought collectives address efficiency, 
energy efficiency in particular, in a very different way.

In the case of agency and power, the high-tech thought 
collectives worry that, despite regulation, the reduction in 
automobility will not be enough to provide significant sus-
tainability benefits (Ewing et al. 2017). According to the 
low-tech collectives, the high-tech collectives underestimate 
the importance of human agency in driving sustainability 
transitions (Spaargaren et al. 2011). Both thought collectives 
think that their pathways will bring social justice when driv-
ing and owning a car are no longer required (Sheller 2018). 
The former collectives see a way forward in using shared 
autonomous vehicles, the latter in decreasing the need to 
travel and investing in lighter modes of transport, such as 
cycling and walking.

As regards ethics and justice, the low-tech thought col-
lectives are worried about questions of future responsibil-
ity if the pathway favouring autonomous driving is realised 
(Koopman and Wagner 2017; Burton et al. 2020). Who will 
be responsible if there is an accident? Will it be the entity 
who developed the software, the one who developed the 
hardware (sensors) or the one who assembled the vehicle 
and sold it (Collingwood 2017)? How should the law and 
ethics address decision-making in a situation where the 
vehicle must choose whose life to save (Awad et al. 2018)? 
Who will own and store our data (Gulsrud et al. 2018)? The 
low-tech collectives are also concerned that citizens may 
have unequal possibilities to use autonomous vehicles and 



32	 Sustainability Science (2022) 17:27–44

1 3

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tu
re



33Sustainability Science (2022) 17:27–44	

1 3

that the attractiveness of autonomous vehicles might reduce 
walking or biking. This would reduce well-being and might 
ultimately lead to an increase rather than a decrease in the 
use of vehicles. Perhaps the key question to be addressed is, 
will it be possible to establish regulation to change people’s 
mobility behaviour to minimise car use and will this nega-
tively impact their scope of mobility (Anable 2005; Bothos 
et al. 2014; Anagnostopoulou et al. 2020)?

Food sector

Regarding risk and uncertainty, the high-tech thought collec-
tives consider the risks of not using the novel technologies 
higher than the potential unknown risks, whereas the low-
tech collectives espouse the opposite view.

In the case of efficiency, the low-tech thought collectives 
argue that the high-tech collectives’ focus on improving the 
efficiency of food production per unit of product will not 
lead to improved sustainability at the food system level, as 
greater efficiency may result in greater consumption (Böhm 
et al. 2018). For instance, a shift from outdoor agriculture to 
cellular agriculture could reduce the land area required for 
food production but might increase biofuel and bio-based 
material production on the fields, leading to even more seri-
ous sustainability challenges than at present.

The views on the importance of distribution of power 
also differ between the thought collectives. The low-tech 
thought collectives regard the concentration of power in only 
a few actors as problematic and would prefer to disperse 
power across small producers (Miller 2012). As the low-
tech farming practices are not patented, the access barrier to 
food production is low, requiring only simple resources and 
local knowledge about farming. Even though the high-tech 
thought collectives may share the concerns regarding the 
concentration of power, they do not think that the associated 
risks are so high that they will prevent the development of 
the technologies.

Where ethics and justice in the food system are con-
cerned, low-tech thought collectives think that livestock 
production is an integral part of sustainable agriculture, 
whereas the high-tech collectives regard the use of animals 
as unethical and unsafe due to animal-borne diseases (Dil-
worth and McGregor 2015).

All in all, our analysis above suggests that a fundamental 
plurality of values relating to (1) risk and uncertainty, (2) 
efficiency, (3) agency and power and (4) ethics and justice 
underlies the visions for sustainability transformation. More-
over, we would argue that the causal complexity and multi-
scale nature (both temporal and spatial) of the problems defy 
any attempt to evaluate these values within a single category, 
let alone a combination of categories. This analysis points 
to a need for meta-discussions on strategies for managing 

such value plurality (Norton 2017), to which we turn next 
in Sect. 3.

Knowledge‑system strategies for managing 
diverging sustainability solutions

In this section, we present three different approaches that 
couple procedural and methodological elements in order to 
manage the normative tensions between high- and low-tech 
thought collectives such as those identified the previous sec-
tion: (1) developing a common evaluative framework for 
identifying co-benefits and trade-offs between different posi-
tions, (2) shifting attention to the pragmatic decision-making 
processes protecting and encouraging the multiple values 
expressed by different thought collectives within a given 
situation and (3) allowing complexity and tensions to persist 
by avoiding common evaluation and contextual convergence.

