Transfer and Learning: Do They Go Together?
Summary and Keywords
While a phenomena dating back to antiquity, it wasn’t until the 1960s that American and European social scientists began seriously discussing occurrences in which it appeared as if localities, states and nations in close proximity were adopting similar policies and programs. These early diffusion studies led to a new field that has variously been referred to under titles such as policy transfer, lesson drawing, policy translations, and policy mobility. While having different focuses and agendas, all of these studies attempt to address issues associated with the movement (or active rejection of a possible movement) of ideas, information, policies, and programs from one political system to another.
While all transfer studies have helped focus social scientists’ attention on the processes and actors involved in the transfer of ideas, techniques, policies, information, and programs, a better link to the knowledge utilization and learning literatures would help advance the usefulness of transfer studies. At a minimum, by considering the insights from the learning and utilization literatures, social scientists should begin understanding some of the outlook changes that individuals involved in transfer undertake that impact individual and institutional long-term understanding of the process and results. It will also start to help opening up the policymaking process to further scrutiny, particularly in relation to where information is flowing and how it is being used as a policy develops and changes.
We learn more by looking for the answer to a question and not finding it than we do from learning the answer itself.
~ Lloyd Alexander
The world is a university and everyone in it is a teacher. Make sure when you wakeup in the morning you go to school.
~ Bishop T. D. Jakes
Since the late 1990s it has become common to encounter discussions related to how foreign ideas and models are transforming policies at the local, national, and international levels. In the academic literature of this movement there is an implicit (and increasingly explicit) belief that learning and knowledge updating lie at its core. This is questionable and, at best, misleading. Discussions tend to use terms like learning and rationality but seldom define what is meant by these terms. Even fewer studies attempt to differentiate learning from transfer, which are clearly different from one another. Similarly, most discussions of transfer use learning and knowledge interchangeably or use learning (and/or knowledge) to mean little more than taking a photocopy of something others are doing without consideration or analysis and using it in a different political system. Still others use the concepts of learning and knowledge to indicate behavioral modification brought about by experience or training. Some even use the term knowledge updating to refer to paradigm shifts brought about as a result of society-wide “social learning.” Complicating this is the noun-verb difference. Most studies of transfer treat learning as a noun, but what is transferred? Other studies and discussions use the transfer and learning concepts as verbs, but what is done with information? Often these studies discuss transfer in relation to transformation or translation as information works its way to and though a new policymaking system. As such, when looked at through the policy cycle, it becomes clear that transfer, learning, and knowledge updating are unlikely to be the same thing or to occur in a single event. It is more likely to be an iterative process where the introduction of new actors and institutions shapes the transfer (and learning processes) as a policy or idea interacts with and moves though the systems involved. Further, while policy transfer and learning processes are often treated as the same, they are different. Because of these differences, learning and transfer require a deeper analysis in order to better understand how what is occurring elsewhere is impacting the governing regimes around the globe.
The Existing State of the Transfer Literature
While policymakers have always looked to others for ideas and solutions, the modern study of the phenomena began in the 1960s. At this time scholars began discussing how innovations appeared to spread among jurisdictions in close proximity to each other. These led to the publication of Everett Rodgers’ Diffusion of Innovation, which explored the way innovations and technologies spread from one jurisdiction to other neighboring systems through direct information sharing and networks of communication. Following the publication of this text, diffusion studies emerged as a focus of policy analysis (Crain, 1966; Field, 1970; Robertson, 1967; Walker, 1969). These studies helped in the analysis of how the communication channels that existed between neighboring jurisdictions led to similarities in policies. Diffusion studies also focused on what happens when an idea or policy takes off. Specifically it was discovered that when diffusion occurs it tends to chart an S-shaped adoption curve across a region. The initial period of the S-curve sees fairly slow diffusion from one system to another. However, there is a “take-off” point where a number of jurisdictions join the bandwagon and adopt the innovation (reform) in short succession. This period lasts for a relatively short period, after which the number of systems adopting the reform trails off fairly quickly. When linked into the learning process a number of authors have found that the S-curve has a final period where the adoption process appears to go into reverse as nations who avoided jumping on the initial bandwagon actively decided not to adopt the innovation as they see the results of the reform in a range of systems and others start to dismantle the reform as a result of unexpected and undesirable outcomes (Brooks, 2007; Levi-Faur & Vigoda-Gadot, 2004; Shipan & Volden, 2008).
In Europe diffusion studies spread into new areas and advanced methodologically. Much of this occurred as diffusion concepts were applied to the activities of the European Union (EU), its internal functioning, its relations with potential accession states, and its activities involving foreign states and projects. Transfer studies have tended to concentrate on two aspects of this literature: the processes associated with uploading of policies from member states to the core institutions of the Union; and the processes of downloading the combined outcome of EU decisions to the Member States through directives and regulations and via individual actors bringing back ideas they liked (Bulmer, Dolowitz, Humphreys, & Padgett, 2007). Another part of this literature fits under the wider field of policy convergence and policy divergence, which looks for the causes of why states are becoming more alike in their socio-economic policy regimes and the reasons some appear to be diverging from this pattern.1
While these sets of literature are vast, there are two sets that are very relevant to this discussion. The first relates to the processes that accession nations undertook to alter their legal and political systems to comply with EU law (or acquis communautaire). While not discussed as a process of coercion, it is beyond doubt that all accession states were obligated to alter substantial components of their governing and legal regimes in order to join the Union. The second set of relevant literature is associated with the Open Method of Coordination (OMC). These studies added to the discussion not only examples of how nations are willing to borrow in order to be seen as legitimate but also examples of how the movement of policy and ideas within the Union shifted from hard law and top-down approaches to bring about convergence in Member State policies though directives and regulations to a softer approach utilizing soft law mechanisms such as benchmarking and league tabling designed to encourage the movement and implementation of best practices and policies amongst member states (see Bomberg & Paterson, 2000; Bulmer et al., 2007; Knill, 2005; Page, Wolman, & Connolly, 2004; Scott & Trubek, 2002; Trubek & Mosher, 2001).
