Another implementation science is possible: engaging an ‘intelligent public’ in knowledge translation

ABSTRACT

As the world contends with the COVID-19 pandemic, scientific expertise has permeated political discourse and the phrase ‘following the science’ is being used to build trust and justify government decision-making. This phrase reflects a problematic assumption that there is one objective science to follow and that the use of scientific knowledge in decision-making is inherently neutral. In this article, we examine more closely the dense and intricate relationships, values, politics, and interests that determine whose knowledge counts, who gets to speak, who is spoken for, and with what consequences, in the translation of scientific knowledge. Drawing key insights from Stengers’ Manifesto for Slow Science, we argue that implementation science has a central role to play in problematising the historic dominance of certain voices and institutional structures that have come to symbolise trust, rigour, and knowledge. Yet to date, implementation science has tended to overlook these economic, social, historical, and political forces. Fraser’s conception of social justice and Jasanoff’s ‘technologies of humility’ are introduced as useful frameworks to extend the capacity of implementation science to engage the broader public as an ‘intelligent public’ in the translation of knowledge, during and beyond the pandemic.

KEYWORDS:

• Implementation science
• knowledge translation
• social justice
• knowledge economy
• evidence-based practice

Introduction

During the COVID-19 pandemic, the boundaries between science and politics blurred. Scientists had to work more closely with government than ever before, highlighting with painful clarity that science does not operate in a political vacuum (Ball, 2021). At the same time, politicians have used the statement ‘following the science’ as both a shorthand for a new ‘better’ era of politics, where government decisions will be based on scientists’ advice, and as a means of justifying difficult decisions (Colman et al., 2021). Sitting behind this statement is the assumption that we can access a singular truth through empirical enquiry and that the process by which this knowledge comes to be used in decision-making is inherently neutral. Popular discourse in the name of science, evidence, and safety has continued to conceal and ignore the ways in which science, economics, and politics interrelate. Our commentary focuses on the serious implications of this perspective – both for society and science.

The risk is, firstly, that science becomes a screen behind which politicians position themselves as ‘rational actors’, obscuring the true motives behind their choices (Carley et al., 2020). The pandemic has ravaged the lives of individuals, families, and communities, exacerbating and intensifying existing conditions of inequity and injustice (Maani et al., 2021; McGowan & Bambra, 2022). While moments of crisis, whether viral, humanitarian, or both, register their impact across all social domains, it is the already fractured experiences of inequity (including, but not limited to, poverty, gender, and structural racism) that become most discernible (Shadmi et al., 2020). Addressing these challenges is not a neutral process but requires a consideration of conflicting social values and interests; the value of lives lost when control measures are relaxed, and the value of wealth lost when they are not; the value of personal liberty and freedom, and the value of collective responsibility to protect the lives of others. These aspects are not uniformly weighted in our societies and their costs are felt most intensely by those who are marginalised and underserved (Rovelli, 2021). In the absence of open discussion based on a clear value system and a responsible arbitration between different interests and values, scientific knowledge becomes a ‘hunting ground’ (Ball, 2021) for rival political players to seek out the scientific knowledge that supports their own position.

Secondly, the emphasis on the importance of science raises fundamental questions about what kinds of ‘science' provide ‘valid' foundations for health-related choices and practices (i.e., what knowledge counts and whose knowledge matters in decisions relating to the public good). From the beginning of the pandemic, the government appeal to science was mostly restricted to health fields, leading to an abundance of important research on COVID-19 from clinical medicine, epidemiology, virology, immunology, and public health (Mercuri, 2020). However, seemingly absent from the conversation and press briefings were experts and data from other fields, such as sociology and the social sciences (Mercuri, 2020); fields that ‘concern more often than not the use and misuse of power' (Popper, 1971, p. 283) and that actively work with (as opposed to on) groups to address society’s inequities (Greenhalgh, 2018; Heinsch & Cribb, 2019). This absence reflects the wider epistemological tensions that exist in healthcare (including clinical practice, policy, and education) (Brosnan & Kirby, 2016), where epistemic legitimacy is partly derived from an alignment with the evidence-based medicine (EBM) movement (Greenhalgh, 2018; Turner, 1995), while perspectives that align with the social sciences and sociology can be marginalised (Currie & White, 2012).