Multiple approaches exist for dealing with normative ten-
sions and conflicts in sustainability challenges, with these 
including individualistic approaches for building empathic 
and emotional engagement (Brown et al. 2019); collabora-
tive approaches, whose aim is to coordinate different inter-
ests and reach solutions (Majer et al. 2021); and emergent, 
transdisciplinary design research, in which the research 
process is designed as it unfolds to cater for high levels of 
complexity, conflict and social fluidity (Breda and Swilling 
2019).

Here, building on Stepanova et al. (2020), we focus on 
the different rationalities which underpin normative/target 
knowledge concerning appropriate goals for action. Current 
sustainability science literature can be systematised in the 
form of a gradient of three broad strategies with different 
modes for managing normative tensions between thought 
collectives. First, the common evaluative framework empha-
sises logic, argumentation, and the use of different forms of 
statistical aggregation to identify and optimise sustainability 
solutions based on differing perspectives. The emphasis is 
on statistical rather than political argumentation. Second, the 
pragmatic decision-making process recognises the impor-
tance of situating the collectives’ differing values and inter-
ests in a specific problem context, and emphasises different 
forms of deliberation and negotiation to support, where pos-
sible, the achievement of shared values. Third, exploring 
complexity does not seek to support consensus but rather 
to bring conflicts to the surface in order to reveal new or 
alternative ways of dealing with sustainability challenges. 
(Fig. 1).

While these three approaches may not cover all existing 
knowledge-system management strategies, our view is that 
they cover the main lines of engagement in sustainability 
science literature. Each strategy is discussed in detail below.



34	 Sustainability Science (2022) 17:27–44

1 3

Developing a common evaluative framework: 
in search of a supervalue and shared metrics

The first knowledge-system strategy for managing tensions 
between different thought collectives is to set up a process 
that seeks to establish a common evaluative framework for 
comparing the co-benefits and trade-offs between sustain-
ability solutions. One key normative driver behind such 
a strategy is convergence-building between the different 
evaluation methods and values underpinning sustainability 
solutions. Common evaluative frameworks operate under 
the assumption that different evaluation methods, values 
and sustainability solutions are commensurate and can be 
reduced to shared supervalues (e.g., Pareto efficiency) and 
metrics (e.g., the World Bank’s Adjusted Net Savings, ANS); 
if not commensurable, the methods at least have compara-
ble units and methods (Kronenberg and Andersson 2019). 
If such a supervalue and the accompanying metrics can be 
agreed upon, common evaluative frameworks are useful in 
establishing a basis for assessing competing sustainability 
solutions (see Wallace et al. 2021). Some integrated assess-
ment models (IAMs) in climate policy (e.g., the Dynamic 
Integrated Climate Change (DICE) model) represent such 
frameworks (Nordhaus and Boyer 2000). Where commen-
surate metrics are lacking, other consistent frameworks are 
used, such as Multi-Criteria Decision Analysis (MCDA), 
which allows one to compare alternatives against a set of 
explicitly defined criteria (Langemeyer et al. 2016, 2020; 
Kremer et al. 2016). The criteria are assessed, weighted and 
aggregated in the analysis phase and then ranked by stake-
holders in the decision phase to inform different land-use 
options, for example (Esmail and Geneletti 2018). Other 
common frameworks include Bayesian Belief Networks 
(Barton et al. 2016) and the Vector Analytic Hierarchy Pro-
cess (Arnette et al. 2010).

The main benefit of the common evaluative framework 
approach is that it provides a systematic and mutually agree-
able basis for evaluating alternative futures. If the building 
of a shared evaluative framework succeeds, it can provide 
decision-makers a significant resource to evaluate syner-
gies and trade-offs. On the downside, reducing the differ-
ent sustainability solutions to a common evaluative frame-
work risks foregrounding certain values and metrics, such 
as quantifiable costs and benefits, and downplaying other 

values that may not be amenable to aggregation, examples 
being a diversity of relational values grounded in the eth-
ics of reciprocity and care (Chan et al. 2016; Himes and 
Muraca 2018) and traditional ecological knowledge (Casi 
et al. 2021). Proponents of some knowledge systems resist 
having their values reduced to preference rankings, because 
such rankings discount interactions and feedback processes 
deemed crucial to their culture and way of life (e.g., Ray-
mond et al. 2013; O’Connor and Kenter 2019). Furthermore, 
this instrumental logic does not allow hierarchies between 
scientific and other knowledge holders to be challenged 
(Turnhout et al. 2020).

