Part 1. An introduction

If you consider yourself a public policy scholar, one of your first exposures to the field might have been the policy cycle. Easy to remember and intuitively appealing, your instructor might have used the policy cycle to structure your first policy course syllabus. You might recall that your first public policy textbook was organized by the policy cycle. You might have simplified the field by organizing readings and theories into the different stages of the policy cycle. Your instructor might have defined the study of policy processes by the policy cycle. Equally likely, you might recall a historical link between the policy cycle and a scholar named Harold D. Lasswell. For Lasswell, you might have been told or read how he formed a new field of study called the “policy sciences,” which you might remember is what your first policy course was about and how he was one of the primary sources for the policy cycle. For many of us, this is a shared experience or myth about the history of policy studies.

In all myths, you will find some truths. Harold D. Lasswell was the intellectual visionary for the policy sciences. There are connections between the policy sciences to the policy cycle and then onto the field of policy studies as we see it today. But myths also abridge parts of history by glossing over the nuances and, in doing so, sometimes bury diamonds in the rough.

In this commentary, we dig up one of these diamonds in Lasswell’s decision functions (Lasswell, 1956) and build on efforts by Auer (2017) and Dunn (2019) to correct misinterpretations. Lasswell’s decision functions contributed to what people now call the policy cycle, and some might view them the same, but they are not. While we discuss the policy cycle, our goal is to polish and present Lasswell’s decision functions as a mostly forgotten approach that deserves a more prominent space in the stable of tools and perspectives in modern policy theories and policy process research.

This task forms part of a wider project to envisage “the New Policy Sciences” as a return to a close interaction between policy research and practice. In our specific examination of Lasswell’s functions, we also highlight a more general focus on how policy process theories and policy analysis intersect (Cairney & Weible, 2017; Cairney, 2021a; Weible & Cairney, 2018).

Part 2. The old policy sciences and the new policy sciences

One of the most influential political scientists in the 20th Century was Harold D. Lasswell. In the study of public policy, scholars regularly recognize Lasswell as one of the creators of the policy sciences. As a movement, the policy sciences aimed to create a new applied and interdisciplinary discipline to advance democracy and help realize a greater human dignity for all.

Briefly, Lasswell outfitted the policy sciences with three analytical pillars with the ambition of putting knowledge to action (Lasswell, 1971; Lasswell & Kaplan, 1950; Lasswell & Lerner, 1951). The first was contextualization, which equates to modern-day policy process research by describing or analyzing the context of a decision situation. The second was problem-orientation, which equates to modern-day policy analysis or evaluation by studying priorities and assessing choices. The third was multi-method, which elevates the need for interdisciplinarity to conduct science crisscrossing and incorporating academic silos of various disciplines and fields. A good policy scientist would integrate these three analytical pillars by diagnosing a context and informing decisions by policy actors using whatever methods are needed —all of which would be in service of democracy and greater human dignity.

In condensing Lasswell’s policy sciences to a single paragraph, we miss the beauty in its infrastructure.Footnote 1 We also argue that, for the most part, Lasswell’s “old policy sciences” have been lost or forgotten among policy scholars. Hence, Cairney and Weible (2017) call for a “New Policy Sciences.” Indeed, calling today’s field the “policy sciences” would misrepresent what the field is today and, in a way, be an insult to Lasswell by assuming we still walk in his envisioned path. Lasswell weaved in his policy sciences strong normative ties to democracy and human dignity. Indeed, we interpret the “Future of Policy Sciences” not as the future of the field but as a question of what to do with Lasswell and the old policy sciences in today’s modern policy studies, given that Lasswell’s goals are as salient as ever.

