Accounting for Socialization: Quantitative Priming,Language,and Tools in a Masters of Public Affairs Program

Abstract

Quantitative accountability has become a widespread rationale for how organizations ought to operate in the twenty-first century. However, we know little about how the people who craft and implement such policies learn this rationale. How do future policy professionals learn quantitative accountability? How do the people responsible for organizational accountability learn it, and learn to do it? To answer these questions, we draw from a two-year ethnography of a cohort of students at a highly regarded Masters of Public Affairs (MPA) program. We find that, instead of directly debating forms of organizational control such as accountability, students learn accountability indirectly through an emphasis on the quantitative techniques that facilitate accountability. MPA students are primed into a quantitative view of their future careers, acquire quantitative “language” and “tools,” and are socialized into accountability in ways that are both tacit and tangible, even as the appropriateness of accountability itself is largely unquestioned.

Introduction

Over the last forty years, organizations across the world have faced a rising tide of “accountability.” Influenced by economic notions of market efficiency (Barberis 1998, Berman 2022; Chubb and Moe 1990; Hood 1995), this tide washes beyond private firms to encompass public and nonprofit organizations. This tide crept slowly at first but gained ground in the 1990s and the new millennium (Shore and Wright 2015a; Strathern 2000; Power 1994). Today, most organizations (1) are pressed to be accountable for their outcomes by being performance or results oriented, (2) face rewards and punishments for those results, and (3) must deal with quantitative measures of performance related to some standard (Stecher et al. 2010). Quantification is central to accountability (Espeland and Vannebo 2007), as the model is based on a trust in numbers (Mennicken and Espeland 2019; Porter 1995; Rottenburg et al. 2015) and techniques that make qualitatively different items commensurate so they can be standardized, compared, and ranked (Espeland and Stevens 1998, 2008).

As quantitative accountability has become a widespread rationale for how organizations ought to operate in the twenty-first century, scholars have examined the impacts of accountability for K-12 schools (Abelmann and Elmore 1999; Ingersoll 2003; Mehta 2013), law schools (Espeland and Sauder 2013), universities (Chun and Sauder 2022; Shore 2008; Shore and Wright 1999), hospitals (Scott et al. 2000; Timmermans and Berg 2010), charities (Hwang and Powell 2009), mission work (Harper 2000) and more (Griffith and Smith 2014). However, we know little about the people responsible for enacting accountability and putting it to work: the managers and policy professionals who help run organizations. How do future policy professionals learn quantitative accountability? How is accountability taught? How do the people responsible for organizational accountability learn it and learn to do it? These questions pertain to professional socialization. They are key to understanding the spread and implementation of accountability, and they remain neglected in organizational research on diffusion, which focuses on more macro concerns of environmental pressures and surface conformity (Bromley and Meyer 2015; DiMaggio and Powell 1983).

To answer these questions, we shift the research focus away from the implementation and impact of accountability and toward a focus on the learning of accountability. To do so, we draw from an ethnographic study of students in a highly regarded Masters of Public Affairs (MPA) program. We find that these future professionals learn accountability indirectly, not through explicit debate and dialogue about preferred forms of organizational governance, but rather through the teaching and acquisition of the quantitative techniques that undergird accountability. Through courses such as statistical analysis (econometrics), public finance, cost benefit analysis, and public program evaluation, MPAs are primed into a quantitative view of their future careers, acquire quantitative language and tools, and are socialized into accountability in ways that are both tacit and tangible, even as the appropriateness of accountability itself is largely unquestioned.

Although quantitative accountability has become a common organizational trope, we argue that its logic does not self-reproduce. Before becoming implemented and taken-for granted, it must be taught and learned—we must “account” for socialization. To make our case, we situate our argument in literature and theory on quantitative accountability, professional socialization, and inhabited institutionalism. After describing our research methods and field site, we examine how this socialization occurs, largely through courses that focus on quantitative methods. Theoretically, we make two contributions. First, we expand the concept of “priming events,” first developed through research on childhood (Corsaro and Molinari 2000), into professional socialization: priming events are activities in which graduate students (in this case MPAs), attend prospectively to their future professional careers. This priming is heavily quantitative, leading to our second contribution: We identify how the MPAs acquire quantitative “language” and “tools,” providing clarity to opaque and varying processes through which quantitative accountability, in ways both ceremonial and substantive, becomes further institutionalized. As an institutional rationale and form of organizational governance, accountability is inhabited by policy professionals who have been primed into quantitative methods, language, and tools.

Quantitative Accountability, Professional Socialization, and Inhabited Institutionalism

Today, accountability is commonplace and nearly taken for granted: Few would argue that organizations should be “unaccountable.” However, throughout much of the twentieth century public and non-profit organizations operated according to what scholars identified as a “logic of confidence and good faith” (Meyer and Rowan 1977). As long as organizations appeared to conform to the expectations of external audiences, at least ceremonially, they were provided with legitimacy (and the funding and support that comes with it) and trusted to go about their work with little interference (Scott and Meyer 1983). In this era, there was more concern with providing democratic access to organizations (such as schools and hospitals) than there was scrutiny of their outcomes (such as learning and health; Hood 1995; Meyer and Rowan 1978).

While there are numerous historical precursors (see Berman 2022, Shore and Wright 2015a), change began to coalesce in the 1980s. In Britain, Thatcher era reforms emphasized market efficiency and collapsed distinctions between the private and public sectors, subjecting public organizations to economic style “bottom lines,” emphasizing results, and replacing trust with audits (Power 1994; 1997). Born from neoliberal market values and tied to literal accounting (Carruthers and Espeland 1991), this style of “New Public Management” (Barberis 1998; Shore and Wright 1999, 2004) spread to Europe, North America, and elsewhere.