In the mobility sector, studies have sought to optimise 
multi-criteria functions, such as accessibility, safety, legal 
rules, passenger preferences (e.g., comfort) and energy con-
sumption (Campos et al. 2009; Claussmann et al. 2018). For 
example, Multi-actor Multi-criteria Analysis (MAMCA) can 
include multiple stakeholders in the process of making deci-
sions about sustainable mobility, including an assessment 
of low-carbon transport policy (Huang et al. 2021). Core to 
this approach is stakeholder analysis, the creation of assess-
ment criteria, indicators and weights, and formulation of 
criteria for the analysis and ranking of weights (Macharis 
and Baudry 2018). In workshop environments, stakehold-
ers have an opportunity to interactively weigh and evalu-
ate scenarios in a tool. While different thought collectives 
may rank alternatives differently based on their own values, 
the MAMCA model is able to limit the set of good options 
to one or two alternatives in light of the optimal solution 
(Huang et al. 2021).

In the food sector, the Life Cycle Assessment (LCA) 
method is commonly used for estimating the environmen-
tal efficiency of agriculture and food production (Poore and 
Nemecek 2018). Proponents of low-tech farming practices 
have criticised the method, as it favours high-yield farming 
systems that use resources efficiently but ignores ecosys-
tem services that low-yield farming systems provide (van 
der Werf et al. 2020). This criticism has led to the develop-
ment of methods that combine traditional LCA with more 
advanced ecosystem service assessment (e.g., Jeswani 
et al. 2018). The LCA method is also criticised for the 
bias caused by subjective choices during the analysis. In 
other words, the LCA practitioner can either knowingly or 
unknowingly influence the results of the analysis through the 

Fig. 1   Three strategies forming a gradient for managing tensions between thought collectives and their respective assumptions



35Sustainability Science (2022) 17:27–44	

1 3

methodological choices and assumptions he or she makes. 
Proponents of LCA have sought to address this weakness 
through increased use of multi-criteria decision analysis and 
participatory methods in combination with LCA (De Luca 
2017).

Although common evaluative frameworks are valuable 
tools for understanding complex phenomena and aid deci-
sion-making, their operation assumes commensurable or 
comparable metrics. Given that different values underlying 
different thought collectives are not always commensurable 
(in optimisation) or comparable (in multi-criteria), as is the 
case in our mobility and food examples, what other alterna-
tives are there to manage normative tensions?

Building contextual convergence: plural inputs 
to practical decision‑making

The second knowledge-system management strategy 
embarks from a different starting point than common evalu-
ative frameworks do. The process for building convergence 
recognises that different value domains exist and cannot be 
aggregated or reduced to some supervalue or shared met-
ric (Chang 2001; O’Neill et al. 2008; Mason 2015; Arias-
Arevalo et al. 2018). In this situational or plural valuation 
approach, it is assumed that no single, overarching system 
of evaluation can identify a single, optimal outcome. This 
strategy thus shifts the procedural emphasis from “what has 
value and how much” (i.e., the common evaluative frame-
work approach) to the development of processes which ena-
ble diverse values to surface and be negotiated when consid-
ering tangible real-world problems in particular situations 
(Norton 2015, 2017; Zafra-Calvo et al. 2020).

The benefit of the strategy is that it seeks to connect 
knowledge to action-oriented approaches and to break down 
power, gender, economic and social inequalities among 
thought collectives. It also seeks to break down systems, 
structures, practices and highly specialised communica-
tions—akin to those found in a thought collective. This 
approach also allows for sustained feedback among nego-
tiation, decisions, actions and outcomes, enabling different 
thought collectives to understand each other’s perspectives 
and potentially reach a compromise.

One of the weaknesses of the strategy approach is that 
it is highly dependent on strong collaboration and commu-
nication among stakeholders and requires an institutional 
capacity for long-term participatory processes involving 
dialogue and negotiation (Zafra-Calvo et al. 2020). Those 
applying the approach rely upon boundary organisations 
that have the capacity and normative desire to connect key 
actors across thought collectives. In some cases, knowledge 
co-creation processes can be compromised by power asym-
metries, prompting a need for culturally sensitive dialogues 
(Matuk et al. 2020).