Thirdly, the notion of a singular ‘scientific’ truth belies the value-laden nature of EBM (Kelly et al., 2015); the dominant hierarchical paradigm influencing the production and use of scientific knowledge in contemporary western societies (Estabrooks et al., 2008). While EBM can be a useful heuristic, Weiler (2009) argued that knowledge ‘hierarchies are the quintessential manifestation of power’ (p. 2) because they signify ‘whose knowledge matters’ and whose does not (p. 7). Depending on their application, these hierarchies can have serious ethical consequences. For example, thousands of lives were lost during the pandemic because of what was incorrectly claimed to be an ‘evidence based’ approach (Greenhalgh et al., 2022, p. 253). Further, in 2020, an absence of ‘perfect evidence’ led to erroneous policy delays in recommending that the general public use face masks to slow the transmission of COVID-19 (Greenhalgh et al., 2020, p. 3), triggering an ‘intellectual sparring match’ between different research streams in the scientific community (p. 1074). The dismissal of certain types of knowledge, coupled with the rapid public dispersion and overvaluing of findings from poorly designed or poorly vetted research (Carley et al., 2020), likely contributed to the shocking inequalities that have characterised the pandemic (Maani et al., 2021; McGowan & Bambra, 2022). Critiques of EBM are not new, yet the challenges stemming from the COVID-19 pandemic have arguably made the need for closer scrutiny of current knowledge practices and the dominant paradigm that underpins them, more urgent.

In this article, we start with an examination of the dense and intricate relationships, values, politics, and interests that determine whose knowledge counts, who gets to speak, who is spoken for, and with what consequences, in the translation of scientific knowledge. In the following sections, we then draw on Stengers’ (2018) Manifesto for Slow Science to consider the potential for a more critical implementation science; one that problematises the historic dominance of certain voices and institutional structures that have come to symbolise trust, rigour, and knowledge. Finally, Fraser’s (1996, 2013) conception of social justice and Jasanoff’s technologies of humility (2003, 2007) are introduced as useful frameworks to extend the capacity of implementation science to engage the broader intelligent public in the translation of knowledge.

A note on terminology

Before proceeding it is necessary to clarify our use of terminology. We view knowledge translation and implementation science as distinct, yet converging, fields. Both offer expanded views of the complex processes of knowledge exchange, yet both reflect a continuous pull towards epistemologies and methods reminiscent of the positivist paradigm – involving an instrumental view of knowledge and taken-for-granted assumptions about objectivity and political neutrality (Greenhalgh & Wieringa, 2011; Reimer-Kirkham et al., 2009). In these fields, terminologies frequently intersect and confuse, with the same terms used to convey different meanings or different terms used to convey the same (Graham et al., 2006; Greenhalgh & Wieringa, 2011). The use of terminology has also shifted over time, both incidentally and through debate (Gray et al., 2015).

Given this hybridity, we define and keep consistent our use of terms. In this commentary, we position implementation science as a distinct field that is broadly concerned with understanding how research knowledge (or evidence) can be successfully translated into practice to achieve research uptake and use (or evidence-based practice). While we recognise knowledge translation as a distinct field focused on the ‘synthesis, exchange and application of knowledge’ in practice (World Health Organization, 2005), in this commentary, we refer to it as a phenomenon (i.e., an observable event) that constitutes a core objective of implementation science.

Whose knowledge counts?

Again and again, it has been argued that knowledge is value laden and inseparable from power. Feminists like Gilmore (2015) contend that the production of knowledge is a political process controlled by those in society with the greatest power. Indigenous peoples have argued that the prominence of Western ontologies and epistemologies have reinforced the monocultural production of knowledge and, ultimately, the reproduction of colonial ideologies through academic institutions (Barber & Naepi, 2020; Bullen & Flavell, 2017). Critical theorists, too, propose that knowledge and power are intimately intertwined. For Foucault (1988, 1994), every exercise of power depends on a scaffold of knowledge that assumes the authority of the ‘truth’. Knowledge therefore has the power to make itself true to advance the interests and power of certain groups, while marginalising others (Foucault, 1988, 1994). These examples illustrate the deep connection between knowledge and the history, culture, and politics in which it is produced and used. It is thus important to examine how scientific knowledge is negotiated, resolved, and reinforced through the motivations, interests, and discourses that underlie its production and use.