New public management (NPM), and accountability more generally, reflect a broader “audit society” (Strathern 2000; Power 1994, 1997) where “the principles and practices of modern accounting and financial control are being applied to contexts far removed from the world of bookkeeping and corporate management” (Shore and Wright 2015a, 421). In the process, the term “accountability,” which can mean many things and take many forms, becomes conflated with “‘accountancy’ so that ‘being answerable to the public’ is recast in terms of measures of productivity, ‘economic efficiency’ and delivering ‘value for money’” (Brenneis et al. 2005; Shore 2008, 281).

In the U.S. context, accountability is a form of governance for public and nonprofit organizations, one that reflects NPM and its emphasis on efficiency, markets, and performance. It is the tie to quantitative methods that makes this form of accountability a technology of governance (Shore 2008, 290; Shore and Wright 2015b). In the United States, as elsewhere, “Measures like cost benefit ratios, performance indicators, rankings, benchmarks, scorecards, and standardized tests are used to evaluate behavior and explain decisions of many different organizational actors” (Espeland and Vannebo 2007, 24).

This model for governing organizations replaces traditional forms of professional autonomy and judgment with criteria that can be measured quantitatively, introducing a new mode of control into work and life (Shore and Wright 2015b, 26). Quantitative accountability is coercive in this regard (Sauder and Espeland 2009; Shore and Wright 2004). An MPA program is a useful site for examining socialization into quantitative accountability because the MPA is among the degrees coming to represent the “new” or “managerial” professionals (Hodgson et al. 2015; Kipping and Kirkpatrick 2013; Noordegraaf 2015). In contrast to the traditional or “sovereign” professions such as medicine and law, these actors draw their status neither from functional rights and autonomy based on their ability to fill vital social needs (Parsons 1939) nor from their ability to monopolize control over a jurisdiction (Abbott 1988; Freidson 1970), but rather through their expertise and complex knowledge (Brint 1994; MacDonald 1995; Owen-Smith 2011). These “new” professionals have an important role in guiding organizations in the twenty-first century (Scott 2008), and share “common administrative or management training and similar occupational norms” where “this abstract generalized conception of management is considered broadly applicable and is viewed as a necessary and legitimate technical skill” (Hwang and Powell 2009, 269). Specifically, they draw from what has been termed “scientized knowledge” (Hwang and Powell 2009; Meyer and Bromley 2013)—the very kinds of quantitative reasoning associated with New Public Management, audit culture, and accountability. In addition to gaining status from their knowledge of accountability, “new” professionals subject others, including the formerly “sovereign” professionals, to accountability.

While there is a growing line of research on new professionals, there is not yet a line of work on their socialization—a contrast to longstanding research on the sovereign professions (Hallett and Gougherty 2018, 2024). To gain further insight, we draw from research on professional socialization in medical (Becker et al. 1961) and law schools (Granfield 1992), as well as childhood socialization (Corsaro and Molinari 2000), and “inhabited institutional” studies of accountability in K-12 education (Aurini 2012; Everitt 2018; Hallett 2010; Hallett and Meanwell 2016; Tsang 2019). Inhabited institutionalism is a useful theoretical framework because it considers both how forms of governance, such as accountability, work as a widespread rationale for how organizations ought to operate, and how people in organizations engage with and “inhabit” these institutional rationales through their social interactions with one another (Hallett and Ventresca 2006). It provides a lens to examine institutional constraints such as curriculum, constraints that partially guide interactions, as well as the dynamics and content of education as they develop through interactions between professors and students and students and their peers.

Inhabited institutionalism combines the macro focus of neo-institutionalism with a symbolic interactionist focus on meaning-making and interactions (Bechky 2011; Binder 2007). Specifically, it posits that institutions, interactions, and organizations recursively relate to one another. Taking an inhabited institutional approach means looking toward both the institutional environment as well as the organizational setting and the interactions therein. This leads to an emphasis on processes of meaning-making that are both local and immediate, as well as those that are extra-local, broad, and public (Hallett and Ventresca 2006).

As with its older, neo-institutional cousin, inhabited institutionalism developed from research on education (Meyer and Rowan 1977, 1978). However, whereas Meyer’s empirical observations of U.S. schools circa the late 1970s lead him and his colleagues to identify loose couplings between formal policies and tangible school practices (what they termed “myth and ceremony”), the policy environment since the late 1990s and early 2000s in U.S. education emphasized accountability and explicit efforts to control how teachers do their work (Ingersoll 2003). The empirical spine of inhabited institutionalism has grown from research that focuses on school accountability, and with a much broader range of coupling possibilities: Instead of assuming loose coupling (as with neo-institutionalism), accountability may be tightly or loosely coupled to an organization’s interaction order, and the nature and dynamics of those couplings are open questions to be answered through the research, lest we have little understanding of how policy actually matters for tangible organizational practice.

Accountability involves a high degree of commensuration, standardization, and coercion based on rewards and punishments, all of which promote tighter couplings between policies and practices (The “myth incarnate” instead of “myth and ceremony”). Based on an ethnography of an urban elementary school and the efforts of a new principal to implement accountability, Hallett (2010) identifies this change as a “recoupling”—a change from loose to tight. By carefully attending to local interactions, Hallett explicates how, somewhat ironically, the dynamic of recoupling created a seemingly irrational state of turmoil from what appeared to be, and was intended as, a rational policy tool.

Aurini (2012) uses a similar ethnographic approach to examine the dynamics of market accountability in a tutoring center that was part of a for-profit tutoring franchise in Canada. The franchise had a standardized curriculum and package of teaching approaches intended to appeal to a customer base that was willing to pay for supplemental education. In this economic context where customers could leave if unsatisfied, Aurini found that managers and administrators held the tutors highly accountable and they had to adhere to practices that were formalized and monitored, creating a tight coupling. Nonetheless, and at the same time, tutors and students alike found times and places to carve out autonomy, exhibiting creativity in their interactions and generating moments of loose coupling in the broader tightly coupled pattern.