In the mobility sector, there is no specific academic 
literature focusing comprehensively on connecting future 
autonomous vehicle-based traffic and the urban planning 
perspective (Williams et al. 2020, cf. Thomopoulos and 
Givoni 2015; Mohorčich 2020). Williams et al. (2020) 
urge research communities and funders to start working 
actively towards such collaboration. However, examples 
can be found in the wider sustainable transport domain. 
Sustainable transport cases from Santiago and Temuco, 
Chile, have demonstrated the possibilities for delibera-
tive valuation and collaboration between citizens and the 
School of Transport Engineering at the Pontificia Uni-
versidad Católica (Chile) and a citizens’ urban planning 
organisation, Living City (Sagaris 2018). A living labora-
tory, grounded in participatory action research, was estab-
lished to shift from a bureaucratic approach to sustainable 
transport to a collaborative approach seeking convergence 
in values, concerns and preferences across citizens and dif-
ferent sectors of transport planning. As part of the devel-
opment of the Temuco-Padre Las Casas sustainable trans-
port plan, a process of free dialogue between participants 
and planning actors was established to openly discuss dif-
fering values associated with road safety and quality of 
urban space, social inclusion, gender and multiple-mode 
transport. The project educated citizens and government 
on how to use a Goal Achievement Matrix to evaluate 
how well specific projects and programmes align with 
the values, concerns and preferences of citizens and the 
transport sector. Despite the plurality of values and con-
cerns, convergence was built across differing perspectives, 
encouraging consistency in plan implementation. People 
with visual, physical and mental disabilities participated 
and identified issues of discrimination in the plan. The 
result was an innovative and more integrated plan with 
active engagement on the part of multiple stakeholders 
(Sagaris 2018).

In the food sector, the discussion on GMOs in the EU is 
an illustrative example of a procedural effort to support the 
convergence of thought collectives. To mitigate the tensions 
between different thought collectives, the European Food 
Safety Agency (EFSA 2005) has a permanent Stakeholder 
Consultative Platform to facilitate dialogue between con-
sumer groups, food and feed business operators, the food 
industry, the food trade and food-related NGOs. The plat-
form advises EFSA regarding its work programme and con-
sultation practices, provides feedback on the effectiveness of 
its policies, alerts it to key issues of current or emerging con-
cerns and risks and provides information and facilitates co-
operation at the technical level (EFSA 2005). The meetings 
take place on average three times per year. In the context of 
the development of GMO policies, the platform is seen as a 
step towards a more inclusive approach and contribution to 
democratic legitimacy (Dabrowska 2007). The practice has 



36	 Sustainability Science (2022) 17:27–44

1 3

also laid the ground for an interactive exchange of views 
between different thought collectives and enhanced mutual 
learning.

But what happens when such a procedural approach fails? 
How do we identify the meanings which are lost during the 
process, when inequalities become even more pronounced 
(e.g., Isaksson and Richardson 2009)? And what are the 
consequences of decisions based on this knowledge for cul-
turally and ethically justifiable futures (Matuk et al. 2020; 
Turnhout et al. 2020)? Depoliticisation of power relations is 
common to knowledge co-creation in sustainability science, 
particularly when striving for a consensus that is considered 
appropriate from a given thought collective’s perspective, 
or when failing to consider the wider political context in 
which sustainability solutions are embedded (Turnhout et al. 
2020). The challenge is to move from a “position of power-
over”—where some participants are dominated or manipu-
lated by others—to “power-with” where all stakeholders are 
empowered (Turnhout et al. 2020). Conflicts and dissensus 
are unavoidable in situations where knowledge integration 
has substantial implications for power relations, necessitat-
ing new ways of embracing complexity, redundancy and 
disagreement (Krieg and Toivanen 2021). This is where it 
may be useful to establish a complexity-embracing process 
that makes no assumptions of convergence.

Embracing complexity and dissensus—no 
assumption of convergence

By definition, in a complex knowledge-system manage-
ment strategy, sustainability scientists should not seek to 
establish common evaluative frameworks, or even estab-
lish a process seeking to build contextual convergence in 
specific decision-making situations through deliberation, 
negotiation and compromise. Rather, different actors should 
be brought together with the aim of hearing them out and 
arguing about their differing values, interests and concerns. 
The aim here would be to understand how each perspec-
tive contributes to grasping the complexity of the social, 
ecological and technological system and to understand the 
value of multiple competing claims to sustainability (Miller 
et al. 2011). The complexity-informed approach is based on 
complexity theory (Mitchell 2009; Capra and Luisi 2014). 
A similar epistemological stance in the philosophy of sci-
ence, namely scientific pluralism (Chang 2012), supports 
this attitude without presupposing integration (cf. Mitchell 
2002; Caniglia et al. 2021).

