Rethinking Science as a Vocation: One Hundred Years of Bureaucratization of Academic Science

Training and Careers in Bureaucratized Science

We expect this bureaucratization of scientific work to affect the training and careers of scientists. Traditionally, scientific training and careers followed a craft model, where aspiring scientists learn to become fully task integrated scientists, through years of apprenticeship under a master craftsman and exposure to all aspects of research, thereby becoming fully able to execute the skills of her trade (Hackett 1990; Hagstrom 1964; Johnson 2017; Laudel and Gläser 2008; Walsh 1989). These fully integrated scientists are equipped with the diverse skills needed to be an academic principal investigator (PI) and, importantly, to train the next generation of integrated scientists. ³

While Hagstrom and Swatez argued that these bureaucratized structures were unusual cases in science in an earlier generation, Walsh and Lee (2015) argue this bureaucratization of science is now widely institutionalized and, in particular, division of labor pushes trainees into premature specialization, becoming semi-skilled participants in teams. Teich (1982) argues that research centers’ dependence on hierarchically organized team science and short-term project funding can produce conditions where graduate students and even young PhD researchers are trained primarily in supporting roles. Johnson (2017) adds nuance and a microlevel grounding to this trend. His interviews point to advisors running large commercially focused academic labs where the faculty have abandoned their fundamental duty of training graduate students in the broad set of craft skills. Instead, these more bureaucratized labs have the students and postdoctoral researchers primarily engaged in routinized tasks, often with limited scientific content:

The work some of my [commercialist] colleagues have their graduate students do just astonishes me. They do things the way it’s done in industry. You will have a bench chemist doing a reaction at fifty-two different temperatures and fifty-two different solvents, with no hypothesis, just trying everything in sight, completely mechanical. Where’s the scholarship in that? That’s a complete waste of the student’s time. (pp. 54-55)

In this more bureaucratized environment, young scientists today might spend much of graduate school optimizing computer code for a large physics experiment or extracting samples in a biology lab or doing the statistical analyses of other people’s data. Such training best prepares young scientists to fill specialist positions that we call “supporting scientists,” which might have organizational labels such as technician, serial postdoc (sometimes called “permadoc”), or staff scientist. Such supporting scientists are researchers with important specialist skills, but who may not be fully capable of executing a complete research project and, likely, not as committed to the research question nor as motivated by the scientific recognition system (Hackett 1994; Hagstrom 1964; Merton 1940, 1973). Traditionally, university labs or research teams have the dual function of producing science and producing scientists who are fully trained to become future PIs (Hagstrom 1964; Johnson 2017; Shibayama, Baba, and Walsh 2015). However, the bureaucratization of scientific work makes it hard to achieve these two goals at the same time. Instead, these structures may end up generating trade-offs in these two goals (Johnson 2017). Put differently, in this changing environment, research teams generate scientists whose composition has changed over time, with fewer integrated scientists and more supporting scientists (Milojević, Radicchi, and Walsh 2018). Furthermore, Johnson (2017) argues that many senior scientists prefer to hire postdocs rather than training graduate students, because the postdocs do not need the broader training that one should give a graduate student and can be put to the more mechanical tasks of larger, more commercially focused, labs. In other words, this system generates both the supply of and demand for supporting scientists. Therefore, research teams still generate scientists but different kinds of scientists from those trained in the craft model. Similarly, Laudel and Gläser (2008) argue that “apprentices fade out of their scientific community by either abandoning research or conducting dependent research, i.e. supporting the research of others who are visible as colleagues” (p. 396).

Policy discussions about this transition tend to bemoan the inability of large numbers of PhDs to make the organizational transition into tenure track jobs (and perhaps the associated inability to make the cognitive career transition into independent scholars) as reflected in multiple generations of National Academy reports (National Research Council 1981, 1998, 2005). However, given the prevalence of such supporting research workers, and their critical importance in the production of science, we prefer to redefine the research workforce away from this traditional image of an apprentice-colleague-master progression (often paired with a graduate student-postdoc-tenure track faculty organizational career) to refocus the discussion on the actually existing work practices in contemporary scientific research.