In a series of studies, Everitt (2012, 2013, 2018) adds an important dimension: professional socialization. While there is a long line of research on the socialization of doctors, lawyers, and other traditional professionals (Becker et al. 1961; Granfield 1992; Haas and Shaffir 1982; see Anteby et al. 2016 for a more contemporary review), it has often overlooked the influence of larger institutional processes related to quantitative accountability. Using fieldwork and interviews, Everitt finds that novice teachers are trained to follow accountability, but at the same time, they are taught to adjust to the diverse needs of their students as a part of compulsory education, what Everitt terms “the injunction to adapt.” Through this process of socialization, and as they gain experience, teachers also accumulate their own “arsenals of practice,” which enable them to comply with accountability policies in a general sense, even as there is variation across their specific teaching practices, resulting in a combination of tight and loose coupling.

Everitt’s insights about socialization are valuable and compel us to further shift the focus from the implementation and impact of accountability to the learning of accountability, and to reflect not only on teachers, but also the “new” professionals who have a key role in bringing accountability to the variety of organizations they run. To advance these theoretical contributions, we expand relevant insights from research on childhood socialization (Corsaro 1992; Corsaro and Eder 1990), and especially what Corsaro and Molinari (2000) call “priming events.” Priming events “involve activities in which children, by their very participation, attend prospectively to ongoing or anticipated changes in their lives” (2000, 17). Extending this to professional socialization, priming events are activities in which graduate students (in this case MPAs), by their very participation, attend prospectively to their future professional careers.

Through these priming events, and the courses in which they occur, the MPAs acquire quantitative language, as well as quantitative tools. We argue that these both support the institutionalization of accountability, although in different ways. In acquiring quantitative language, the MPAs can participate in the discourse of accountability, even when they themselves do not directly employ quantification in their work. This language, even when it is more ceremonial than substantive, nonetheless reproduces the accountability status quo. Quantitative tools, in contrast, enable the MPAs to engage in techniques that actively promote substantive accountability in their work: more than myth and ceremony, these tools make accountability incarnate, even though direct debate about accountability was rare in their professional training.

Research Methods

The empirical material for this paper originates from a two-year ethnography of the MPA program in the “School of Public Affairs” (SPA) at “Central University,” ¹ alongside in-depth interviews of students, faculty, and administrators. The program is highly regarded and considered a leader in public affairs education in the United States and the world. Although there is some variation across these programs, there is also considerable conformity, as they seek accreditation by the Network of Schools of Public Policy, Affairs, and Administration (NASPAA). SPA is viewed as a model program, and historically it had a significant role in the establishment of NASPAA and the typical core curriculum. We focus on the MPA because it sits between the Masters of Public Policy (MPP), which focuses more on policy analysis, and the Masters of Public Administration (MPAd), which focuses more on management. Indeed, there is a saying in the program that, after completing the required core classes, if students obtain a concentration in policy analysis, the degree resembles an MPP, whereas if they get a concentration in public or non-profit management, it resembles an MPAd.

In this way, the research cite provides some leverage for examining all three degrees. NASPAA does not make fine distinctions among these degrees; instead, it groups and counts these programs together. As of 2024, there were close to 230 such programs with approximately 25,300 students (NASPAA 2025). The graduates of these programs gain employment in a variety of organizations across the public, nonprofit, and private sectors, and what they learn has the potential to diffuse and become a source of isomorphism and organizational change.

At SPA, for logistical purposes the full class of MPA students (approximately 115) is grouped into cohorts that take the same core courses together. To structure our fieldwork, we selected two cohorts (25–30 students each) and observed them as they completed their core courses. “The core” reflects NASPAA recommendations and is common in these programs: Public Management Economics (applied micro-economics), Statistical Analysis for Effective Decision Making (statistics, regression, econometrics), Public Finance and Budgeting, Public Management, and Law and Public Affairs. Three of these courses (statistics, finance and budgeting, and economics) have a heavy emphasis on the kinds of quantification that underlie accountability. Accountability is not the only rationale in the program, and as a hybrid degree, the MPA also includes a focus on civic and community rationales, distinguishing it from the Masters of Business Administration (MBA) (Anteby 2013; Khurana 2007). Nevertheless, throughout the ethnography, quantification, and the accountability that it supports, either eclipsed civic and community rationales, or was viewed as a means to achieve those rationales. As such, in this article, we focus on quantitative accountability and examine civic and community themes in the larger project.

After the core, we observed additional courses that were part of the two largest concentrations: policy analysis and non-profit management. These included cost–benefit analysis (CBA); public program evaluation (PPE); advanced statistics (regression techniques; econometrics); nonprofit management; and fundraising. Again, three of these courses are heavily quantitative (CBA, PPE, and Advanced Statistics), and even when these courses were not required for a concentration, they were popular electives.

In the final semester, we each observed a capstone course where students worked with external clients in a consulting capacity. Beyond the classroom, we made regular observations of “the gallery,” an informal space where students would socialize and study between classes. We also attended social events and bar crawls, some of which were sponsored by the school, others by students. For each observation, we took jottings (on computers, via texts, or paper) and converted them into fieldnotes upon leaving the field. Overall, this collaborative approach to ethnography allowed us to understand the program from differing yet complementary perspectives (May and Pattillo 2000).

In addition to the observations, we conducted 168 interviews with 79 different students. We invited all students in the full class to participate and got more responses from students in the cohorts we were observing. Nevertheless, we obtained interviews with students from all cohorts. The sample also allowed us to account for different social and demographic groupings and program concentrations. We interviewed students in their first semester (fifty interviews), second semester (forty-eight), fourth semester (forty-six), and five years into their careers (twenty-four interviews). Of the seventy-nine students, fourteen did all four interviews, nineteen did three, nine did two. Interviewing students at multiple points allowed us to trace their evolving understandings of the program and their education.