Procedures embracing complexity offer a valuable per-
spective for understanding the value of redundant, even com-
peting and conflicting, sustainability solutions in helping to 
“avoid erroneous ‘one-track’, ‘race to the future’ visions of 
progress” (Stirling 2010, p. 1031). Moreover, the complex-
ity strategy contributes to the repoliticisation of knowledge 

co-creation processes, reaffirming that conflict is an essen-
tial component of democracy (Turnhout et al. 2020). It thus 
offers a counterweight to contextual convergence (3.2), 
where there is often a tendency to reduce complexity to a 
‘shared’ set of aspirational principles for designing, imple-
menting, evaluating and scaling a given sustainability solu-
tion (Schäpke et al. 2018; Frantzeskaki et al. 2019).

On the downside, complexity-informed strategies offer 
no or very little help for decision-makers struggling to find 
the most effective, quick, or feasible pathways to sustain-
ability. The strategy also suggest there is a high societal 
cost in both knowledge generation (multiple sustainability 
solutions developed in tandem) and the implementation of 
pathways (lack of integration). This cost risks draining pub-
lic resources and slowing down transitions to sustainability 
before humanity crosses key global tipping points (Wash-
bourne et al. 2020). Moreover, by relying on the emergence 
of new pathways from complex patterns, the strategies may 
render the conflict between thought collectives susceptible 
to hijacking by interests not willing to respect planetary 
boundaries (Smyth et al. 2017).

The mobility sector reflects complex dynamics of mul-
tiple forms of (human and non-human) agency and power 
at play (Kitchin et al. 2017). While conflicts between high-
tech and low-tech thought collectives often centre around 
mobility, accessibility, parking space, and the density of 
urban living (Shoup 2005; Anderson et al. 2016; Creutzig 
et al. 2016), there are many other forms of agency and deci-
sion-making that remain hidden to citizens. For example, 
complex algorithms used in various phases of autonomous 
vehicle operations enable new, complex forms of governance 
that are difficult to trace or access unless one has compre-
hensive knowledge of what is taking place (Bissell 2018). 
Complexity-informed processes will be important in politi-
cising and making visible the different ethical standpoints 
and underlying logics of autonomous vehicles, enabling the 
public to better understand and balance the efficiency ben-
efits of the new technologies in relation to critical social and 
personal health considerations.

In the food sector, despite widespread support for broad 
goals such as food security and sustainable food produc-
tion and consumption, there may be disagreement between 
thought collectives on the actions required to achieve these 
goals (Tuomisto 2019). For example, there is a “repertoire 
of interpretations” of food security (Mooney and Hunt 2009; 
Carney 2012), each supported by its own thought collective 
and each having its own policy implications. Mooney and 
Hunt (2009) point out that there are three collective action 
frames underpinning the goal of food security (hunger, com-
munity and risk). The effort to achieve consensus inevitably 
generates contested claims that have substantive and nor-
mative dimensions. Unlike the plural perspective on values 
(3.2), this process leads to a contentious, multi-organisation 



37Sustainability Science (2022) 17:27–44	

1 3

political field of varying degrees of power wielded by dif-
ferent thought collectives, some being insiders to the sci-
ence process, others outsiders (Mooney and Hunt 2009). Yet, 
current multi-stakeholder processes (MSPs) are criticised 
for their inability to make visible alternative ways of under-
standing the complex system and counter-hegemonic posi-
tions (Duncan and Claeys 2018).

Strategies 3.1–3.3 open a range of options for managing 
normative tensions between thought collectives. Although 
forming a range of options to how normative tensions can 
be managed, all three strategies embark from very different 
worldviews, strengths and weaknesses. One size does not fit 
all. The next section puts forward a set of reflexive questions 
that would help a sustainability scientist to evaluate which 
strategy fits a particular context and what kind of reflexiv-
ity is required in applying each strategy. The discussion on 
reflexivity concludes with the identification of key research 
gaps and new insights needed to realise the dormant poten-
tialities of each knowledge-system management strategy.

Practicing reflexivity at multiple levels: what 
should we be reflexive about?