Since the 1980s, the modern university has undergone a process of ‘diversification’ that increasingly emphasises private (over public) funding sources, the transfer of technology, and economic competitiveness (Kleinman & Vallas, 2001). This has, understandably, raised questions about the role of institutions (including academic, funding, and industrial) in shaping scientific research fields (Frickel & Moore, 2006a, 2006b), and elevating the perceived ‘value’ of scientific knowledge (Bai, 2020). Several reasons for the increasing importance placed on scientific research over other practices that produce knowledge – such as embodied, relational, and place-based systems of Indigenous knowledge (see Latulippe & Klenk, 2020) have been proposed. One is the impact of globalisation, which privileges the unregulated interplay and interdependence of markets, especially financial markets (Scott, 2009). This ideology promotes the production of extrinsic outcomes, such as research and skills formation as the primary purpose of the modern university to the exclusion of other social, intellectual, and cultural agendas. Closely associated with this is the discourse of the knowledge economy. In essence, the idea of a knowledge economy implies that there is a market for certain forms of knowledge, especially those that can be turned into a profit and enable organisations to gain a ‘competitive advantage’ (Brennan & McGowan, 2006, p. 145). Once knowledge is viewed as a top-down, marketable commodity, it risks becoming an instrument of social exclusion rather than a public good.

The narrow lens of economic reasoning, which reduces all values into costs and benefits (Barry, 2000), is particularly unsuited to the holistic integrated approach needed to deal with most social problems. The discourse of the knowledge economy is often ‘limited by [the] shallow technocratic, functionalist, [and] utilitarian values’ (Rooney & McKenna, 2005, p. 307), which privilege economic gain and ignore ‘fundamental features of human existence such as family, emotion, sentiment and love’ (p. 311). In this market-oriented environment, there is an inevitable blurring of boundaries between external and internal values, and a tendency to rely on the dominant cultural assumptions and material interests of institutions. These profit-driven interests leave little room for more altruistic conceptions of science and inhibit the kind of innovation and transformative change that would benefit historically disempowered groups (Hess, 2007; Woodhouse et al., 2002). Instead, they shape scientific inquiry into an ultra-competitive system that ‘sacrifices long-term productivity through an excessive obsession with short-term efficiency’ (Jaeger et al., 2022, p. 1). This unrelenting drive for efficiency and profitability can lead to ‘undone science’, in which areas of meaningful inquiry ‘are left unfunded, incomplete, or generally ignored’ (Frickel et al., 2010, p. 445).

The risks of ‘fast science’

When scientists are bound by industrial interests and the need to confirm the promises that attract their industrial partners, their shared concern for the reliability of the knowledge they produce might subsequently be destroyed. As Stengers (2011) observed, the knowledge economy leaves no time for debate and hesitation. The increasing privatisation of science means that industry can buy the results it wants, quickly, before competitors get the product to market (Muecke, 2018). This places the peer review process at risk. Under pressure, dissenting voices are disqualified, minority views are not considered, and peers forget to ask fundamental questions: why are we doing this? What will it be used for? (Muecke, 2018)? These questions would prompt necessary, deeper discourse with peers from other fields, such as sociology, philosophy, and the social sciences, who are well qualified to address them. Stengers (2018) referred to this lack of meaningful discourse as ‘fast science’; an environment divided into allies that matter and those who, whatever their concerns, should not disturb the progress of science.