While diffusion studies, particularly those that grew out of EU studies, helped focus attention on the role networks played (often in the background) in the temporal and geographic spread patterns of innovation between political jurisdictions and how the internal characteristics of an innovation could assist in the attractiveness of its diffusion (Crain, 1966; Eyestone, 1977; Gray, 1973), the concept and study of policy diffusion has been criticized on a range of fronts. For instance, most diffusion studies have explicitly or implicitly equated the spread of innovation with borrowers being involved in a deliberate and active effort to learn from the innovative system. However, as the concept of political systems grouping around suboptimal innovations illustrates, things can spread in the absence of reliable learning. Diffusion studies have also been criticized for ignoring how the inherent characteristics of an innovation and/or the borrowing system interact to influence its subsequent spread and adoption pattern. While not a universal issue in diffusion studies, the importance of the adaptation processes involved in the spread of innovations has been underdeveloped and seldom studied.
Diffusion studies have also been criticized for a tendency to underplay or ignore the micromechanisms involved in the spread of innovations, particularly when this spread occurs across national boundaries (Berry & Berry, 1990; Berry & Baybeck, 2005). As such, diffusion tends to ignore the role played by personalities, ideologies, and even politics in the movement of innovations. A final criticism worth mentioning relates to spurious diffusion. Because diffusion studies neglect the micromechanisms involved in learning and movement, there is a tendency to offer few definitive ways to prove that observed similarities are the result of learning versus the result of simple coincidence (Gilardi, 2003; Phillips & Ochs, 2004).2 In other words most diffusion studies offer no way to get around Galton’s problem (Braun & Gilardi, 2006; Jahn, 2006).
The early 1990s saw the emergence of a new wave of scholarship that built on earlier diffusion studies and focused on a process that became known as lesson drawing (Bennett, 1991; Bennett & Howlett, 1992; Rose, 1991, 1993; Wolman, 1992). Like diffusion, lesson drawing is interested in how ideas and policies spread. However, unlike most diffusion studies, lesson drawing is interested in the microprocesses involved in the movement of ideas and policies across geographic boundaries. For lesson-drawing, rationality is the key to explaining who becomes involved in the movement of ideas and policies, how they are involved, and how and why lesson drawing occurs. The logic is that policymakers are able to draw lessons from localities where policies are successfully working in a real-world situation. This allows them to reduce the risks and costs associated with the development of an entirely new policy in their home system when a similar problem arises (Rose, 1993, 2005). As such, while diffusion studies are primarily concerned with the spread pattern of a policy, lesson drawing examines the logic driving policymakers to look to exogenous systems for solutions to newly arisen (or unsolved standing) problems.
While the focus on rationality adds insights into why policymakers might be interested in and engage with the movement of foreign ideas and polices, lesson drawing’s genuine innovation was its focus on the microprocesses of the movement of ideas and policies and the role of rational learning in the transmission process. In this, the literature divided learning by the degree to which policymakers saw it as running from copying a foreign model to using information from a range of different policy models as an inspiration for the development of a “new” or hybrid model (Rose, 1991).
As with diffusion, a number of shortcomings have been pointed to in relation to lesson drawing. Probably the most frequently made criticism relates to lesson drawing’s reliance on the rational actor model as its primary explanatory variable. While some form of rationality might underpin the actions of some of the agents involved in lesson drawing, it is equally clear that many of the agents and decisions involved in the process rely on considerably less rationality than suggested by the lesson drawing literature. For instance, it has been well documented that there is a tendency in the international community to irrationally herd around sub-optimal norms in the areas of economic policy and utility regulation (Bulmer et al., 2007; Levi-Faur, 2002; Nelson & Morrissey, 2003). Similarly, studies have demonstrated that a range of transfers have occurred not out of the rationally to solve a specific problem but rather due to the fears and ideologies of policymakers (Hadjilisky, Pal, & Walker, 2017; Way, 2003). Indeed cultural factors have been shown to override rational impulses when agents engage in the transfer (or not) of sustainable development models, which are often shaped more by tacit, culturally embedded beliefs than by any rational analysis of what is occurring elsewhere (see Dolowitz & Medearis, 2009; Dolowitz, Kelley, & Maderis, 2013).
A second criticism of the lesson drawing literature is its tendency to argue that lessons travel as a result of a voluntary processes where borrowers actively look for solutions to their problems. While it is likely that a range of bilateral transfers between advanced industrial nations are more-or-less voluntary, it is much less likely to be true of interactions occurring between advanced and developing nations or between advanced and underdeveloped nations (Stone, 2001; Drahos, 2002; Busch & Jörgens, 2005). It has been demonstrated that it is equally untrue that entirely voluntary motivations occur when developing nations turn to or are forced to engage with international lending institutions ad organizations (Green, Ottoson, Garcia, & Hiatt, 2009). International governing organizations (IGOs) and nongovernmental organizations (NGOs) have also been shown to include more-or-less coercive mechanisms involving conditionality or obligations in exchange for financial support. This has most clearly been illustrated by the EU in relation to its activities with African nations, border states, and those wanting to join the Union. Beazer and Woo (2016) captured this process while studying the IMF:
The International Monetary Fund (IMF) often seeks to influence countries’ domestic public policy. . . . One increasingly exercised took at the IMF’s disposal is conditionality, or explicitly linking financial support to borrowing governments’ commitment to policy reform. . . . The IMF and other international institutions use conditionality to encourage governments in crisis to adopt difficult . . . reforms that domestic leaders might otherwise avoid. . . . IMF programs have enormous economic and social consequences for participating countries.