Cairney and Weible (2017) argued that we need to modernize Lasswell’s old policy sciences to contemporary times by (1) embracing the multiple approaches (e.g., theories) in the field; (2) incorporating better human agency, the science underlying human choice, and take a broader perspective of choices in the policy process; and (3) embracing the applied and basic nature of policy studies, thereby bringing together aspects of policy analysis/evaluation and policy process research. In laying out his reimagined vision of the new policy sciences, we embrace Lasswell’s original vision of realizing greater human dignity for all, especially toward greater political equality in our governing systems. Furthermore, in today’s language, we would describe the New Policy Sciences as consisting of policy process research (mainstream, interpretive, and others) and policy analysis or evaluation. This accepts inherent tensions within and across our communities, including supporting the unity of science and practice and science for science’s sake (Dunn, 2019; Berglund et al., 2022).

In this commentary, our efforts focus on revisiting and securing a place for Lasswell’s decision functions in contemporary policy process research.

Part 3. Lasswell’s decision functions

Lasswell’s focus on contextualization included several discussions of decision functions (also called decision processes, Lasswell, 1970). You will find descriptions of the decision functions by Lasswell in several sources, including Lasswell and Kaplan (1950), McDougal (1952), and notably Lasswell (1956; see also Lasswell (1971) and Clark (2002)). Possibly the best contemporary treatment of the decision functions is Dunn (2019), whose work we rely heavily on for the arguments herein.

The decision functions help guide research on the arenas of power and the choices in a government or policy area. As we hope to convey in this commentary, studying these decision functions, by themselves or in conjunction with other theories and approaches, can form and advance localized and generalized knowledge toward better democratic outcomes and greater human dignity.

The decision functions included the following seven classifications described in Lasswell (1956, 1971) and Dunn (2019).

  1. 1.

    Intelligence relates to information, planning, and the need for all governments to possess information to make good decisions.

  2. 2.

    Recommending relates to pressuring the government to make decisions in a particular way. This function is overtly political by emphasizing efforts to influence policy processes outside or in between elections. It has also been called “promotion” (Lasswell, 1971).

  3. 3.

    Prescribing relates to the formal enactment of a public policy. We would also call this policy adoption or change in today’s parlance.

  4. 4.

    Invoking relates to establishing the legal, management, and administrative apparatuses and resources, including the specification of assigning enforcement responsibilities.

  5. 5.

    Applying relates to the implementation of the public policy.

  6. 6.

    Appraisal relates to the evaluation of public policies and their outcomes.

  7. 7.

    Termination relates to stopping or ending a public policy.

In establishing the decision functions, we lay out several assumptions and arguments concerning their use. We use more contemporary vernacular (connected to the modern policy process literature) and interpretations to communicate them. We construct these assumptions to establish and foreshadow the usefulness of the decision functions in today’s policy studies. The assumptions also overlap and operate interdependently; we partition them this way to emphasize what we consider the essentials of the decision functions.Footnote 2

Assumption 1: The decision functions operate with teleological reasoning with base values driving their creation and use toward achieving value-desired ends. The underlying logic of the decision functions is a teleological relationship, with individuals motivated by base values to shape and influence the decision functions toward securing resources and achieving the value-desired end (scope values) (Lasswell, 1971; Dunn, 2019). In other words, individuals are motivated by values (base values) to achieve their values (scope values) through the decision functions, which become instrumental. The categorization of base and scope values includes power, rectitude, respect, wealth, wellbeing, enlightenment, skill, and affection (Lasswell, 1971). The spirit underlying this assumption is the construction and use of the decision functions by individuals.

Assumption 2: All governments have multiple governmental and non-governmental organizations that perform, to various extents, the decision functions for supporting their politics and public services. From a foundational perspective, governments carry out certain functional activities to achieve value-based goals over time. Governments perform these functions differently and with different effects. Indeed, the capacity and effectiveness of these functions vary. They can become negligible and malfunction. Moreover, multiple organizational units can perform any one of the decision functions. For example, prescribing (enacting) public policy can occur in administrative agencies, legislatures, judiciaries, among many others. Outside formalized centers of authority, non-government entities can also perform the decision functions, such as through public–private partnerships. There is no assumption that the decision functions occur in a sequence, as assumed in the policy cycle. Instead, the decision functions align more with arguments related to polycentricity; see later discussion.