During interviews, we asked students about their backgrounds, aspirations, and academic and social experiences. Students in the program were overwhelmingly white and middle class, with around two-thirds identifying as women. Our sample shares these demographics, yet we recruited a variety of students to participate in the interviews so as to capture a range of experiences. We also conducted interviews with sixteen faculty and five administrators. Overall, the interview sample helps us to explore the range of experiences within the program and changes in the students’ lives over time.

The combination of data enables us to triangulate our findings. We analyzed the data through an iterative, abductive process (Timmermans and Tavory 2012). In abductive analysis, ethnographers are “neither theoretical atheists nor avowed monotheists, but informed theoretical agnostics” (Timmermans and Tavory 2012, 169). As a result, “in-depth knowledge of multiple theorizations is thus necessary both to find out what is missing or anomalous in an area of study and to stimulate insights about innovative or original theoretical contributions” (Timmermans and Tavory 2012, 173). Specifically, we drew from literatures on quantification, accountability, socialization, professions, neo-institutional theory, and inhabited institutionalism.

Through this process we identified, analyzed, and developed the insights on quantitative methods, priming, language, and tools as largely indirect means through which the MPAs are taught, and learn, the logic of accountability. Presenting field research on the classes we observed presents a challenge, in that so much of the material is numerical that broad swaths of our fieldnotes are coded as “quantitative” and are filled with formulas and discussions of formulas. Instead of using this material to restate what can be found in the textbooks used in the classes, we instead focus on the passages that speak to priming and the students’ responses. Although these passages did not fill as many text units as did formulas and discussions of formulas, they were common and more revealing of the meaning and implications of the education the students were obtaining. Such is the challenge, and benefit, of a qualitative understanding of how quantitative rationales are taught and learned.

Findings

Accountability Directly, Briefly

As we will see, throughout the whole of our fieldwork accountability was taught indirectly, through the quantitative techniques that facilitate accountability. Nevertheless, there was a short period in which accountability was addressed head-on. It occurred early in the first semester during the core “Public Management” course during a two-day module on “Managing Performance,” sandwiched between a prior section on ethics and followed by a section on organizational decision-making. The module stressed themes that are prominent in accountability reforms and policies, that (1) organizations should be performance and results oriented, (2) there should be rewards and punishments for those results, (3) based on quantitative measures of performance related to a standard (Stecher et al. 2010).

The assigned readings addressed U.S. policy at the federal level, highlighting similarities, continuities, and differences across the Clinton, Bush, and Obama administrations (Breul and Kamensky 2008; Joyce 2011). In class, Professor Robertson introduced the module as “Maybe the essence of why people manage, to manage performance,” including “how to measure effectiveness.” Reiterating the articles, he outlined Clinton’s reforms, specifically the 1993 Government Performance Results Act (GPRA), the National Performance Review, and National Partnership for Reinventing Government. For the Bush administration, he recalled that “a lot was made that he was the first management president, he had an MBA,” and he outlined President Bush’s “Management Agenda and Program Assessment Rating Tool (PART).” For the Obama administration, he discussed their interest in performance-informed budgeting and emphasis on cost–benefit analysis and quantitative program evaluation (Fieldnotes).

As the class discussed these initiatives, students raised issues with quantification. For example, a student asked:

“What about qualitative data? A lot is lost with just quantitative. Sometimes it’s not a matter of numbers. There’s more than that.” Professor Robertson agreed, “That’s one shortcoming,” but explained that the reforms “really talk about numerical, measurable goals, because it’s possible in a lot of agencies. But you’re right, and that’s one of the important shortcomings.” (Fieldnotes, early first semester)

Professor Robertson acknowledged the problem but carried on with the theme. Pushing further on quantitative indicators, he played a clip from a podcast titled: “Management, Measuring Performance, Dealing with Goals,” and featuring former Obama Housing and Urban Development Secretary Shaun Donovan. In the podcast Donovan emphasizes “a focus on getting numbers and hitting goals” that reflect “what we wanted to be held accountable to.” He says, “Once you’re counting things and in agreement about what we can count,” there is “incredible inspiration coming out of that,” and “if we’re making our numbers and on track to meeting our goals,” he can “sleep at night.” Reiterating these points, at the end of the module Professor Roberson emphasized: “Indicators in general need to be measurable,” and these waves of reform push “objective measures” and “most of which will be quantitative” (Fieldnotes).

Interestingly, direct discussion and debate regarding accountability was largely absent from the remainder of our fieldwork. Nevertheless, and importantly, our fieldwork was full of the quantitative techniques associated with accountability, including econometrics, budgeting and finance, cost–benefit analysis, and program evaluation. These courses were replete with “priming events” that linked these techniques to the student’s future careers. In these priming events, and in the students’ responses to them, the MPAs acquire quantitative language and tools that indirectly support organizational accountability, even as explicit discussions of accountability are rare.

Quantitative Methods and Professional Priming

This kind of priming became evident in our first moment of fieldwork. Our observations began on a sunny August morning with an orientation program intended to prepare the new students for the heavily quantitative aspects of their training. As we walked into the foyer of Whitewood Hall along with a cluster of students, we were greeted by a second-year student. She checked us in, smiled and quipped: “Are you ready for Mini Math? There’s a derivative with your name on it!” (Fieldnotes, late summer). As the new students chuckled and said “Yes,” she directed us to a classroom. It was our first fieldnote—and the first experience for the students—and we were already witnessing the prominence of math in the program.