Part of the explanation for the involuntary nature of these interactions is that they occur between agents operating under unequal power configurations. Not only are these interactions unlikely to be voluntary in nature but they are less likely to involve learning (or learning as intended) because, “changes in the thinking of political leaders . . . are not usually the sort of things that can be ‘engineered’ by actors who are external to the country in question” (Booth, 2005, p. 1; see also Hadjilisky et al., 2017). As such, a number of unexpected outcomes can result from policymakers’ failure to develop the knowledge necessary to understand why a policy that worked well in one system did not work as well when they transfer it into their own system. Similarly, in these situations it is likely that once the policy enters the system, indigenous actors will work at co-opting the policy in ways that minimize their need to change it or the ways the policy affects the existing order of things.
Building on the diffusion and lesson drawing literatures, a group of scholars began discussing what has come to be known as policy transfer (Dolowitz & Marsh, 1996, 2000; Evans & Davies, 1999; Radaelli, 2000). At its core, policy transfer is “a process by which knowledge of policies, administrative arrangements, institutions and ideas in one political system is used in the development of similar features in another political system” (Dolowitz & Marsh, 2000, p. 3).3 To help frame the analysis, a series of questions were developed to assess the macro and microprocesses involved in the movement of policies, ideas, techniques, and information from one political system to another, from one time to another, and/or from the international to the national or local (Dolowitz & Marsh, 1996; Evans & Davies, 1999). By focusing on what moved, who moved it, and into what “conditions” a policy was moved, the transfer literature was better able to examine the question of what was learned (or not) during the process of movement, development, and implementation than either the diffusion or lesson drawing literatures had. It was also better able to address issues associated with why transfer often appeared to end in failure to achieve the desired goals of policymakers (Marsh & Sharman, 2009).
While the policy transfer literature has much to commend, it too has shortcomings. First, much of the literature focuses on voluntary transfer process. This has allowed the role and processes involved in less voluntary forms of transfer to remain fairly understudied, particularly as they interact within political systems, semi-independent sub-units of political systems (e.g., British Council), bilateral arrangements and pilot projects, and the role of international financial institutions (IFIs), IGOs, and domestic and international NGOs in the spread of global paradigms and “best practice” models. Transfer studies have also tended to neglect the human questions—the political, ideological, and unobservable (tacit beliefs) involved in transfer. As a result, much of the existing literature looks overly mechanistic: If you have problem X, look to system Y, borrow Z, and then α will follow. In reality this seldom occurs, and at a minimum lessons combine with other information and ideas prior to entering the political process and continue this as a policy works its way through the policymaking process. At any stage it is possible that the “lesson” will be transformed and/or translated into something new or more palatable to the importing/receiving system. More importantly, by focusing on the voluntary and logical side of transfer, the literature has tended to overlook the possibility that lessons might emerge and be transformed by ideological predispositions, whom policymakers are willing (or able) to talk to, and what the transferring system shows (or the borrowing system sees). This links to a lack of analysis of agency and motivation (or to equating it with the rational need to solve a problem) in most transfer studies. At a minimum this hides the irrationality involved in transfer associated with political motivations and ideologies. Or as Meseguer and Gilardi (2009) argue, “[E]ven if a particular policy is showing good results elsewhere, it may not spread if it is found to be ideologically alien, electorally risky and/or unlikely to be passed” (p. 533).
This is itself linked to the role of motivation, which is often overlooked by all types of transfer studies. If transfer studies integrated motivations that underpin the activities of lenders and receivers, it might begin to better explain where and why actors turn to one location for information but not others. Motivation can also start to draw in the concept of learning and how deeply agents become involved in learning when engaged in transfer, policymaking, and implementation. For instance, a politician might engage in transfer to find a model he or she can use to symbolically appear to be doing something. From a different position, this same politician might engage in transfer in order to create a policy capable of meeting an indigenous need. The same policymaker working at implementing a policy may be motivated to look to other systems to discover how the technical aspects of the policy operate in the originating system in order to discover the minutiae of how it is embedded into the wider policy arena (Dolowitz & Medearis, 2009).
While much of the literature suggests policies are taken wholesale, in reality, borrowed ideas and policies will generally undergo substantial transformations. Rather than D being borrowed from E and implemented exactly as D appeared in system F, policymakers involved in policy transfer and policymaking “are like a composer writing a symphony for a number of instruments; the quality of the symphony will depend upon the melody written for each instrument and also upon the combination of the many melodic lines” (Sharma, 2009, p. 58). By neglecting the complexities of the process associated with the development of a policy and the nature of learning involved in the movement and transformation of ideas, information, and policies, the transfer literature is missing much of the micro-detail of the end product, possibly leading to much misunderstanding and misrepresentation.
Translations and Mobilities
While transfer is an improvement on what came before, its shortcomings have led a new group of scholars to relabel and refocus their study on the translations that occur to initial ideas and policies as they work their way from one system to another and then through to the implementation process (Clark, Bainton, Lendvai, & Stubbs, 2015; McCann, 2011).4 While there are differences between the mobilities and translation literatures, at their core both attempt to analyze how hybridization, adaption, and mutation occur during the movement of a policy, and thus, how ideas and policies are translated (Prince, 2009). In brief, both are concerned with how “place, space and scale, coupled with an anthropological/sociological attention to social relations, networks and ‘small p’ politics, both within and beyond institutions of governance, promise to deepen and strengthen” understanding of the role “foreign” has in the policy process (McCann & Ward, 2013, p. 3). As such, instead of seeing transfer as a point-to-point process, translations and mobilities attempt to broaden the study so that transfer is seen as “a global-relational social product—one produced by its circulation . . . among cities, as much as its development in cities. . . .” (p. 5). For these literatures, policy is not something waiting to be “taken” or “sent” from one political system to another; rather, it is developed in networks that live in the ether surrounding and engulfing decision-makers. In the simple act of moving, policies are mutated as they combine with other ideas, policies, and experiences. As such, translation can be seen as “a series of interesting, and sometimes even surprising, disturbances can occur in the spaces between the ‘creation,’ the ‘transmission’ and the ‘interpretation’ or ‘reception’ of policy meanings” (Lendvai & Stubbs, 2007, p. 175). The overall goal of the mobilities and translations literature is to understand how the settings in which policies move transform the policy and influence the impact of what is received. Not only are transformations occurring while the policy moves, but it continues its transformation as it works its way through the receiving system and into its implementation (Peck & Theodore, 2015; Porto, 2016).