Assumption 3. The decision functions apply at different levels of government and policy-issue specifications. The decision functions work within systems of government that operate semi-independently toward value-oriented outcomes pursued by individuals involved. Thus, the decision functions can be used to compare different countries as a whole without much specific reference to a particular policy area or, more narrowly, to compare subsets of that political system (i.e., a policy subsystem). The decision functions can also occur at any level of government (e.g., as might be found in a federally structured governing system).

Assumption 4. The decision functions fluctuate in their capacity and impact with shifts in societal base values. The decision functions are both the artifacts and arenas of politics; they do not exist independently from individuals’ base values. Hence, the decision functions will wax and wane over time in conjunction with shifting societal base values, particularly those in power.

Assumption 5. The decision functions occur in a context. They emerge, exist, and evolve in a broader policymaking context or environment. They do not happen in a vacuum devoid of a setting, shaped by (but not exclusive to) cultural, socio-economic, physical, and institutional parameters. Of course, this also includes people and their values.

Assumption 6. The decision functions consist of sub-functions. Decision functions are constructs. We create them politically to achieve our base values, and we identify them as researchers to help make sense of, learn about, and contribute to our governing systems. Given the complexity of our governing systems, decision functions themselves include sub-functional routines to help achieve the role. The degree of sub-functional specialization will likely reflect the complexity and understanding of the problem, the value-orientations of the people involved, and the capacity to respond. For example, different sub-functions might exist in implementing a public policy for regulating behavior and delivering public services within the same policy subsystem.Footnote 3

The decision functions serve researchers and practitioners in conducting single case studies and comparative analyses. McDougal (1952) and Lasswell (1956) describe the challenge of doing comparative law and public policy if we only rely on traditional models of government, such as the separation of the powers of legislative, executive, and judicial. Instead, we need a more comprehensive lens for guiding the study of what governments do. Thus, the decision functions can be used cross-nationally and longitudinally to aid researchers in adding to the streams of knowledge about policy and politics and practitioners trying to make sense of their situation and act accordingly.

In addition, the decision functions have scope and purpose, drivers of human behavior, clearly defined conceptual categories that are generally related and can support theoretical inquiry—that is, the decision functions operate as a framework (see Ostrom, 2005). Yet, the decision functions also lack several things, such as theoretical arguments to explain how they relate to each other and methodology or methods in applying them.Footnote 4 The decision functions were also created before the emergence of contemporary policy theories and remain removed from their knowledge. Perhaps more important, and as we elaborate on below, the decision functions are portable, which means we can upload them into other contemporary theoretical frameworks to help guide and interpret research on the policy process and contribute to developing better policy process theories.

Figure 1 below provides a visual depiction and a more contemporary interpretation of the decision functions. In Fig. 1, we place the decision functions in a policy subsystem. The decision functions are not portrayed as a cycle but rather a collection of interdependent activities contributing to the policy subsystem. The decision functions contribute to the outcomes, and this feeds into the broader political environment and can feedback into the policy subsystem. The inputs and outcomes represent bucket concepts, including the base values of individuals and groups as inputs and desired scope values as outcomes.

Fig. 1
figure 1

A visual depiction of the decision functions

Full size image

An interesting feature of the decision functions is that we can imagine the relative size of each slice of the decision functions as taking up relatively more or less space to another and changing over time. For example, there might not be much appraisal or termination in some policy subsystems, thereby shrinking the size of these slices. Hence, we should interpret Fig. 1 as one image among many of the changing decision functions for this policy subsystem or others. We can also imagine a similar image of a non-policy-specific governing system.

Part 4. The decision functions and realizing human dignity

Suppose we are to bring Lasswell’s decision functions back to the future. In that case, we also do not want to divorce them from their normative underpinnings related to realizing greater human dignity through the policy process. Indeed, these normative underpinnings provide the foundational rationale for the importance of Lasswell’s decision functions.