In this fast science environment, ‘true scientists’ must resist any temptation to spend precious time negotiating ‘non-scientific’ questions that might also concern the wider public. Instead, situations are ‘dismembered’ and abstracted into objective and rational dimensions, and ‘arbitrary complications’ are discarded (Stengers, 2011). Reliability is achieved by purifying and controlling the knowledge production process. In this way, knowledge becomes bound to the constraints of its ‘native environment’; outside of this environment, its reliability is no longer a matter of scientific judgement, but subject to ‘the messy complications of the world’ (p.10).

Yet, a crisis shows up the strengths and weaknesses of a system and during the pandemic, the imperative of fast science ‘not to slow down, not to waste time’ (Stengers, 2018, p. 101) was amplified:

Ideas were placed on preprint servers without peer review, filling a knowledge vacuum, and in so doing became the only truth in town. The amplification of ideas through social media elevated flashy, reductive solutions over nuanced approaches that recognised the complexity of the messy world around us. (Galea, 2021, p. 1463)

Dinis-Oliveira (2020) warned of the risks ‘speed science’ poses to academic integrity and values, noting that ‘a pandemic with a “paperdemic” will be even more complicated to manage’ (p. 174). Galea (2021) too, emphasised that, in a time of uncertainty and crisis, such as the pandemic, there is a need for ‘epistemic humility’ about what we know and the boundaries of our knowledge. Unfortunately, he (2021) noted, the pandemic saw plenty of examples of ‘epistemic arrogance and the assertive exposition of positions at the expense of the measured thinking that befits a time characterised principally by unknowns’ (p. 1463). When science leans heavily into certitude and ignores messiness and uncertainty, a decisional impasse is created, one that does not afford decision-makers enough latitude to consider the broad range of factors that must equally occupy their decision-making. Thus, the COVID-19 pandemic highlighted the urgency of challenging our understanding and use of science (Greenhalgh et al., 2022) – confronting the consequences of the knowledge economy and its ‘powerful hold on our imaginative resources’ (Stengers, 2011, p. 12) and, in doing so, making space for a new scientific paradigm.

The role of implementation science

Several authors have argued that implementation science is increasingly relevant in helping decision-makers navigate the extensive and unwieldy scientific literature during the COVID-19 pandemic (O’Connor et al., 2020; Taylor et al., 2020; Wensing et al., 2020). These discussions revolved around the need to: (i) promote the strength of the evidence as a priority to optimise treatment and care provided during the pandemic and ensure that the dictum ‘do no harm’ is maintained; and (ii) develop new perspectives and approaches to the rapid collection and analysis of ‘real world’ data (Wensing et al., 2020). While these suggestions signal a promising recognition of the need for transformation and change in the translation and use of scientific knowledge, they often fail to address deeper considerations. For example, questions about what constitutes ‘strong evidence’ and how new approaches to the ‘rapid’ collection and analysis of data can avoid reproducing scientific abstraction and reductionism, to instead embrace complexity during the pandemic and beyond. To answer these questions, we argue that careful consideration of the ‘epistemological baggage’ (Sovacool & Hess, 2017, p. 741) of implementation science is needed.

The origins of implementation science lie in the evidence-based movement and attempts to broaden the scope of EBM to improve ‘clinical effectiveness’ and close the ‘implementation gap’ (Boulton et al., 2020, p. 379). However, implementation science is said to embrace the complexity and mediating relationships of the research-to-action process more fully than conventional EBM (Gray et al., 2014). As Greenhalgh and colleagues (2004) put it, implementation ‘requires changing the system and, hence, organisational as well as individual change’ (p. 591). This involves working with complexity, multiple contextual layers, and power politics (Ferlie et al., 2001, as cited in Greenhalgh et al., 2004).

In response to a growing acknowledgement of the inherent complexity of knowledge translation, implementation science is increasingly drawing on methodologies and approaches from the social sciences and humanities to explore translation on multidimensional, iterative, and flexible ways (Kitson et al., 2018). As Rooney and McKenna (2005) noted, the humanities and the qualitative methods within their toolkit have an important role to play in connecting values, knowledge, and ethics, subsequently ‘bringing “into view” the most complex areas of intellectual life’ (p. 316). The expansion of qualitative methods in implementation research signals the desire of those within the field to create a more sustained dialogue with the social sciences. While this represents an important development, Boulton and colleagues (2020) noted that contemporary implementation science seems to focus solely on reconciling social science with evidence-based methodologies, at the expense of ‘ignoring the dominating tendencies of the evidence-based movement’ (p. 379) from which it originates.