While the idea of translation is clearly appropriate for some transfers, it is less obvious for others, particularly where one sees a replication emerge out of the process. In a similar vein, one of the most difficult issues with adapting a translations perspective to the study of transfer is attempting to fit the analysis into social constructivism. Thus, most translation studies attach a few sentences or paragraphs on social constructivist analysis, but this clearly takes a back seat to the standard questions of who, what, when, where, and why found in diffusion, lesson drawing, and policy transfer.
Learning and Policy Transfer?
All told, much of the transfer literature appears to offer mechanistic formulations of the transfer process: If you have problem X, look to system Y (or W, N and G), borrow Z, and α will follow. Looking and taking is clearly not the whole picture of what occurs when actors engage in policy transfer. Rather for change to occur, there must be an element of learning involved. And the link between learning in the policy development and transfer processes is considerably more complicated than simply taking a pre-wrapped policy off the shelf of another government’s policy regime. At a minimum the nomenclature associated with transfer implies that a range exists in the level to which actors engage in knowledge updating and that there are a range of subtleties in how lessons are subsequently applied when policies are developed. For instance, lesson drawing implies that the actors involved in the transfer process engage in a rational learning process and that this occurs before, during, and after the transfer takes place due to a series of ongoing evaluative processes (Rose, 1991, 2005).5 On the other hand, diffusion often appears to happen in the absence of any formal learning and little observable knowledge updating. As such, “while learning is central to ‘the human condition,’ it is not easy to define.” Particularly, “learning need not process information correctly, draw valid inferences, nor improve diagnosis and policy recommendations [emphasis added]” (Weyland, 2004, pp. 4–5). It is equally clear that “humans never look at ‘the facts’ with complete neutrality and objectivity, but always interpret them in light of general cognitive schemes and the specific theories they embrace” (Weyland, 2004, p. 5). Thus, what is learned does not necessarily lead to a better understanding of the existing situation, the situation existing in the system/s that were looked to, or necessarily a better understanding of the impact the global environment might have on the transfer process.
As with transfer, much of the existing learning literature focuses on observable change in how things are currently occurring. However, when viewed through the transfer process, learning can occur in the absence of immediate or directly observable change. For example, if the individual or group of agents who engaged in learning about a foreign political system is not positioned in an institution or policymaking system in such a way that they can introduce their lesson, nothing may come of it (i.e., no change), even though learning and transfer occurred. It should be stressed that this is not necessarily the end of the process; a “window of opportunity” may open (see Kingdon, 1995). When the window opens, as long as those that acquired information are in a position to inject it into the discussion, then their knowledge of a foreign system may be used to shape a policy or political output (i.e., bring about change). In a similar way, individuals operating in larger institutions often find that when they feed information into the policy processes, it must first go through institutional processing before it can find expression. In these circumstances, information originating elsewhere may be expressed in ways that make it unrecognizable as the lesson that was initially transferred. This is particularly likely when the information transferred is modified to better match the pre-existing internal psychological filters an agent or institution uses to understand the world, or when the information is recombined with other ideas that have been “stored” for later use (Weber & Hsee, 2001).
Tied to the issue of transformed and unused lessons, most transfer studies present learning as if it was easy and perfect. In reality when learning is viewed as part of the transfer process, engagement in the learning process can vary along a continuum running from full engagement to no engagement. Based on the level of learning engagement involved in the transfer process, it is possible to see learning as falling along a continuum running from perfect learning all the way to minimal learning. Stone (2004) refers to these two extremes as soft and hard learning. Others have discussed the process as single-looped and double-looped learning (Argyris, 1976). No matter how it is referred to, each end leads to a different form of transfer and outcomes, as “learning is uneven and imperfect . . . [and it] can be of different ‘orders’: shallow, tactical or instrumental . . . as opposed to deeper social or policy learning” (Stone, 2004, p. 549). In light of these distinctions, it can be argued that the poorer the quality of information, the less likely an accurate image of the original system or idea will emerge, and the less likely an accurate knowledge map will develop.
In addition to the degree of learning that can occur in the transfer process, there are likely to be different forms of learning. For lesson drawing (and much of the transfer literature) policymakers engage in rational learning. They turn to foreign ideas and policies in order to solve an existing problem by drawing on (in an unbiased, educated fashion) the information needed to develop a similar solution in their own system. Even scholars who relax the model to “bounded rationality” assume that the process is undertaken in a voluntarily way and that information is only sought on how to address a specific problem. Unfortunately, while there is a lot written on learning and transfer from the rational position, as Meseguer (2005) states, “[L]earning is hardly tested; and . . . the few attempts that do exist . . . suggest that there is little support for the hypothesis that learning proceeds in a rational fashion” (p. 76).