Human dignity refers to members of society realizing their optimal level of valued-based outcomes (e.g., equity, respect, rectitude, affection, wealth, wellbeing, respect, enlightenment, and power) (Lasswell, 1971; Mattson & Clark, 2011). These values, to some extent, are created and negotiated by society, which requires some degree of political equality among society’s members in influencing societal decisions. Given that policy decisions are often understood as a societal reflection of values and priorities, the policy process is an instrumental arena that can collectively address human dignity.

The decision functions then represent arenas of power in policy processes; they are situations where decisions shape the abundance and distribution of societal values. As politics shape decisions and the subsequent winners and losers, the decision functions provide a lens for assessing these results. Moreover, because this lens embraces complexity rather than glossing it over, it can be used to explicitly evaluate how a political system prioritizes or subverts human dignity.

Too often, our contemporary lens of social equity falls solely on the single government agency as found in the representative bureaucracy literature (Bishu & Kennedy, 2020). Similarly, our focus on political equality falls too much on electoral politics or shaping agendas (Dahl, 1998). These are oversimplifications of how the intertwined issues of social equity and political equality exist in political systems. Oversimplifying the myriad ways the policy process influences social equity and political equality, or lack thereof, risks masking areas that contribute to their realization.

The decision functions point to power in any government, regardless of its formal structure -from federal to unitary or presidential to parliamentary. The decision functions can then support political and social justice assessments in the policy process.

Part 5. What happened to the decision functions?

With few exceptions (e.g., Clark, 2002; Steelman & Kunkel, 2004), we don’t see the decision functions applied in modern policy process research. What happened to the decision functions is a walk-through history or our interpretation of it. As described by Auer (2017) and Dunn (2019), the upshot is that Lasswell’s decision functions were either swept into the corner and forgotten by most scholars or morphed into the policy cycle.Footnote 5

Why did the decision functions seem to morph into stages of a cycle? One possible explanation is that Lasswell himself (1971), and key scholars inspired by his work, began to describe the decision functions as occurring in a sequence or as many phases in a collective process. The earliest example to connect the decision functions with the policy cycle is Jones (1970), who coined the “policy cycle” with inspiration and adaptation from Lasswell’s decision functions. Next, several other sources, including Lasswell’s student Garry Brewer (1974, p. 240), relabeled and updated the decision functions into “six basic phases through which a policy or program passes over time.” Then, Anderson’s (1975) public policy textbook, May and Wildavsky’s (1978) edited book, and Brewer and deLeon’s (1983) textbook organized around the policy cycle. As a result, Lasswell’s legacy continues to be mixed and blurred with the policy cycle (see deLeon, 1999), and many textbooks continue to portray the field within the conceptual box of the policy cycle (e.g., Hill & Varone, 2014; Howlett et al., 2009; Knill & Tosun, 2020). These (re)produce the myth of the decision functions by placing them in the narrowly constructed paradigm of the policy cycle.

One explanation for such developments is that the phenomenon of policy processes is so difficult to define. Reading the scholarship of the 1950s and 1960s, U.S. scholars struggled to develop a manageable definition of this area of study. Part of the morphing of the decision functions to the policy cycle relates to the analytical benefit of a singular, rational decision process (e.g., identifying problems, developing alternatives, choosing a solution, implementing it, evaluating it). Moore (1968), another Lasswell student, describes how the decision functions map or correspond with the sequence or phases of making decisions from a legal perspective. Hence, the decision functions, perceived as a sequence, can seem like a reasonable simplification of the procedural way an idea becomes a policy and is implemented (especially since it resembles so strongly the “five steps” of policy analysis: define a problem, generate solutions, use values to compare them, predict their effects, and make recommendations—Cairney, 2021a). It is a rationalist interpretation of policymaking, intuitively appealing as a life cycle of an idea and a helpful simplification of the complexity of actual policy processes. Most importantly, the decision functions offer far more than a sequence of decisions depicted in the policy cycle.

However, not all policy scientists equate the decision functions with the policy cycle. Notably, Clark (2002), Auer (2017), and Dunn (2019) are among those who maintain the original conceptualization of the decision functions as articulated by Lasswell (1956), including arguments against the decision functions occurring in a cycle or sequence.