This section deals with how thought collectives can 
improve the application of the three knowledge-system 
management strategies through more reflexive practice. 
Our use of the notion of reflexivity is motivated by an 
increasing body of literature calling for reflexivity on the 
part of sustainability researchers (Wittmayer and Schapke 
2014; Popa et al. 2015; Haider et al. 2018; Fam et al. 2020; 
Montana et al. 2020). This literature characterises reflex-
ivity loosely as the critical awareness of one’s taken-for-
granted assumptions and values that guide one’s research, 
as well as the ability to revise these through collabora-
tive research in particular (see Suddaby et al. 2016 and 
Boström et al. 2016 for discussions grounded in sociol-
ogy, from which the notion originates). The focus of the 
analyses is often on who should be reflexive—individual 
researchers, research groups or scientific fields as institu-
tions—and how to implement reflexivity (von Wehrden 
et al. 2019; Freeth and Vilsmaier 2019; Montana et al. 
2020). However, we consider it necessary first to expli-
cate what we should be reflexive about more systemati-
cally (Suddaby et al. 2016). It is expected that divergence 
and convergence in thought collectives will be addressed 
by reflexivity on, for example, research stances in episte-
mology, methodology and implementation (Hazard et al. 
2019) or reflexivity on implicit normative values that 
guide sustainability research (Wiek et al. 2011). Carrying 
out the knowledge-system management strategies identi-
fied in Sect. 3 will be different depending on the context 
of any given project. Distinguishing what we should be 

reflexive about during the application of the three strate-
gies is a first step towards their deployment. Hence, we 
present a case for ‘multi-level reflexivity’ that will identify 
and apply each of the procedures sensibly.

Assumptions in the model: reflexivity 
about methodological choices

Practicing scientists often refer to the decisions about 
what assumptions to make in modelling as a matter of 
art and judgement, suggesting that such decisions draw 
on domain-specific and tacit expert knowledge (Muldoon-
Smith and McGuinness 2020), which is not transparent 
to outsiders. This mind-set is not exceptional in develop-
ing model-based common evaluative frameworks. Since 
these involve value-based parameter choices (e.g., what 
types of costs and benefits to consider; how much weight 
should be put on each; what the acceptable threshold of 
toxic chemicals in the environment is) as well as epistemic 
choices (e.g., how accurately to represent natural and 
social systems), the potential for divergence in opinions 
on how to choose the ‘right’ parameter looms even larger. 
Some scholars (e.g., Pindyck 2013, 2017) criticise Nord-
haus’s DICE model (Nordhaus 2017), a prominent IAM 
used in global climate policy, for example, for unjustified 
epistemic choices (e.g., the unrealistic damage function) 
while others (e.g., Winsberg 2018) criticise it for unjusti-
fied ethical assumptions of risk neutrality and the choice 
of a particular discount rate for future welfare.

The reflexive stance in the context of such contested 
integrated decision-support model-building means that 
scientists—individually or collectively—become more 
conscious and explicit about their epistemic and ethical 
choices. What is more, reflexive users also develop and 
adopt clear analytic guidelines to distinguish legitimate 
and illegitimate values (Intemann 2015), or to jointly 
analyse the ethical and evidentiary dimensions of model-
building for sustainability decision-making (Vezér et al. 
2018; Valles et al. 2019). Researchers seeking to manage 
the role of values can, for example, ask reflexive questions 
such as the following to promote ‘systemic accountability’:

1.	 What are the strengths and weaknesses of the research 
practices in evidence gathering and analysis?

2.	 What are the research practices’ ethical strengths and 
weaknesses?

3.	 How will the answer to Q1 affect ethical issues?
4.	 How will the answer to Q2 affect evidence gathering 

and analysis? (Valles et al. 2019, p. 270–271, slightly 
modified)



38	 Sustainability Science (2022) 17:27–44

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Assumptions about worldviews: reflexivity 
on societal decision‑making context

Disagreements on science-based sustainability policy are 
not limited to the choice of parameters and variables in 
integrated assessment models; rather they extend to the 
very choice of a given evaluative framework, especially 
when one tries to determine what the problem is in homog-
enising values among stakeholders. This type of disagree-
ment over platforms reveals not only epistemic and ethical 
tensions (or their coupling), but also conflicting world-
views (e.g., about human nature or historical visions such 
as progress and enlightenment) and the metaphysics of 
values (e.g., anthropocentrism vs. non-anthropocentrism). 
For these reasons, we cannot expect any comprehensive 
evaluative framework to achieve universal support.