The program required incoming students with borderline Graduate Record Examination (GRE) math scores to enroll in Mini-Math, and it was encouraged for anyone wanting a refresher, all of which was seen as necessary given the emphasis on quantitative methods in the program. Mini-Math was well attended and throughout the week, students not only learned and relearned algebra, calculus, and the basics of probability, the program administrators and professors also primed them to see math as part of their future careers. For example, during orientation the first day, the Mini-Math program director told them: “Math is a tool, an important tool” for what they would be doing “as professionals. . . analyzing. . . interpreting. . . managing” (his emphasis, fieldnotes). From the beginning, students were primed to see math as central to their professional lives.

This priming was also apparent during the course. Take, for example, how the Mini-Math instructor introduced one of the early topics in the course, the technique of substitution:

The instructor tells the students: “In the professional world you are dealing with multiple equations.” He uses the example of maximizing cost functions and says that you end up with a system. To deal with those systems of equations, substitution can be used where what you have from one equation can be moved to another equation. (Fieldnotes, late summer before start of program)

During this interaction, the instructor links the “professional world,” math, and economics (maximizing cost functions), all during a course intended to prepare students for the more intensive instruction that would begin at the official start of the semester.

This kind of socialization continued throughout the week. For example, in a subsequent class, the instructor was leading an exercise that used math to understand an important policy issue: the economics of oil prices. He told the class: “Finding the equation is just a dry matter,” but when it’s put in context it’s different. “All the time it’s about application and context. When you are a professional it’s about application.” Later he emphasized that finding equations and integrals to understand scenarios and contexts is “what we do as professionals” (Fieldnotes, late summer, emphasis added). As if to reiterate these points, at the end of Mini-Math and heading into the next set of orientation activities, the Director of Graduate Student Services told the students: “Monday is the start of your professional career” (Fieldnotes, late summer).

Primed to think of math as generally “professional,” classes began in earnest, and throughout the four semesters of coursework, we witnessed a more specific form of priming: what can be called “job dropping.” For example, on the first day of “Statistical Analysis for Effective Decision Making,” Professor Barnes introduced the course by saying it would provide them with great skills for their jobs, and whatever they do, the class will “empower you” and help them “know about the world.” Turning playful, he adds that they will be able to “impress your friends and neighbors” (eliciting chuckles from the students), by being able to define “heteroscedasticity” and bringing it up in conversation to be “erudite.” He continued:

He’s had lots of students get great jobs based on skills from this class, the advanced statistics course that follows, and from learning Statistical Analysis System software (SAS). These skills have “lots of applicability” and are used widely to “manage business” and “manipulate and use data to reveal critical information” and “maximize performance” regardless of whether jobs are in public organizations, non-profit, or for-profit organizations. Then he tells them about a former student who got a job at a prestigious consulting firm because of his familiarity with SAS, and the firm “loved that.” The student started out there for his internship, which lead to a permanent position. The firm asked him, “Where do you want to go?” and he said “Boulder Colorado” and now he’s there (students respond with “wows”). He continues: “I have many many of these examples,” so all of this will help them get really good jobs and advance in those jobs. These skills will be “one of the critical differences” between them and other candidates and will give them a “leg up.” As another example, he had a student interview with the Environmental Protection Agency (EPA). They asked her to define “heteroscedasticity” so she did and added “I can correct for it with SAS,” and they hired her “on the spot” (eliciting more “wows” from the students). (Field notes, first semester)

Although Professor Barnes did not use the explicit word “accountability,” he emphasized the ability to “maximize performance” with the quantitative skills they would learn, and with specific examples of jobs in for-profit and public organizations.

While Professor Barnes was perhaps the most “erudite,” priming via job dropping was common. For example, in his popular “Cost–Benefit Analysis” course, on the first day of class Professor Harrison emphasized: “One of my former undergraduates got a job at the Commerce Department” (Fieldnotes, early second semester). Likewise, on the first day of the “Public Program Evaluation” class, Professor Bailey emphasized:

The class is “particularly useful” for everyone, “even if numbers aren’t your thing,” because “program evaluation and these statistical techniques aren’t really going anywhere,” and even in non-profits there is pressure to show that your interventions matter. For example, she recently got an email from a former student working in a non-profit organization, and their donors want to see evidence that programs work, so program evaluation has become a part of her job in fund development. (Fieldnotes, early third semester)

Much like Professor Barnes, Professor Bailey did not explicitly mention “accountability,” but she stressed the importance of “evidence that programs work,” and how her own former students had used the quantitative techniques from the class in their careers.

Priming occurred throughout our observations, including the final semester of course work, when students were taking their capstone classes. In one such capstone, the theme was “how to measure the results of programs whose results are hard to measure,” and students were working with an array of clients to help them develop ways to measure and assess program inputs and outputs. Although the students had been taught such techniques, their clients were often hesitant and at worst resistant. Professor Maines tried to assuage them:

Part of the challenge is that “outcome-based ratings have their fans and detractors” and “lots of organizations feel it is the devil incarnate coming at you.” As a result, “You’re running into that in terms of data availability or willingness,” and with public and non-profit organizations, “things have high emotion laden political content” and those politics are reflected in the availability of information and willingness to participate. “We’re simulating the real world here. I wish it wasn’t so stressful. You are dealing with the kinds of problems you’ll be dealing with again in your professional career.” (Fieldnotes, middle fourth semester)

Without using the word “accountability,” Professor Maines emphasized outcomes and the importance and availability of quantitative data. He acknowledged resistance to measures and assessments but nonetheless primed them and urged them on with reference to their careers.

Student Responses: Surprise

Our interviews with the MPAs indicated that they were generally appreciative of these priming efforts and the quantitative skills they were acquiring. For example, a student said of her statistics professor: “He is really great about trying to give us things that we will come across in our career. He’s like, (Excited voice) ‘Oh, you’re actually going to . . . you’re going to use this one day.’ So I appreciate that” (Interview transcript, late first semester). Another student said: “Skill wise, you walk out of Stats with an actual skill that you can put on your resume, and SAS” (Interview transcript, late first semester).