We also need to be careful not to overplay the connection between the decision functions and the policy cycle. There were multiple inspirations, including Easton’s systems theory (1955) (see discussions in Sabatier & Jenkins-Smith, 1993; Lindblom and Woodhouse, 1993; Parson, 1995) and Simon’s decision-making model (Kingdon, 1984).

It is remarkable to think of the profound effect this—seemingly innocuous—clarification of Lasswell’s functions has on how we describe their legacy. When expressed as the ancestor of the policy cycle, the decision functions can be dismissed too readily as unrealistic and unhelpful to the contemporary study of policy processes. When described consistently with Lasswell’s original description or thought of more as functional activities rather than straightforward descriptions of a policy process, they sidestep many of the problems that emerged with the policy cycle and offer other benefits to policy process research.Footnote 6

In contrast, the decision functions provide an image of the policy process focused less on stages or a linear cycle but more on how and where governments operate. It also provides a lens that focuses less on a single policy as it transverses through a government from agendas to implementation, but rather how the system as a whole operates and could include one or more public policies. In a modern context, such a lens would lend itself to policy process research that helps unpack and address the complexities of wicked problems or the systemic inequities that undermine human dignity and democracy.

Part 6. How can the decision functions help contemporary policy process theories and research?

Distinct from the policy cycle, the decision functions offer several benefits to contemporary policy analysis and policy process research. The decision functions have always been a component of policy analysis research as practiced in the traditional policy sciences under the confluence of knowledge and action (e.g., Clark, 2002). As such, we avoid recapping this area of scholarship or extending it to the broader field of policy analysis (e.g., Weimer & Vining, 2017). Instead, we offer five fruitful areas of research that engage the decision functions with contemporary policy process theories (e.g., see Weible & Sabatier, 2018) with some connections to the broader policy process research community (e.g., see Cairney, 2021a). Of course, policy process research involves more than what we reference, but we consider this an excellent place to start articulating the benefits of the decision functions.

  1. 1.

    How do we understand the structure and activities of modern governing systems?

    Generally put, policy process research focuses on understanding public policy and the surrounding people and organizations, their political actions, events, and outcomes (Weible, 2018). It inevitably involves governments and how power is sought and wielded through formal and informal channels of influence, from policy change in legislatures to regulatory decision-making or dominant narratives in the public discourse through the news and social media. Thus, an ongoing pursuit is portraying and understanding the structure and interdependencies of government and relevant non-government entities related to policy processes.

    We have always known the policy process is complex. What has changed is our understanding of the complexity and a recognition of the challenges we face studying it. Contemporary theories have depicted the complexity of our governing systems in several ways. The Institutional Analysis and Development Framework and the Ecology of Games Theory, for example, examines governing systems through polycentricity, defined as structures of governance with multiple centers of authority overlapping in some manner (perhaps competitively or cooperatively, at least from a behavioral perspective) (Ostrom et al., 1961; Berardo & Lubell, 2019; Theil et al., 2019; Weible et al., 2020b). But, of course, all governance units are, to various extents, polycentric. The question is how to study polycentricity and build knowledge about it. We see similar arguments in research on multi-level governance (MLG), which describes the sharing of power vertically, between many levels of government, and horizontally, between many governmental, quasi-non-governmental, and non-governmental organizations (Cairney et al., 2019).

    A common thread woven throughout this scholarship is an attempt to understand the game board of politics, which establishes political opportunities, constraints, and targets. However, our knowledge of what constitutes the workings and dynamics of this game board remains largely unknown. The Ecology of Games Theory, for example, might provide a network map of the interdependencies of the decision-making venues for a particular policy issue in a locale (Berardo & Lubell, 2019). Yet, under this research tradition and others, the categorization and utility of these venues remain conceptually and theoretically ambiguous.