Competition, Commercialization, and Bureaucratization

Growing team size is not the only force generating bureaucratic structuring and a cadre of supporting scientists. Competition for funding and the demands for productivity, reinforced by the rise of high-stakes incentive and evaluation systems (Chatelain-Ponroy et al. 2018; Gläser, Spurling, and Butler 2004; Whitley 2007), also lead to an emphasis on specialization and training in supporting roles, leading to a cycle of supporting scientists (Hackett 1990; Teich 1982). Therefore, both size and competition reinforce these dynamics in the division of scientific labor, producing a fundamental transformation in scientific work toward deskilling and marginalization. Johnson (2017) argues that in the current university environment that emphasizes productivity and funding, bureaucratically structured, commercially oriented labs are increasingly outcompeting more traditionalist craft structured labs. As universities emphasize technology transfer more and more over time (Mowery and Shane 2002), many research labs are becoming more like commercialist labs, with their members’ work more cognitively mechanical and bureaucratized (Johnson 2017).

Specialization: Vocation versus Alienation

Weber (1946b) laid out a cogent summary of the structural and cognitive/attitudinal foundations of science as a vocation in his lecture one hundred years ago. Weber begins with a discussion of the work conditions of a young aspirant to the role of professor (academic scientist), contrasting the Privatdozent system (a type of journeyman way station between the graduate student apprentice and the master professor) in German universities of his day, with the more bureaucratized system of US universities. Weber (1946b) also compares the craft model to the large research institutes in Germany, which required considerable funding to sustain their scale and were organized more like a bureaucratized capitalist enterprise (Weber 1978, 974). In particular, Weber (1946b) emphasizes the hierarchy of the modern science institute (the rise of the research “manager”) and the proletarianization of researchers, highlighting the separation of the researcher from the means of production of research. However, this changing organization of work had not yet, and maybe still hasn’t, changed career structure expectations or the mindset of scientists, although the risk is there. As Weber argues, such bureaucratized structures may increase productivity but may not be compatible with science as a calling:

As with all capitalist and at the same time bureaucratized enterprises, there are indubitable advantages in all this [NB: productivity]. But the “spirit” that rules in these affairs is different from the historical atmosphere of the German university. An extraordinarily wide gulf, externally and internally, exists between the chief of these large, capitalist, university enterprises and the usual full professor of the old style. This contrast also holds for the inner attitude. (Weber 1946b, 131)

Weber then goes on to analyze the internal attitude of the scientist’s calling. Weber (1946b) notes the increasing specialization of science (even one hundred years ago) but argues that this specialization may be a precondition for living one’s calling:

In our time, the internal situation, in contrast to the organization of science as a vocation, is first of all conditioned by the facts that science has entered a phase of specialization previously unknown and that this will forever remain the case. Not only externally, but inwardly, matters stand at a point where the individual can acquire the sure consciousness of achieving something truly perfect in the field of science only in case he is a strict specialist. (p. 134)