While students were receptive to the priming, the fieldwork and interviews indicate that they were surprised by the heavily quantitative content of the program. Perhaps they should not have been. The promotional materials the program uses to advertise the degree are clear about the course requirements and include testimonials that echo the priming around quantitative skills. In one such published testimonial, a former student who had a prestigious job in the Federal Government working for the Office of Management and Budget said:

S.P.A. gave me an opportunity to hone my quantitative and analytical skills, which prove invaluable while preparing the President’s budget. . . S.P.A.’s collaborative environment and emphasis on group projects helped me to define the unique strengths I have to offer in a team setting. As a result, I’ve quickly become comfortable assuming a leadership role, whether on government-wide fiscal reports or at the helm of a professional organization. (Emphasis added)

Not unlike the classes during Mini-Math, this testimonial links quantitative skills with professional careers.

Nonetheless, the students did not expect so much math in a “Public Affairs” degree. As one explained:

When I first said I wanted to go to a Masters program I was thinking public affairs is going to be, again, a lot of the political science stuff I did in undergrad but more study of actual problems in government rather than theory. I did not expect much math, but then when I first started looking at—one of my friends got me a Public Affairs textbook to look at. . . And that textbook, it was Public Management [a core class that is not math centric]. So I thought, “Oh all public affairs are going to be theory like this.” I didn’t realize it would be math based until looking at the curriculum here, where it said Econ, Finance, etc. And I didn’t realize how math based until I started taking my coursework. Of my classes, almost everyone involved is doing math and data equations. (Interview transcript, fourth semester)

This student expected a focus on “actual problems in government,” and “didn’t realize how math based” the program was. Another student said much the same thing, while relaying a conversation with her mother:

My mom, when I showed her my schedule for the first semester, which was like all math, which I was not expecting, she looked at that, and she was like, “Okay, well if you do fail out. . . you’re welcome to come back home.” (Laughing) And I was like, “Alright, Mom. Thanks.” (Interview transcript, late first semester)

The unexpected quantitative focus created a fear of failure and a lack of confidence from her family.

Indeed, the quantitative focus was not only a surprise, for many students, it was a source of concern and a mismatch to their skills and previous education. These students experienced considerable stress. For example, as students sat together in the back of a classroom before the start of their statistics course during the first semester, they were talking about their recent assignments in economics and statistics:

Brenda says she was worried about economics and that stats was alright, but now they flipped. They talk about how Professor Wright said they could work on the econ homework in groups, and they didn’t expect it to be straight math. Angela says she hadn’t had math and calculus since high school. Brenda says with the economics homework she was crying over it. (Fieldnotes, first semester)

These students had come to the program with an interest in gaining experience with non-profit organizations to help people in a tangible, hands-on way. This disconnect between their expectations, backgrounds, and the classes they were taking provoked a range of emotions.

This kind of response was not unusual because the students came to the program with a broad range of academic backgrounds and varying exposure to quantitative reasoning. In a telling exception, a student with a degree in math recalled: “I think I was the only math major. I was definitely the only one I knew of. There might have been somebody else who was that I never met or talked to about it.” Given her initial expectations of “Public Affairs,” she added:

I remember being really worried about my GRE. I was—my last semester of college, I found out I had a brain tumor. . . So, I was like in my last fall semester, and I found out I had a brain tumor and I had to take the GRE, but it was really hard to prepare or study, and I remember contacting admissions at one point and just asking like, y’know, what the minimum score was and what they were looking for and it was like “Oh, we just wanted to make sure you have strong enough math skills. That’s the main section we’re worried about,” and that was a huge relief to me because that’s not the section I was worried about. (Interview transcript, career interview)

This student also said that, with her math training, “it was a really easy transition for me, but it was really a lot harder for my peers who studied liberal arts or like history or political science to go back and do this really challenging stats course or two.”

Regardless of how surprised the students may have been, quantitative methods were an intentional feature of the curriculum, and the students had to adjust to make it through the program. As the Director of Career Services explained:

They learn quickly that they have to be, have to have at least an appreciation for the quantitative side of policy analysis and determination. And they get that. They’re drinking out of the quantitative fire hose the day they enter the program. They won’t, some won’t like it. (Interview transcript)

To the extent that graduation is a successful indicator, the students did sufficiently learn these approaches: Only a handful left the program, and the vast majority completed the degree.

Language, Tools, and Quantitative Accountability

Although the students were surprised, they generally deemed their quantitative training to be valuable, but in different ways. Some felt it was important to be versed in the “language” of quantitative methods, even if they did not expect to use those methods directly in their work. Other students actively used quantitative methods as important tools in their careers. In the first case, in generally accepting (if not directly using) quantitative methods as valuable, they were indirectly supporting the forms of accountability that those techniques inform. In the second case, the students used quantitative tools to promote forms of accountability in their careers.

While the students were appreciative of their training, for many of them the quantitative approaches that they learned were less of a “tool” and more of a “language.” As one explained:

I don’t necessarily plan on running a lot of regressions in my life, and I don’t want to be a researcher, but I think being able to understand and communicate with them and see like what great insights they would have and how to incorporate in that my work, I think just knowing the language of statistics is important. (Interview transcript, second semester)

This student does not anticipate actually doing statistics in the future but does think being able to “communicate” and to know “the language of statistics” is valuable. Similarly, another student commented that the purpose was “not even do the basic computations” but rather to “use a proper vocabulary” (Interview transcript, first semester). As if echoing this, another commented that statistics was useful because it was “good to know how to like talk that language” (Interview transcript, fourth semester).