Rather than acknowledging its epistemological lineage and the paradigmatic assumptions this implies, implementation science tends to be framed as a pragmatic science that aims to systematise the implementation of ‘best evidence’. For example, in proposing a framework that incorporates implementation science into ethics, Sisk and colleagues (2020) acknowledged that the implementation of interventions can strongly influence whether people will enact normative values. Yet, the authors did not consider the (in)compatibility between these ethical norms, nor the values that underpin the field of implementation science. As Boulton and colleagues (2020) explained, ‘much implementation research does not stem from attempting to place implementation into a wider cultural/historical framework; rather, it stems from a pragmatic paradigm aiming to improve healthcare practices and patient outcomes’ (p. 385). Findings from our recent systematic review (Heinsch et al., 2021) too, reveal that implementation science has tended to overlook the economic, social, historical, and political forces that determine which voices are privileged and which are not, in decisions relating to the public good. It is thus at risk of obscuring wider questions of whose interests it is serving and to what end. To counter this, we suggest that implementation science must foster an independent space for critical questioning of its own taken for granted assumptions.

Another implementation science is possible

We propose that Stengers' (2018) Manifesto for Slow Science offers important insights for implementation science that can help to shift its focus to problematise the historic dominance of certain voices and institutional structures that have come to symbolise trust, rigour, and knowledge (notably, those that originate from the evidence-based movement) while sustaining the (intended or unintended) silencing of non-quantitative, non-positivist paradigms that have given voice to the oppressed and disadvantaged (Greenhalgh, 2018). For Stengers (2011), slow science is a reminder for scientists ‘to accept what is messy not as a defect but as what we have to learn to live and think in and with’ (p. 10). This, she argued, requires a radical redistribution of expertise; rather than seeking reliability through the objections of competent colleagues who all share the same values and work in similar environments, slow science pursues ‘out there’ reliability, gathering people – including academic and non-academic protagonists – around an issue that divides them, encouraging mutual learning. Critical social science, for example, employs participatory and action research approaches that emphasise research with (as opposed to on) marginalised groups, and the role of collectively produced knowledge in developing critical consciousness in such groups (Freire, 1973). From this perspective, the questioning of science by the broader public is not an imposition, or worse, an indignity. Rather, as Stengers (2011) observed, it is an opportunity for scientists to engage with a more discriminating and demanding public, ‘one that refuses any exaggeration of the power of scientific knowledge’ (p. 12). This, she noted, is a process that ‘will be, and must be, slow, difficult, rich in friction, pulling and tugging between diverging priorities’ (p. 11).

For implementation science, Stengers’ (2018) slow science perspective offers encouragement to resist the urge to develop rapid approaches to data collection and analysis (Wensing et al., 2020). Rather, slow science motivates us to connect with others via relationship and dialogue ‘to learn and draw new consequences from each other’s experience’ (Stengers, 2018, p. 127). We argue that it is through this connection and the embodied and values-driven knowledge that arises from it, that the dictum ‘do no harm’ can be maintained (Wensing et al., 2020, p. 2). As Stengers (2011) observed, connection between diverse protagonists, ‘including those who are not academically formatted but are empowered to object’ (p. 11), allows for the emergence of intercorrelated values; values that can emerge because those who meet have learned how to effectively connect them without commanding the authority of one over the other. Through this connection, she noted, somebody can feel transformed by the understanding or the perspective of someone else. Furthermore, something which appeared insignificant can be seen as something that might indeed matter. This form of connection, we propose, provides an important foundation for the inclusion of subjugated knowledges; ‘the humble stuff of lived experience and values’ (Weick, 2015, p. 35) that has been explicitly undervalued within the hierarchy of scientific respectability and ‘rigour’. Gaventa and Bivens (2014) referred to this as a process of ‘cognitive justice’, arguing that the production of democratic knowledge requires a democratic process, in which ‘the research process is itself a form of giving voice, of challenging power relationships, and of breaking down the dichotomies of the researcher and the researched’ (p. 169).