Linking Concepts: Learning and Transfer
Given the above, it would appear that the transfer literature could benefit from a more explicit understanding of learning. One of the first to see this was Heclo (1974), who attempted to link learning into the international movement of policies between Britain and Sweden. For Heclo the learning was a social process of “collective wondering what to do”: “Policymaking is a form of collective puzzlement on society’s behalf; it entails both deciding and knowing. . . . Much political interaction has constituted a process of social learning expressed through policy” (pp. 305–306). Applied to transfer, what policymakers learn will relate to the outcome of their collective puzzlement relating to information involving the activities of a foreign political system. In this, learning is not just random puzzlement on the part of policymakers, but is shaped by the individuals involved in the movement of information and the relationship between the individuals and institutions they are embedded in; and it is shaped by what already exists in the transferees’ home system. It is these paths that create flows that help explain what information moves from one system to another and how it is subsequently shaped and used in its new socio-political system. One of the consequences of Heclo’s social learning model when applied to the transfer process is that it becomes unlikely that learning will ever be fully observable or involve formulaic copying in which the original model is precisely replicated in the new location.
While Heclo was one of the first scholars to link the movement of policies to the learning process, he is not alone. Probably the most ambitious attempt was developed by Paul Sabatier (1987) and subsequently Sabatier and Jenkins-Smith (1993, 1999). For this, Sabatier developed the advocacy coalition-view policymaking, which sees policy as something that develops over at least a 10-year period of time. Policies develop though a learning process that occurs in coalitions and the sub-coalitions associated with it. Learning is possible because coalitional actors engage in a large range of interactions across multiple levels of governance. This allows actors operating inside and outside traditional governing institutions to share information and develop a policy or policy area over time and across space (Sabatier & Jenkins-Smith, 1999).
The core insight for the transfer process is that learning is constrained. Or as Sabatier and Jenkins-Smith argue, a coalition’s ability to learn is constrained by a set of “deep core” beliefs. These beliefs lead information to be filtered so that it is reinterpreted according to the coalition partners’ shared views of reality. As a result, learning, even when applied to “policy cores” and “secondary matters” (progressively more open to change) is an inherently political process. As such, one of the difficulties with studying transfer is that much of the observed change will be of an evolutionary nature, where the location and timing of transfer and learning will be difficult to capture or measure.
Another concept of learning related to transfer is Peter Hall’s concept of “social learning.” For Hall (1988), learning is a “deliberate attempt to adjust the goals or technique of policy in the light of the consequences of past policy and new information so as to better attain the ultimate objects of governance [emphasis added]” (p. 6). Within this, learning can be expressed through three degrees of change. First order change is seen in routine or incremental change, such as when the procedures governing the application processes associated with the receipt of welfare are slightly altered. While this might be involved in some of the more basic transfers, it is unlikely to involve complex learning and is rather more a “monkey-see-monkey-do” process. Or as Dobbin, Simmons, and Garrett (2007) argue, first order change is likely to be “based on fads, revered exemplars, or abstract theories, rather than solid evidence” (p. 451).
Unlike first order change, second order change involves “more strategic thinking” and is associated with changes in policy instruments and plans. When engaged in transfer, this is most likely to be the realm where it will be observed, as it will likely involve looking for and thinking about policies and best instruments. Third order change involves altering one’s deep core beliefs (paradigm shift). In undergoing third order change, policymakers change their worldview, underlying assumptions, beliefs, or goals. Not only is third order change outside the normal course of policy development and change, but it is unlikely to be a core element of individual instances of transfers (Hall, 1993, pp. 275–281). If third order change is to be tied to the transfer process, it is most likely to occur over long periods of time and involve cascading transfers that end in a paradigm shift (such as the spread of the neo-liberal economic and social policies since the mid-1980s).
When linking Hall’s model to transfer and learning it is important to remember two points. First, just as with advocacy coalitions, the core of the model is about change in the behaviors and beliefs of “elite” policymakers, not transfer or learning per se. Second, according to Hall, policy deliberation “takes place within a realm of discourse . . . [where] much of it is taken for granted and unamenable to scrutiny as a whole” (Hall, 1993, p. 279). Because deliberations are confined to discourse, when linked to transfer, learning will most likely be constrained and most closely linked to the translation processes that surround information as it moves and works its way through the policymaking and implementation processes.6
Where Do We Go From Here?
If the transfer literature is to move forward it will need more than a link to the learning literature; rather, it needs to make better links to and assimilation of the knowledge utilization and policymaking literatures. To do justice to these diverse sets of literatures would take an entire book. As such, let it suffice for this discussion to say that at its core knowledge utilization concerns the way in which knowledge develops, works its way into the thought processes of policymakers, political institutions, and policymaking processes. It also addresses how this new information is subsequently used by policymaking actors and institutions in the development of new policies or adaptation of old policies and programs (Hoppe, 2005; Love, 1985). The key is that knowledge utilization looks not only at how knowledge is created but also at how it is communicated and disseminated. This itself involves testing it against one’s own intuition and assumptions, and transforming the information into a form that is usable (Reich, 1981, p. 34). Just as with policy transfer, knowledge utilization is seen as a complex process involving a range of individuals, organizations, and societies and their political, socioeconomic, and psychological influences (Larsen, 1980, p. 424).
One of the insights that results from linking knowledge utilization to transfer is that the tempo involved in both the movement of information and its subsequent utilization in the policy process becomes a factor worth examining. For instance, due to the nature of knowledge acquisition and updating, it is likely that much of the knowledge gathered from a foreign political system will enter and subsequently be used by a policy system slowly. This is due to the tempo modulating what and how much is learned and how it can be shifted from one system into another. As the utilization literature has demonstrated, much of the knowledge acquired by agents of change is likely to be filtered and recombined on its way through the decision-making process. This is particularly true if the tempo is slow and cumbersome. As such, knowledge of how a foreign system operates is initially likely to lead to only small changes in a policymaker’s conceptual frame and in the importing system (possibly leading to third order change but only in the long run). When the tempo of transfer is quick, and knowledge is able to enter a system directly and in identifiable ways, what is used is likely to bring about change that is often later found to make the situation worse. This is because when knowledge is utilized in unrefined ways, it is not likely to be reshaped to fit the political-cultural-ideological needs of the new political system.