Students made similar comments regarding the popular “Program Evaluation” and “Cost Benefit Analysis” courses, both of which were heavily quantitative. Regarding program evaluation, a student reflected:

That was a lot of the background work of establishing evaluations and what sort of that language is a little bit more of the statistics behind it, that it’s helpful when reading evaluations and understanding what those mean, learning where to find them, those types of things. (Interview transcript, fourth semester)

While the class certainly involved “a little bit more of the statistics behind it,” there was considerable focus on “that language” as a way to understand what an evaluation means. Likewise, in reflecting on the CBA course, a student stressed that, rather than doing CBA themselves, “What we’re doing is evaluating someone else’s cost-benefit analysis and determining whether it’s any good. . . So again, it’s that language and sort of understanding about what these concepts are that was important” (Interview transcript, career interview).

These students did not anticipate doing the technical work of statistics in their own careers. Although they did not envision putting these methods to work in a direct way, they accepted quantitative techniques and the “language” as important. Notably, in their time in the program, they did not learn any qualitative methods as a compliment or alternative to quantitative methods, and they did not question the legitimacy of quantitative methods.

When students graduated from the program they found employment in a wide range of jobs, including positions in a large urban public school system, in local government, in the federal government, in private consulting firms, in sustainable energy start-ups, with nonprofit organizations and philanthropies, and more. Those who emphasized quantitative “language” were able to participate in the discourse around numbers that increasingly characterizes modern organizations (Berman and Hirschman 2018). However, they themselves did not produce the numbers. They were not the key quantifiers or “rationalizers” in their organizations, yet through their participation, they nonetheless accepted and tacitly supported quantitative accountability. Their familiarity with quantitative language enables them to participate ceremonially, even as they do not create or directly enforce the substantive products of the ceremony.

Other students viewed their quantitative training as more closely wedded to their future work and even their own identities. For example, when asked to describe what made something “professional,” a student responded: “I think it’s the math, and knowing when to use it and how to use it. In what situations. How to interpret the results of statistics, or how to interpret a company’s budget. That’s what makes you professional” (Interview transcript, second semester). For this student, and echoing the priming she received much earlier during “Mini Math,” math was much more than a language. Math was something to “use,” a tool, and using such a tool marked one as a “professional,” which was a status to which she aspired.

In much the same way, another student described the degree as “professional” because “the way you’re taught to quantitatively look at qualitative issues, it teaches you a way of thinking. And that’s what a professional degree is, it’s a discipline, a way of approaching a problem and the tools to do it” (Interview transcript, second semester). Instead of emphasizing “language” or “jargon,” this student references a “discipline,” a deeper way of “thinking,” of “approaching a problem” and using the corresponding “tools.” Moreover, instead of thinking of qualitative issues as distinct, they are to be converted and viewed “quantitatively.”

As they moved into their careers, these students were more active in using their quantitative training and tools to substantively engage various forms of accountability. One such student became involved in educational accountability. He found himself increasingly drawn to quantitative methods, and after receiving his MPA he enrolled in a PhD program in “Inquiry Methodology” in the School of Education at the same university. He explained that this program was relatively new, and “started around with ‘No Child Left Behind’ because of all the testing.” The program featured “a lot of psychometric components, analysis of tests, testing surveys” and the like. His funding involved working with a faculty mentor as an “evaluation associate” and “research analyst.” In this capacity, he conducted “program evaluations” to assess educational programs in two nearby school districts (Interview transcript, career interview). Interestingly, he had no prior background in education—he was originally drawn to the MPA based on his hands-on experience with public and nonprofit organizations that aid homeless youth—but he went on to use his quantitative training to engage in educational accountability.

Another former student advanced to a job as “Chief Performance Officer” for a mayor in a major metropolitan area. She said of her MPA:

I use that degree every single day. So, I do statistical analysis on a really regular basis. There’s not many people here who have an MPA so having that sort of classically trained bureaucratic lens to look at you know—could we apply cost-benefit analysis here? We do randomized control trials on occasion. So how could we apply program evaluation, and when we can’t do randomization, how can we use then the skills from program [evaluation] to mitigate some biases and get to maybe not causal conclusion, but a stronger correlate that can provide the decision makers with better information? (Interview transcript, career interview)

More than a language, her quantitative training provided her with tools to “provide the decision makers with better information.” Continuing, she said using “performance indicators” and “metrics” provided the means to create “agreement that we’re going to hold ourselves accountable and this is how we’re going to hold ourselves accountable, through these measurements.” Her engagement with accountability was not ceremonial, it was substantive, and the quantitative tools she learned enabled her to make accountability incarnate.

While that MPA was working in local government, another one was using quantitative tools to meet the accountability demands of the federal government. He was a green energy analyst with a company doing work contracted by the federal government. He explained:

The Feds are required to—if you’re going to do an investment, it has to be life cycle cost effective. . . So like any measure, if I was going to do—if I was going to do like a lighting retrofit of a facility, so let’s just say I’m taking out all the fluorescent bulbs. I’m going to put in all LEDs, or that’s the proposal. And I would need to run the cost-benefit and basically show that the costs are indeed paid for by the benefits. And they’re paid for in an acceptable time frame, which I think for the Feds is a ten-year window. It has to pay back in ten years. (Interview transcript, career interview)

He spoke of accountability in a cost–benefit format as if such an approach was largely unproblematic. That is, this view upholds economic efficiency as a priority, “It has to pay back in ten years.” He believed deeply in green energy and sustainability, and he was dedicating his career to these issues, yet he was a participant in a system that put a quantitative value and limit on something that is priceless and under great threat in the twenty-first century: the environment (Ackerman and Heinzerling 2002).