One way in which practitioners respond to this chal-
lenge is Participatory Modelling (PM) (Voinov and Bous-
quet 2010; Voinov et al. 2016, 2018), a type of iterative 
and interactive collaborative model-building process 
among scientists, stakeholders and decision-makers. In 
PM, non-scientists or non-modellers (whom we refer to 
as stakeholders here) play important roles in different 
degrees: some are subjects from whom information is 
extracted, some co-learning participants, and some even 
co-management partners (Lynam et  al. 2007). Again, 
this process of stakeholder participation is often consid-
ered as “a craft, not a science” (Creighton 2005, cited 
in Voinov and Bousquet 2010, p. 1278), but in different 
ways than scientific modelling in general is an art form. 
First, researchers must consider what level of stakeholder 
involvement is appropriate, balancing their interests in and 
resources available for particular management and deci-
sion-making processes. Second, they have to assume the 
position of ‘neutral’ facilitators to gain stakeholders’ trust 
in the process, while at the same time remaining explicit 
about their own partial interests (e.g., promotion of a 
favoured modelling approach or data collection for aca-
demic publications). Third, they must be responsible for 
the validation of models in two distinct senses (Voinov and 
Bousquet 2010). First, model components and assumptions 
have to be consistent and theoretically and empirically 
grounded (i.e., traditional objective validation). In addi-
tion, models have to be ‘persuasive’ and accepted among 
stakeholders as the right problem-frames (i.e., intersubjec-
tive validation). Validity in the first sense may be at odds 
with validity in the second, for example when a simple 
agreeable framing might be misleading given the uncer-
tainty and complexity of the system behaviour. In sum, 
researchers seeking to manage the process of participatory 
modelling and its use may facilitate co-production by ask-
ing reflexive questions such as:

1.	 Who owns the process? Should the researcher–stake-
holder relation be one of consultant-client or studying-
studied, or should they be co-management partners? The 
ethical and legal standards to adopt depend on which 
relation is assumed.

2.	 Who chooses the model/problem framing? What are 
suitable modelling platforms/options for a given con-
text? How should researchers, as professionals, make 
comprehensive and usable toolboxes and frameworks 
available to stakeholders, going beyond promoting spe-
cific approaches of specific research groups?

3.	 Who is responsible for the validity of models? Can 
researchers be responsible for updating models beyond 
the project’s time horizon? (adapted from Voinov and 
Bousquet 2010, Sect. 4.2).

Assumptions about stake: reflexivity about interests 
and influences

According to the third strategy (3.3), conflict is not inher-
ently bad; it recognises that disputes and disagreements are 
inevitable. Conflict is detrimental only when it escalates to 
the level of destructive relations (Tropp 2015). Accordingly, 
the aim of reflexivity here is to encourage engagements 
across thought collectives that enable alternative perspec-
tives to be heard in a non-destructive way. Managing con-
flict requires better understanding of assumptions of stake, 
including different types of interests and levels of influence. 
It necessarily requires a shift from social to ‘societal’ psy-
chology, which considers not only individual differences but 
also the role of the media, political organisations, histori-
cal awareness and education processes (Reykowski 2015). 
Researchers seeking to manage the level of conflict can ask 
reflexive questions to promote ‘cooperative independence’ 
such as the following:

1.	 How can equal status between thought collectives be 
attained through institutional authorities, laws and cus-
toms? (Tropp 2015). For example, could this be achieved 
by changing the mechanisms through which knowledge 
is validated within and across thought collectives (Tengo 
et al. 2017)?

2.	 What strategies can be employed to enhance intergroup 
contact? For example, seeking out different opinions 
instead of avoiding them can build skills and resilience, 
which are needed in managing different opinions con-
structively (Böhm et al. 2020).

3.	 How can common identities between thought collec-
tives be built? For example, how might recategorisa-
tion of the groups under one inclusive, superordinate 
category increase empathy, self-disclosure and accept-
ance (Dovidio and Banfield 2015)? Such an identity 



39Sustainability Science (2022) 17:27–44	

1 3

can be built, for example, on perceived interdependence 
(Dovidio et al. 2020).

We have argued that sustainability science’s success 
in providing solutions for society depends on its capacity 
to understand and moderate normative tensions between 
thought collectives. In this section, responding to the recent 
calls for moving beyond merely ‘more reflexivity’ (Boström 
et al. 2017; Montana et al. 2020) in environmental sciences, 
we have provided a three-level typology of what type of 
reflexive research management is needed, focusing on how 
we should handle tensions across thought collectives in sus-
tainability science. We can summarise some of the insights 
as follows: in specific modelling contexts, researchers’ 
reflexivity revolves around assumptions underlying models 
and their ethical consequences (4.1). In broader problem-
framing contexts, researchers should reflect on their exact 
role in the process (4.2). In an open-ended space of thought 
collectives, tensions are not inherently bad but need to be 
contained by co-operative attitudes (4.3).