According to Stengers (2018), this requires, first and foremost, accepting that we are situated. Acknowledging situatedness demands a practice of positioning that carefully attends to the power relations at play in the processes of knowledge production (Haraway, 1988). We ourselves are part of an ‘infectious milieu’ of academic habits and pressures – the colleagues who argue that we are not being objective enough or the journals that insist that we conform to their norms. Rushing enthusiastically into this milieu can obscure our vision, separating us from our power to see that objectivity, under the guise of neutrality, hides a very specific position (male, white, heterosexual, human) (Haraway, 1988). Instead, Stengers (2018) encouraged us to learn how to connect with each other to resist and dismantle academic habits, activate the imagination, and ‘create interstices where another science could discover its own demands’ (p. 12–13). Haraway (1988) proposed that this might be achieved through a process of ‘partial connection'; accepting that knowledge is always incomplete and stitched together imperfectly, and joining with one another ‘to see together' through a process of ongoing critical interpretation and power-sensitive conversations (p. 586). In the following section, we propose two useful frameworks to extend the capacity of implementation science to engage the broader ‘intelligent public’ in a process of knowledge translation that joins the cacophonous and visionary voices of very different – and power-differen- tiated – communities into a collective position.

Engaging an intelligent public

Fraser’s concept of ‘parity of participation’ (1995, 1997, 2000, 2005, 2008), we believe, offers a useful framework to extend the capacity of implementation science to consider who is included or excluded in the process of engaging an intelligent public. Fraser (1996, 2013) proposed a multidimensional conception of justice that illuminates how social justice depends not only on the distribution of goods, but also on the patterns of recognition and participation in society. Someone can be systematically disadvantaged, and substantially so, if their identity is not recognised or valued and/or if they do not have a meaningful chance to help construct the structures and cultures from within which they pursue their lives (Heinsch & Cribb, 2019). She argued that a society is just only when its social arrangements ‘permit all to participate as peers in social life’ (2005, p. 73). She noted that injustice arises when ‘the boundaries of the community are drawn in a way that wrongly excludes some people from the chance to participate at all’ (2008, p. 408). Fraser thus, highlighted the need to challenge and democratise, not only the ‘what’ of justice (i.e., ‘what should count as a just ordering of social relations within a society’; 2005, pp. 70–71), but also the ‘who’ (i.e., ‘who counts as a subject of justice in a given matter’; 2008, p. 399) and the ‘how’ (i.e., the process through which the ‘who’ is determined). For implementation science, this highlights important opportunities to critically examine ‘whose’ interests and voices are represented in the construction of scientific knowledge and ‘how’ these boundaries are drawn.

To ensure parity of participation, Fraser (2008) proposed the ‘all-subjected principle’. According to this principle, ‘all those who are subject to a given governance structure have moral standing as subjects of justice in relation to it’ (p. 411). At its core, this principle emphasises the need to incorporate the interests of all those with a stake in the outcomes of democratic decisions. As Habermas (2006) argued, ‘deficits in democratic legitimation arise whenever the set of those involved in making democratic decisions fails to coincide with the set of those affected by them’ (p. 78). In the context of implementation science, the ‘all-subjected principle’ radically expands the space for legitimate knowledge claims, facilitating ‘collective intelligence’ by opening all knowledge processes and decisions to contestation by excluded voices.

The importance of public participation in the production and use of scientific knowledge is increasingly being recognised as ‘a standard operating procedure of democracy’ (Jasanoff, 2003), and is captured in new paradigms of scientific discovery, such as ‘Mode 2’ (Nowotny et al., 2003). Yet, participatory opportunities cannot, by themselves, ensure transparent and democratic scientific processes. People might lack the specialised knowledge and resources needed for meaningful participation and might therefore be easily misled by powerful actors pursuing their own interests. Alternatively, they might not be included early enough in the decision-making process to exercise influence. Even when participation is timely, ‘transparency may exacerbate rather than quell controversy, leading parties to endlessly deconstruct each other’s positions instead of deliberating effectively’ (Jasanoff, 2003, p. 237).