This kind of valuation is characteristic of Western styles of thought (Fourcade and Babb 2002) and is particularly apparent in U.S. healthcare. For example, one MPA became an analyst for a major U.S. health insurance company. Of her training she said: “Cost-benefit analysis became like one of the linchpins of my career. I mean it’s, yeah. I mean pretty much everything, every decision that you make in healthcare analysis comes down to a cost-benefit analysis” (Interview transcript, career interview). As with the previous example, this form of quantitative accountability puts a price on something many cultures deem a priceless right: Health. Far from being ceremonial, she uses this tool to create substantive accountability.

Discussion and Conclusion

The spread of principles and techniques of financial accounting into new systems of measuring, ranking, and auditing performance represents one of the most important and defining features of contemporary governance. (Shore and Wright 2015a, 415)

I think that any way you can use numbers is always—not only looks better, it probably is better in making sure that you’re able to get your recommendations. (MPA career interview)

Whether quantitative methods were viewed as a language or a tool, students in the MPA program that we studied largely accepted the value of numbers and were primed to see quantification as part of their future professional careers. This is not to say that people in the program did not recognize the limitations of such an approach. Indeed, while our fieldnotes are flush with quantitative material, they are also littered with disclaimers that acknowledge problems with measurement. For example, in the course on quantitative program evaluation, the professor—herself an economist who studied the impacts of accountability policies on schools—allowed that measurement can have unintended consequences and incentivize bad behaviors: “Pick your quantitative measure, pick your goal distortion.” In the conversation that followed, a student brought up a scandal in public schools in Atlanta, Georgia, where teachers promoted cheating on standardized tests. The student asked, since that was “illegal,” was it really “rational?” The professor responded:

“Absolutely,” when you face the prospect of having schools taken over because of low test-scores, having outsiders come in and “gutting the entire staff,” then “why wouldn’t you go in an falsify your test scores?” adding that it is actually “a very rational incentive that people respond to.” (Fieldnotes, third semester)

Importantly, this professor was acknowledging inexorable problems with quantification (Espeland and Sauder 2007; Shore and Wright 2015a). However, disclaimer made, she proceeded with the quantitative task at hand; quickly returning to instruction on how to measure organizational outcomes as a means to assess the impact of policy interventions. This was the norm throughout our fieldwork: Problems were acknowledged but not deeply interrogated, and the quantitative work carried on. Yet there is more at stake here than numeracy, because these techniques are wedded to a widespread rationale of organizational control: accountability (Espeland and Vannebo 2007).

Although contemporary accountability has become synonymous with “accountancy” (Shore 2008, 281), it is important to recognize that it can mean many things and take many forms. However, in the program we studied, there was little discussion of these alternatives. An example that proves this general rule is found in the case of an MPA who, when we interviewed her five years into her career, had a position as senior analyst in natural resources and the environment at the U.S. Government Accountability Office. This was the type of high profile, federal job that many students cherished, and which the MPA program advertised as an exemplary outcome. She said the MPA was an important credential, without which she may not have been hired, but she was doing qualitative evaluations. She explained:

GAO is interesting because they bring you in for two years to train you in the GAO process. So, essentially, it’s like going back to school and learning a whole new skillset. So, they can bring in people with this huge range of backgrounds and train them on how to do interviews, how to write up interviews. (Career Interview)

She had to learn these techniques on the job, as she had no exposure to qualitative methods and qualitative accountability in the MPA program.

It is possible that students in other MPA programs do learn these alternative techniques. As with all ethnographies, we take care to not overgeneralize based on our findings. At the same time, there is reason to expect isomorphism, because the program we studied had a role in establishing the very standards that NASPAA uses to accredit other programs, it is recognized as a leader in the field and is upheld as a model program. If we are to understand how accountability operates and how it spreads as form of organizational control, we need more research on these educational settings.

Nor is the MPA the only degree that features this kind of training: there are many curricular similarities across the MPA, the MBA, and the MPP. Although their foci may be somewhat different, all these programs stress quantitative language and tools. Many international students seek enrollment in MPA, MBA, and MPP programs in the United States, and it is also true that these programs are increasingly being created in universities around the globe. What are the similarities and differences in content and training across these degree programs and across their national settings? What do these similarities and differences tell us about accountability and the policy professionals who inhabit accountability? These are important questions, and future comparative research can shed much light on the form, content, and dynamics organizational accountability.

For the time being, and for this article, we have limited our focus to the question of how future professionals are taught and learn accountability. By focusing on the MPA, one of the degrees associated with the “new” or “managerial” professions, we find that direct debate about accountability as a form of organizational governance was rare in the program that we studied. Nonetheless, the MPAs learn accountability indirectly, via the quantitative techniques that underlie accountability. In examining these processes, we make two contributions to theories of professional socialization and inhabited institutionalism. First, we expand the concept of “priming events,” which was initially developed through research on childhood socialization (Corsaro and Molinari 2000), and extend it to professional socialization. In this arena, priming events are activities in which graduate students (in this case MPAs) attend prospectively to their future professional careers. As we have seen, in the MPA program this priming is heavily quantitative, leading us to the second theoretical contribution, regarding quantitative “language” and “tools.” Identifying quantitative language and tools lends clarity to opaque and varying processes through which quantitative accountability becomes further institutionalized. Equipped with quantitative language, the MPAs can participate in discourses around quantitative accountability, even if they themselves do not develop or directly utilize such techniques. This engagement may be more ceremonial that substantive, but it nonetheless sustains the apparatus, lending it credibility in the absence of critique. Equipped with quantitative tools, the MPAs can engage substantively, giving flesh to the apparatus and making accountability incarnate.

As prominent as quantitative accountability has become, it does not self-reproduce. Rather, it is inhabited by policy professionals who have been primed into quantitative methods, language, and tools, and who use language and tools to enact accountability in ways that are both ceremonial and substantive. If we are to understand quantitative accountability as a contemporary mode of organizational control, it is not enough to examine its impacts and outcomes. We must also account for socialization.