Based on the knowledge utilization literature it is also likely that when an agent uses knowledge gathered from a foreign system, the agent not only transforms it, but if the knowledge is not fully disseminated and understood, the agent might use it in fairly selective ways—for example, “as a political weapon legitimizing an already advocated political position” (Hoppe, 2005, p. 203). For policymaking this is problematic. When information is used as a weapon instead of in its original setting (or as the lenders intended), the bits of knowledge used (out of the totality of what was transferred) are likely to lose vital information and in selective ways, which is likely to lead to problems with any resultant policy (Boden & Zwi, 2005; Weiss, 1991). Even when agents attempt to be true to transferred knowledge, it is unlikely their lessons will be complete enough to truly include all the factors that led to success (or otherwise) in the originating system (or systems), particularly when they are not party to all of the material that was transferred. This is in part a result of information itself; nothing can be fully known, no matter how scientific. Rather, knowledge and information are packaged and moved and unpackaged as policymakers attempt to understand what is being transmitted in light of their own cultural and structural needs.
While it is clear that an interaction between knowledge utilization and the transfer literatures would benefit both, it must also be realized that there are a range of issues involved in attempting to adapt them. For instance, there is a link between the knowledge utilization literature and that relating to evidence-based policymaking (Bogenschneider & Corbett, 2010; Greenhalgh & Russell, 2009; Ham, Hunter, & Robinson, 1995; Marston & Watts, 2003; Sanderson, 2002). However, when applied to transfer, one must begin to question what counts as evidence, as what works in one setting will often rely on a range of factors beyond the directly observable. So if evidence of “success” in one system is used as evidence in another, it might be begging for failure as an outcome, especially when that success is due to a number of factors external to the policy being used as evidence. An example of this can be seen in much of the discussion relating to the Wisconsin workfare miracle. The introduction of the workfare program appeared to drive down the benefit claimant rolls during the late 1990s and was used as evidence to help shape the subsequent federal welfare reforms of the 1996 Personal Responsibility and Work Opportunity Reconciliation Act (PRWORA). However, a much more mixed picture emerged once the economy started to decline. Many now discuss the Wisconsin and PROWRA workfare reforms as more of a noose than miracle.
In a similar way both transfer and knowledge utilization literatures suffer from a number of issues that will need to be addressed if transfer is to best use the insights of knowledge utilization. For instance, neither literatures have properly addressed what happens when agents misuse or discontinue to use knowledge. In fact, issues of misuse are particularly difficult to address in the transfer literature, as knowledge of how things are done in a foreign system are clearly amenable to manipulation and misunderstandings, particularly where tacit knowledge is involved. However, as long as those interested in applying the insights of knowledge utilization to transfer are aware of these issues, as will be illustrated below, the interaction of the two will greatly enhance the utility of the transfer concept.
Transfer, Knowledge, and the Policy Process
The difficulty in examining learning from foreign systems and seeing if and how appropriately policymakers utilized any knowledge should not be seen as a reason for jettisoning the idea of learning and transfer. Rather, by focusing the lens of knowledge utilization on the transfer process and directing both at the policymaking and implementation processes, it is likely that the study of policy transfer will become even more useful for scholars and policymakers alike. By using the knowledge utilization framework in the analysis of policy transfer, the process can be seen as occurring over time and in a series of stages, which culminate (or not) in a recognizable policy action. Once this is incorporated into transfer studies, the view of transfer as being little more than a process of actor in A looking to B and taking C to solve problem X must be restructured.
While the focus of much of the knowledge updating literature has been on long-term change, it must be acknowledged that when agents engage in the transfer of information knowledge, updating is not confined to long-term change. Rather, it can and does lead to immediate change in how policies are used and in the way issues are understood. As such, knowledge can make an immediate impact, particularly when used as an instrument in battles to alter existing policy (Hertin, Turnpenny, Jordan, Nilsson, Russel, & Nykvist, 2007; Radaelli, 2009). The key here is that while transfer can help lead to instrumental change, knowledge utilization theory illustrates that this is not necessarily a straightforward process. In the first instance, knowledge that arises out of transferred information may sit within a policymaker’s conceptual knowledge map and be impossible to trace back to its origin. There will also be instances where an agent’s knowledge base is the result of the convergence of a range of transferred ideas combined into a single usable model. Similarly, knowledge may be held until a window opens that allows its use in the policy system, its origins being lost while it is held in a policy stream or after being coupled with other ideas and models. Of course one must ask if there is anything different about this form of knowledge use from a similar situation involving indigenous knowledge, or at what point do we stop calling something transfer and begin referring to it as knowledge utilization?
All lessons are transformed as they go through the policymaking and implementation processes. As such, transferred data is little more than one of many different pieces of data that combine during the policy cycle. It is this combination of data that help policymakers update their knowledge as transferred data encounters other policymakers and other types of information exogenous and indigenous to the system. At any moment in the policy cycle an individual policy will be in a state of flux and modification. As such, any imported idea or model is constantly confronted by and mixing with other ideas and models, some indigenous, and others transferred.
Attaching a knowledge updating view to this development pattern suggests that to understand transfer, scholars must look beyond where policymaker A sees a policy in system B and then uses it in an unaltered form to create a similar policy in system A. Rather, it is far more likely that due to the complexity of the policy process, policymakers in system A are likely to see a range of policies in systems B, C, and D and that these (or part of these) policies are combined with E, F, and G to create a “new” policy Z. And as Z works its way through the policymaking process, it will be further altered and modified as new ideas (some transferred, some indigenous) mix with it. When the former occurs, it is far more likely to be linked to systems that allow for a great deal of unitary government control, involve a form of technocratic learning, and are used to initiate very small alterations, or in some symbolic fashion.