    The decision functions can provide one way to make sense of the polycentricity and MLG. The decision functions bring attention to the roles and activities of a governing system, where these lie, and how different government and non-government units have overlapping capacities to perform them. In other words, the decision functions provide a means to track and understand the complexity of governance to see how and where various functions and malfunctions occur. For example, we might identify venues that lean toward intelligence (supply of information), prescribing (authority to adopt public policies), or applying (implementation).Footnote 7 The result would better describe the nodes in a polycentric system and their ties. Incorporating the decision functions into the study of polycentricity opens new research doors for assessing the purpose of different decision-making units and portraying their overlap.

  2. 2.

    How do we understand the shifting of societal values and their effects?

    As described, the traditional policy sciences depicted people motivated by values to realize their values through the different decision functions in any governing system. Such an assumption prefigured many of today’s contemporary theories. The Advocacy Coalition Framework (ACF), for example, assumes that belief systems are the fundamental driver of political behavior and the design of public policy (Jenkins-Smith et al., 2018). Though dissimilar in its descriptions, other contemporary theories and frameworks share this underlying assumption (e.g., values are the underlying source of narratives in the Narrative Policy Framework, see Shanahan et al., 2018).

    Yet, contemporary theories and frameworks struggle in linking such value orientations to public policies and their effects. Current ACF scholarship, for example, primarily uses its model of beliefs to understand advocacy coalitions (e.g., see Weible et al., 2020a). Less common in using belief systems is linking them to the content of policy change and changes in the governing system.

    The decision functions offer a new way to think about belief systems and their effects. The eight base and scope values in the policy sciences can be uploaded into the ACF (and other frameworks and theories) as a means of organizing fundamental values (deep core) and policy-related beliefs (policy core). This would provide another way to compare and contrast the values and beliefs of the different coalitions. We can then explore how these values and beliefs motivate coalitions to shape and influence the decision functions to achieve their desired outcomes over time. For example, a minority coalition might attempt to impose criteria and constructions in the appraisal function (i.e., evaluation) of policies adopted by a dominant coalition. Likewise, a dominant coalition might seek to maintain control based on what issues are deserving for the recommend function (i.e., agenda setting).

  3. 3.

    How do we understand the impacts of public policies on politics and outcomes?

    Some of the most critical policy process insights relate to policy feedback, historical institutionalism, and policy drift (e.g., Mettler & SoRelle, 2018; Riccucci, 2018). These studies take long-term perspectives and argue that fundamental value orientations in public policies shape not just social constructions but also what governments emphasize or de-emphasize and the allocation of tangible and symbolic resources, including the role of citizens in the policy process (Moon & Cho, 2022).

    We can also extend these arguments by looking at long-term changes in public policy that can reinforce or undermine policy-related goals or normative criteria of political equity over time. For example, policy feedback literature often focuses on resource and interpretive dimensions of the downstream effects of public policy. Yet, we know the impacts of public policy must be undertaken by at least one of the decision functions, and the long-term societal outcomes filter back into the decision functions as well. Examples include changes in resources to civic and interest groups from policy changes that later shift in recommendations (i.e., agenda setting). Similarly, Jones and Baumgartner (2015) tracked changes in the information processing capabilities (i.e., intelligence functions) in the U.S. government over decades. We can, thus, continue these efforts by following shifts over time in other functions of government.

  4. 4.

    What are the patterns of stasis and change over time?

    The study of policy processes is about the study of stasis and change. We see the literature exploring explanations and descriptions of change. From an ideal perspective, we envision such change as adaptive to shifting signals in the environment, as found in adaptive management and learning (e.g., Gerlak et al., 2018). However, people cannot process all information, fully understand the environment where they operate or anticipate all the effects of their choices. Instead, policy theories identify the many ways in which policymakers address bounded rationality (for a summary, see Cairney, 2020 pp. 231–2).