This contrast between Weber (1946b) and Marx ([1844] 1959, [1867] 1999) leads us to think about the meaning of specialization in Weber’s use of the term. If specialization means the same for Weber and Marx, we can draw two opposite predictions: one (Weber) is that specialization sustains science as a vocation, whereas the other (Marx) is that specialization undermines science as a vocation. Another possible interpretation rests on decoupling specialization into field specialization and task specialization. Weber seems to be referring here to field specialization, where each integrated scientist specializes in her (increasingly narrow) field and contributes to science using the depth of her knowledge of that specialty. Therefore, Weber argues, only the specialist can truly develop a scientific result. This interpretation of Weber’s meaning of (integrated) specialist seems most likely, as it distinguishes specialization from the division of labor, which shows up in his later discussion. On the other hand, Marx’s arguments about alienation resulting from specialization may be more focused on task specialization. As was the case when manufacturing work transitioned from craft to industrial production, scientific operations are split up, isolated, and each made the exclusive function of a separate supporting scientist, producing alienated task specialists, that is, the separation of conception from execution can reduce commitment to the outcomes of the work (Braverman 1974; Chinoy 1955). Braverman (1974) argues that the advance of industrial capitalism is characterized by an increasing separation of conception from execution. Larivière et al. (2016) show that this separation is common in scientific work. Therefore, proletarian scientists experiencing task specialization can become semi-skilled operatives, mechanically completing externally assigned tasks (Johnson 2017; Gläser, Spurling, and Butler 2004), without embracing science as a vocation. Echoing the work of Marx ([1844] 1959) and later Braverman (1974) on the relation between division of labor, deskilling, and alienation, Walsh, Lee, and Tang (2019) argue that division of labor is pathogenic, in part because it generates alienated “hired-hand” researchers who have lost the calling and therefore have to be closely monitored and controlled (Roth 1966; Hackett 1994). Similarly, Merton (1973, 332) argues, “the changing organization of research may make for estrangement of scientific workers from the scientific inquiry in which they have taken part, after the fashion observed for complex division of labor by Adam Smith, Hegel and Marx.” Reflecting this tension in the meaning of specialist, Weber (1946b) also prefigures the existence of men and women of science who may serve science best in a supporting role:

However this may be, the scientific worker has to take into his bargain the risk that enters into all scientific work: Does an “idea” occur or does it not? He may be an excellent worker and yet never have had any valuable idea of his own. (p. 136)

The relations between the different meanings of specialization (field vs. task) or the level of specialization in Weber’s term (specialist vs. generalist) and a scientist’s attitude toward science as a vocation can generate a variety of testable research questions. In particular, can commitment and satisfaction be sustained if work in a bureaucratized structure no longer allows living the calling (Duffy and Dik 2013; Robinson and Barron 2007; Bloom, Colbert, and Nielsen 2021)?

The Rationalization of Science

We can also contrast Weber (1946b) with Schumpeter (1942) on the question of whether a collective scientist can fulfill the challenge of solving the increasingly boundary-spanning problems of contemporary science. By collective scientist, we mean supra-individual projects (those at the European Organization for Nuclear Research [CERN] being an extreme case), where the team is making the discovery, and the results are not readily attributable to any member (Gläser, Spurling, and Butler 2004). Such team projects are increasingly the norm to the point where the team often is listed as the “author” on the paper describing the finding. However, this still leaves us with the question of the individual team member’s attachment to the project and commitment to/experience of science as a vocation. Weber (1946b) notes that division of labor (including outsourcing of statistical analyses) may make the project vulnerable to missing critical results, and, furthermore, notes contributing to the advance of science cannot be easily rationalized:

No sociologist, for instance, should think himself too good, even in his old age, to make tens of thousands of quite trivial computations in his head and perhaps for months at a time. One cannot with impunity try to transfer this task entirely to mechanical assistants [NB: supporting scientists] if one wishes to figure something, even though the final result is often small indeed. But if no “idea” occurs to his mind about the direction of his computations and, during his computations, about the bearing of the emergent single results, then even this small result will not be yielded. (p. 135)

In contrast, Schumpeter (1942) argues innovation is becoming routinized as a team activity of trained specialists who systematically and deliberately pursue innovation rather than depending on a flash of individual genius. A good example is the movement toward “rational drug design,” where drug design moves from random screening driven by an individual researcher’s insights (Baba and Walsh 2010) to team work using specialized knowledge to examine the cell structures and then design molecules that exactly fit the opening in the cell receptor (Werth 1994). Schumpeter (1942) argues this rationalization of innovation becomes the dominant form; makes progress an automatic, self-sustaining process; and further makes the head of the organization “just another office worker.” In this transition, Schumpeter concludes that eventually large enterprises will lead innovation, wiping out the small- or medium-sized firms. Schumpeter’s view is consistent with the collective scientist model that we can see in an organization like CERN and also with Weber’s description of the great science institutes of his day. This debate raises two related questions for future research. First, do size and bureaucratization change the types of discoveries (Milojević 2015; Wu, Wang, and Evans 2019)? Second, does size, bureaucratization, and rationalization of scientific work change scientists’, especially supporting scientists’, vocational attitude or self-image?