When knowledge updating occurs as a result of transferred ideas, policies, and information, it is likely to occur over a series of stages rather than a single instance of all-encompassing updating. At a minimum, as a policy works its way through the system and develops into its final form, the types of knowledge (and or lessons) needed for it to progress will change as will the actors and institutions involved in the policy’s development. For instance, when an idea first transfers, the knowledge updating process may involve little more than the function of enlightening by helping policymakers focus on a situation in their home system that is similar to a problem occurring elsewhere. As a result of this awareness, information (even the same that led to enlightenment) might be used symbolically or as a way to frame a situation as a problem in their system. This can then lead to the same (or new) information being combined with political goals to develop a strategic weapon in a political battle over the importance and definition of the newly discovered problem. Jumping forward, the information used to finalize a policy solution is far more likely to be a combination of a number of different knowledge bases that have built up over the policy process and are utilized in a working manner. This is true because as a policy develops, new actors and institutions come to the table, bringing in different collections of knowledge, interests, motivations, and goals (Dobbin, Simmons, & Garrett, 2007; Hoppe, 2009; Meseguer, 2005; Radaelli, 2009). All told, if something approaching second and third order change is to emerge from the transfer process, it will likely result from the culmination of a range of learning experiences and processes involving hard and soft lessons, not any single instance of policy movement or grand learning experience.
Where and when an agent becomes involved in the transfer and policy process is also important for understanding what is transferred and how this information is used. For instance, when an agent becomes involved in the development, passage, or implementation of a policy can say a lot about what motivation the agent has for using a lesson and the type of knowledge the agent will offer (and the strategies he or she will have to employ in the use of this knowledge). In fact, outside the instance where a policy is the result of copying and mimicking-back (without any knowledge updating), a great deal of information is likely to be gathered. Unfortunately, due to the nature of the policy process and the institutions involved, a great deal of this information will be “lost” or “held” until it is no longer relevant. This can occur for a number of reasons. For instance, many examples of transfer and knowledge underuse are due to a misfit between an existing indigenous situation and the situation in the originating system. This is true despite the fact that transferred knowledge can often be used in more than one situation or the situations are similar but not recognized as such. Knowledge of a foreign system can be lost when an agent or institution with the information is not placed (or moves) in the policymaking process where the information can be accessed. An agent of transfer’s institutional role can impact what knowledge the agent has access to and what he or she can do with this. By way of illustration, information held by a low level bureaucrat who is not in a position to forward it to those involved in policy development or implementation higher up in the institution might find it disappearing. However, the same information might find its way into the policy process and be used in the development of a policy if taken up and forwarded by a policy entrepreneur (or policy champion). In a similar way, foreign ideas being held in limbo may emerge if a situation changes or a core actor who had been blocking the use of the information moves (or the one with the information moves to a more favorable position or institution).
Not only does transferred knowledge interact with the policymaking and implementation processes as a result of actors but it is also shaped by the institutional settings it finds itself embedded in (and the level of governance at which it operates). For example, it is often the case that institutional constraints interfere with local actors’ desire and ability to introduce data on foreign entities into the policy process. This can involve anything from institutional tacit knowledge constraints (such as when English administrators argue that German environmental solutions can’t work here because our system is too different), to budget constraints prohibiting actors from looking to distant systems for ideas, and even having a technician in charge of urban planning who “wanted to transfer the green roof model but was blocked by his political superior” (interview conducted, August 15, 2013). Looking at the same issue from the opposite end of the governance structure, an actor sitting in a similar institutional setting at the international level will often have to rely on faith that the receiving system will understand the correct lessons, have the technocratic ability/skills needed to act upon the information, and have the political will to carry out any required alterations to the existing policy mix that exists. Or as Sharma illustrates: “Decentralization is sometimes designed merely to receive loans from international agencies. The design of decentralization in such cases cannot be expected to aim to bring about long-term systemic reforms” (2009, p. 51).
All told, transferred information can be used by a range of actors, operating on different levels, holding different degrees of power, and having different institutional and structural capacities. This leads to a situation where the same information may lead to a range of different outcomes as a result of different levels and types of knowledge emerging. This is particularly true when information emerges from outside a political system or situation. Thus whether knowledge is used for instrumental, conceptual, or even organizational purposes will depend on a number of factors often overlooked by the existing literature.
It is clear that the literatures surrounding the movement of ideas, policies, and lessons has added to our understanding of the policy process. These literatures have also aided our understanding of the processes driving the globalization of policy and governance. However, absent from the literatures is a discussion of what is learning and how this interacts with the transfer process (from the perspective of transmitters and receivers). By linking transfer to learning and knowledge updating it will be considerably easier to move beyond simple statements that policy x or idea y was transferred from system a to system b. While this might be a visible output, it doesn’t necessarily equate with what was learned. Rather while any one policy may appear as an output of the policy process, the learning might have involved a study of the strategies and techniques used to pass the policy in the home system. Or it might have involved learning about the best ways to implement the policy once passed. A better understanding of learning and knowledge updating will also help overcome issues associated with spurious diffusion/Galton’s problem that few transfer studies (particularly large-n diffusion studies) address.
By considering what is learned (and by whom), it should also be easier to explain why it often appears that “bad” or inappropriate models spread quickly while “good” or more suitable models never transfer. Stated slightly differently: “Confusion tends to arise, especially from the inference that evidence of the diffusion of a program is equivalent to diffusion of knowledge about that program” (Bennett, 1991, p. 32). Rather, to understand the linkages between learning and transfer, one must “distinguish clearly between knowledge of a foreign program, utilization of that knowledge, and the adoption of the same program [emphasis in original]” (Bennett, 1991, p. 32).