    Bounded rationality of people also transfers into their organizations (Baumgartner & Jones, 2005) and, hence, into the decision functions of government. We, thus, would not expect the decision functions to operate as smooth interlocking machines. There will be friction in how these decision functions work at the organizational level, just as there is at the individual level. Whereas Jones and Baumgartner (2005) honed in on disproportionate information processes and their impacts on agenda setting and policy outputs (intelligence and proscribing functions), we can start understanding the effects of bounded rationality concerning other decision functions and explore the resulting implications. Such research would point to the inefficiencies in our governing systems wherein some decision functions are less adaptive or responsive than others, particularly to the influence of marginalized voices.

  5. 5.

    How do we realize a greater democracy and human dignity?

    One ongoing critique of policy theories is the general absence, though not uniform, of normativity in assessing their depicted processes and effects (e.g., Heikkila & Jones, 2022; Ingram et al., 2016). The bases for realizing human dignity rest with people having equal opportunities to influence government and having their values accounted for in the collective values produced through government and public policies. To date, however, efforts to understand and study political equality, as part of democracy, tends to emphasize elections, the correspondence between public opinion and policy decisions, and policy outcomes (e.g., Achen & Bartels, 2016; Clawson & Oxley, 2016; Gilens & Page, 2014; Schlozman et al., 2018). Moreover, the insights across these literatures tend to be scattered and disconnected, preventing holistic interpretations of any governing system.

    The decision functions offer a way to categorize and integrate the different arenas wherein governments represent people performing their various activities. In other words, and for example, a democracy should not just operate with representation just in implementation (equivalent to representative bureaucracy) or any other single functional area, but ideally across all of them. More likely, however, governments will be adhering to democratic principles in some functional areas over others. Thus, we can evaluate policy processes under many of our theories by anchoring assessments of the effects of policy choices (i.e., a policy change and design) and political behavior (e.g., from narratives to lobbying) across the decision functions (Heikkila & Jones, 2022; Siddiki & Cali, 2022). This is ultimately a ripe area of original empirical inquiry and foundational to the new policy sciences (Cairney & Weible, 2017). Overall, these opportunities with the decision functions show that this analytical lens can sync with other theoretical approaches with the possibility of adding new knowledge about the policy process. We have a typology based on some generic assumptions consistent with many contemporary theories and frameworks and, arguably, help move the field forward.

Part 7. Conclusion

“Rough diamonds may sometimes be mistaken for worthless pebbles.” Sir Thomas Browne.

The study of public policy has numerous approaches and ideas that have been swept into the dustbin or forgotten over time. Some have been subsumed by other approaches or purposely disregarded for being overly narrow or simply mistaken. In this commentary, we reexamined and polished what we consider a diamond in the rough in Lasswell’s decision functions.

The decision functions have been buried and forgotten partly by the mass of writing in Lasswell’s tome and the hegemonic rise of the policy cycle. While the decision functions have been forgotten and mistaken for the policy cycle, all is not lost. We find that within the decision functions is a typology of government action that can contribute to original questions and research opportunities in contemporary policy process theories and research and serve as a foundation for new ways of thinking.

This prospect of shining the decision functions and bringing them into the tool kit and lexicon of policy studies, particularly policy theories and policy process research, seems more appealing than using them as part of a historical narrative that ends with a rejection of the policy cycle as descriptively inaccurate and misleading in practice. We ask that new and experienced scholars give the decision functions a chance to help guide and interpret their policy research.

In this commentary, we build on the conversations and recent efforts to resurrect the decision functions led by Dunn (2019) and Auer (2017) to revisit the decision functions and offer ideas for using them in conjunction with policy process theories. By linking the decision functions to theories, our intent is not to downplay the importance of the decision functions in traditional policy science scholarship that unifies it with a problem orientation in bringing knowledge to action in the policy process (Lasswell, 1971). However, we also do not foresee using the decision functions solely for science’s sake in the future. Whether theories contribute to practice depends more on how they are applied than what comprises them (Berglund et al., 2022; see discussion in Heikkila & Jones, 2022). More importantly, the new policy sciences should embrace pluralistically the diversity of perspectives and applications that avoids artificially separating our streams of knowledge and enhance communication among our communities while supporting the scholarship therein (Berglund et al., 2022; Cairney & Weible, 2017).