To resolve such a dilemma, Jasanoff (2003) argued that the substance of participation must change. She proposed a set of ‘technologies of humility’, which make explicit the values and interests that lurk within the technical, and ‘acknowledge from the start the need for plural viewpoints and collective learning’ (p. 240). Consisting of four focal points of framing, vulnerability, distribution, and learning, the ‘technologies of humility’ offer questions to ‘engage the human subject as an active, imaginative agent’ (p. 244). These questions ask: ‘What is the purpose; who will be hurt; who benefits; and how can we know?’ (p. 240). Public engagement on these points, Jasanoff argued, ‘promises to lead neither to a hardening of positions, nor to endless deconstruction, but instead to richer deliberation’ (p. 227). From this perspective, the question for implementation science is not whether the public should be involved in the production and use of scientific knowledge. This, we agree with Fraser, is a matter of social justice. Rather, the question is how to achieve more meaningful participation that enables citizens to bring their knowledge and skills to bear on the resolution of common problems that are often uncertain, ambiguous, and uncontrollable. Jasanoff’s technologies of humility represent a possible means of engaging different expert capabilities and facilitating different forms of connection between experts, decision-makers and the public. In her words, these ‘are pebbles thrown into a pond, with untested force and unforeseen ripples’ (p. 243). Yet, they offer an important starting point for a deeper debate on the future relationship between science and society.

Looking forward

So, what does ‘another’ implementation science look like? We believe that another implementation science is one that attempts to realise Stenger’s vision of a ‘reclaimed science’ (2011, p. 10); a science that resists the fast, competitive, benchmarked research of the knowledge economy and embraces the art of dealing with and learning from what scientists too often consider to be messy. We suggest, somewhat paradoxically, that such a vision requires an urgent ‘slowing down’ of implementation science. Rather than holding us back, slower approaches to implementation might actually help us to make faster progress in addressing the ‘wicked problems’ (Angeli et al., 2021) generated by the COVID-19 crisis. Slow science offers us an opportunity to do ‘less but better’, by thinking in longer timescales, surveying larger horizons, nurturing the next generation of scientists, facilitating collectiveness, acknowledging teamwork, and engaging in value-based decision making (Frith, 2020).

Although future implementation efforts might never fully escape the hold of the knowledge economy, there is critical work to be done in redefining how scientific knowledge is distributed and who gets to participate in its production. A parity of participation should not only be a goal of implementation science, but should be a basic premise, where the voices of those who are so often ignored by science (Graves et al., 2022) – racially disenfranchised, women, and LGBTQI + communities – instead, become fundamental to knowledge work (Boone et al., 2018). In achieving this goal, implementation science has an important, interrogative role to play, asking ‘whose interests are being served, and by what means?’ Implementation science, after all, is well placed to problematise the historic dominance of certain voices and institutional structures that have come to symbolise trust, rigour, and knowledge.

As we look to a more inclusive and ethically justifiable future of science, the time for industrial aims and pursuits of singular truths is over. Our commentary suggests it is time to fully acknowledge and respond to the messy reality of social, cultural, and economic life. We must address key dimensions and patterns that hinder public recognition and participation in the translation of knowledge, during and beyond the pandemic. Constant and consistent effort should be made to reflect on the assumptions that underscore the choices made in the planning, execution, and evaluation of implementation – to acknowledge the implications these have in furthering, or subverting, the public good. In progressing parity, Boone and colleagues (2018) reassured that ‘whatever the chosen pathways are, these will have downsides and will need constant re-evaluation’ (p. 323). Our analysis has argued that the participation of an ‘intelligent public’ must be the raison d’être of implementation work, a justification for our purpose; as we do not simply translate, but we translate for the purpose of meaningful outcomes.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The author(s) reported there is no funding associated with the work featured in this article.