Second, the transfer literature would be greatly enhanced if it began to examine the factors motivating pushers and borrowers to engage in transfer, learning, and knowledge utilization. As, Unalan notes: “When studying policy transfer, one of the key factors that we need to understand is what drives actors to engage in the process, as these reasons can influence the whole process, including the outcomes, and the application of knowledge, beyond the initial selection of candidate ‘lessons’” (2009, p. 439; see also Campbell, 2002).
While a considerable amount of literature has been written on the role of entrepreneurs and policy advocates, not nearly enough has been done to link their transfer activities to the overall policymaking process and how this interacts with the knowledge updating activities that emerge. More importantly very little has been done to examine how those opposing the forced importation of a lesson use the policy process to advance their own agendas or transform an undesirable into something more suited to the indigenous environment. Or, how those opposed to a transferred policy can alter its effects once it enters the implementation process. Finally, the role of national and international policy cycles in the spread of knowledge, and thus, when and why international ideas become common knowledge and subsequently linked into national policymaking cycles, needs considerably more attention by those interested in transfer.
Third, a better understanding of the role the political plays in the transfer, knowledge updating, and implementation processes needs to emerge. To date, the transfer literature has done little to understand or integrate how the politics surrounding the transfer of a policy or idea shape the overall use of data. In fact, few transfer studies have spent time analyzing how the general political climate of a transfer situation influences the transfer and knowledge utilization processes. By doing this it should be possible to begin understanding the role of games. For instance, there are clearly situations where international agents actively work at bypassing national level actors and policy processes in order to transfer data directly to the local. Similarly there are local agents who use lessons from (and actors floating around at) the international level in order to block national actions. More to the point, the investigation of the political in the transfer process necessitates an integration of the ways actors promoting (or resisting) transfer operate in the confines imposed by the institutional, cultural, ideological, and socio-political systems of the receiving political system. Without considering these types of influences on motivation, how actors perceive a situation, or what they see as being a valid model or idea, what might at first appear to be an illogical decision or policy may turn out to be perfectly logical in light of the political situation surrounding all transfer and policymaking situations.
Fourth, studies must begin to take into account how information and knowledge is gained during the transfer processes and subsequently altered and reformed as it works its way through the policymaking and implementation processes. This should help shift the focus from the current “have-policy-will-travel” model to one that examines how a range of competing transferred models develop and work their way into and though the policy process at the same time, often competing with each other and being combined into new models. As Manning argues, “[W]e might surmise that policies will only fit depending on their place in policy sequences, dependent paths and slow processes. . . . [A] transferred policy might have quite different consequences depending on how, when and where it is adopted into a particular setting” (2006, pp. 164–165).
Finally, with some exceptions within the translation literature, the role of social constructivism and discourse has not been integrated into the transfer literature and or examined for how this interacts with knowledge perceptions and updating. Noticeably absent is work examining the way some “ideas consist of taken-for-granted assumptions about values, attitudes, identities, and other ‘collectively shared’ expectations. . . . [T]hese . . lie in the background . . but constrain action by limiting the range of alternatives that elites are likely to perceive as acceptable and legitimate” (Campbell, 2002, p. 23). As a result “what gets transferred may well differ from what has been learned,” and what is learned may not be what was originally transmitted (Dwyer & Ellison, 2009, p. 394). This is because the “same communication will be interpreted and received differently by different individuals and organizations, the differences reflecting their different contexts, sensitivities and perspective” (Chapman, 2002, pp. 29–30). This is doubly true when one considers that much of the information relating to foreign models appears in snippets that are then filtered by agent and the institutional setting the agent and lesson operate in. All told, what one agent learns or thinks he or she has learned might be quite different from what the agent he or she is sitting next to has learned, as well as from what those who provided the lesson have learned. Because of this, the focus on agents and their roles and understandings of information should take on a more central role in the transfer studies than it currently does.
Overall, unlike the presentation of policy transfer in most studies, those engaged in the process face a range of obstacles that are likely to alter the way knowledge emerges from the information that was initially moved and then how this is subsequently used in the policy process. While some exceptions exist, such as when an actor is placed in a position to feed information directly into practice (such as when a politician uses rhetoric he or she heard being used effectively in a foreign system) most instances of transfer involve a rough ride. In this process much of the initial information that enters a system will be taken away, filtered, and mixed before used. This filtering and mixing process will continue to occur as the policy is moved though the political system, encountering and entering different organizations, and being adopted and adapted by different actors. Once a foreign idea or policy has entered the policy process it can be examined within a single organization or a range of organizations, simultaneously or sequentially. As a result, while a great deal has emerged from the existing literature, with a degree of learning and adaptation the transfer concept will be able to provide years of analytic and conceptual study.
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(1.) It is worth noting that convergence and divergence are not exclusive to EU studies, and that when they are applied to cross-national studies, convergence is often discussed as a fairly mechanistic process. Greatly simplifying the argument, much of the convergence literature tends to attribute the cause of policy convergence to some form of determinism. Often this is itself implicitly based on levels of industrialization and shifts towards post-industrialization (Collier & Messick, 1975; Ross & Homer, 1977).
(2.) Also known as spurious diffusion and is related to what is more commonly known as Galton’s Problem.
(3.) Transfer studies cover topics including: social policy (Dolowitz et al., 2000); crime control (Jones & Newburn, 2007); public welfare (Pierson, 2003); education (Bache & Taylor, 2003); development assistance (Stone, 2004); urban planning (de Jong & Edelenbos, 2007; Dolowitz & Medearis, 2009); utilities regulation (Bulmer et al., 2007); and environmental policy (Betsill & Bulkeley, 2004; Holzinger et al., 2008).
(5.) While not the primary focus of this article, the notion of policy evaluation is closely linked to learning and knowledge updating. More importantly, recent studies have begun to link evaluation processes and outcomes to concepts of policy learning and knowledge updating (see Borras & Hojlund, 2015; Sanderson, 2002).