Conclusions and future pathways 
for sustainability science

Our current understanding of planetary boundaries requires 
a systemic and rapid shift in all sectors (McPhearson et al. 
2021), and in ways that engage with academics, decision-
makers and citizens (Patterson et al. 2021). These shifts 
are highly complex and require new forms and systems of 
knowledge. A key question is, how can sustainability sci-
ence navigate diverging views on sustainability solutions? 
To address this question, we have described a continuum 
of low-tech and high-tech collectives in the mobility and 
food sectors. In the mobility sector, the collectives diverge 
on whether the future of mobility should be based on leap-
frogging development to autonomous vehicles that would 
be safer and more fuel-efficient, or whether cities should 
resort to integrated and densified urban planning that co-
locates activities to reduce mobility needs in general. In the 
food sector, a similar divergence between high- and low-tech 
collectives was observed between those supporting cellular 
agriculture and GMOs on the one hand, and those support-
ing traditional farming practices on the other. While the dif-
ferences between the two collectives centre on sustainability 
solutions, there are deeper tensions between worldviews, 
values and methods at the heart of their discussions.

The divergent sustainability solutions between these col-
lectives are rooted in disagreement over the valuation of risk, 
uncertainty and efficiency, as well as over fundamental val-
ues and views on nature, agency, ethics and justice. These 
tensions, if left unmanaged, threaten the viability of sus-
tainability science as a problem-solving discipline. Against 

this background it is crucial to establish knowledge-system 
management strategies that have the potential to bridge the 
collectives and their divergent normative underpinnings, 
celebrating rather than ignoring divergences in interests 
or opinions across groups. Such bridging has promise in 
bringing forward sustainability solutions that are more 
legitimate and resilient compared to solutions developed in 
siloed thought collectives. We have put forward three strat-
egies for managing the normative tensions between collec-
tives: (1) common evaluative frameworks; (2) co-creation of 
knowledge geared towards practical problem-solving; and 
(3) accepting the complexity and plurality of values and 
facilitating a discerning discussion about values, interests, 
and stakes.

While all three strategies have utility in both mobility 
and food production, they also contain marked shortcom-
ings limiting their application. Rather than offering clear-cut 
answers, we have established a set of reflexive questions to 
help sustainability scientists employ these three strategies 
and untangle normative tensions arising from their employ-
ment. Instead of emphasising the need for more reflexivity, 
or asserting who should be reflexive, we maintain that there 
are different kinds of reflexivity at play in the context of the 
three management strategies, necessitating a novel multi-
level understanding of reflexivity.

Acknowledgements  AIHM acknowledges EU funding through the 
Marie Sklodowska‐Curie grant number 840207. The authors acknowl-
edge the support of Helsinki Sustainability Science Institute which 
received funding from the Academy of Finland. NS acknowledges 
UEF//Water programme and its funders Olvi Foundation, Saastamoinen 
Foundation and Wihuri Foundation. RT acknowledges Academy of 
Finland funded Centre of Excellence in Law, Identity and the European 
Narratives decision no. 336678.

Author contributions  NS, CM and MN conceived the idea in a joint 
workshop with input from HT, LR, HT, AIHM, MSRM, CL and NK. 
NS, CM and MN led the writing and revision process with input from 
HT, LR, HT, AIHM, MSRM, CL, SL, AV, RT and TM. HT and RM 
provided draft text for sections on food systems and LR, SL and CL 
on mobility systems. MN, MS and HT provided draft texts for the 
philosophical parts of the paper.

Funding  Open access funding provided by University of Eastern Fin-
land (UEF) including Kuopio University Hospital.

Open Access  This article is licensed under a Creative Commons Attri-
bution 4.0 International License, which permits use, sharing, adapta-
tion, distribution and reproduction in any medium or format, as long 
as you give appropriate credit to the original author(s) and the source, 
provide a link to the Creative Commons licence, and indicate if changes 
were made. The images or other third party material in this article are 
included in the article's Creative Commons licence, unless indicated 
otherwise in a credit line to the material. If material is not included in 
the article's Creative Commons licence and your intended use is not 
permitted by statutory regulation or exceeds the permitted use, you will 
need to obtain permission directly from the copyright holder. To view a 
copy of this licence, visit http://​creat​iveco​mmons.​org/​licen​ses/​by/4.​0/.

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40	 Sustainability Science (2022) 17:27–44

1 3

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