Tensions in the Bureaucratized Vocation

Weber develops his argument by moving beyond the structural conditions that make the vocation of science difficult to enact in contemporary academic institutions and going into depth on the meaning of a vocation for science. The task hyperspecialization of scientific work raises the question of whether such collective scientists, “a productive mechanism whose parts are human beings,” to quote Marx ( [1867] 1999, Ch. 14, sec. 1), can collectively and individually have a calling for science. Weber rejects the claims that a vocation is evidenced through a public “personality” as a scientist. Fame is not necessary nor sufficient as evidence of being of the elect (cf. Weber 1930): “Instead of this [fame], an inner devotion to the task, and that alone, should lift the scientist to the height and dignity of the subject he pretends to serve. And in this it is not different with the artist” (Weber 1946b, 137). Weber’s internal orientation aspects can be contrasted to Merton’s (1973) socially focused view of science. In the Mertonian framework, one is only a scientist to the extent that one publishes her findings and these are accepted and taken up (cited) by peers (Merton 1957). Merton argues that recognition from the published work can itself be a reward for scientists, but further that it can bring follow-up material rewards such as individual income and resources for future work, which shows the importance of recognition in science. This is an outward facing motivation to conduct science. On the other hand, Hagstrom (1964) argues that bureaucratization leads, for most supporting scientists, to a loss of the traditional Mertonian link between contributions to science and the citation-based recognition system. This quest for fulfillment through peer recognition may be still a goal for a declining number of project leaders but not for the growing number of supporting scientists. Hence, bureaucratization may destroy the Mertonian incentive system. However, the collective scientist may make compelling enough contributions that the individual members still feel they are fulfilling their calling (perhaps in the way that symphony musicians feel about orchestral performances). As Weber (1946b) concludes in Science as a Vocation: “We shall set to work and meet the ‘demands of the day,’ in human relations as well as in our vocation. This, however, is plain and simple, if each finds and obeys the demon who holds the fibers of his very life” (p. 156). This demon is the compulsion that derives from having a calling, in Weber’s case, a calling to do research and advance knowledge (cf. Bunderson and Thompson 2009).

It is an empirical question whether the new organization of science is consistent with an inner calling for science—and whether such a calling is necessary for the advance of science. Such a calling may be even more difficult to maintain as increasingly bureaucratized scientific teams are also forced to justify their growing resource demands through appeals to the practical implications of their work (Johnson 2017). Weber (1946b) suggests that such appeals are, at best, orthogonal to the vocational attitude of the scientist:

One does [science], first, for purely practical, in the broader sense of the word, for technical, purposes: in order to be able to orient our practical activities to the expectations that scientific experience places at our disposal. Good. Yet this has meaning only to practitioners. What is the attitude of the academic man towards his vocation—that is, if he is at all in quest of such a personal attitude? He maintains that he engages in “science for science’s sake” and not merely because others, by exploiting science, bring about commercial or technical success and can better feed, dress, illuminate, and govern. (p. 138)

The demon that compels the pursuit of scientific advance may reside inside the individual. However, in a craft model of scientific work, the structure of the work also draws out the vocation for the work. The training and holistic nature of the tasks in a craft model helps develop and reinforce one’s vocation. It helps one recognize and express one’s calling. The bureaucratic structure of contemporary scientific work is less supportive of this vocation. Moreover, relatively, and perhaps absolutely, fewer and fewer scientists will be trained as integrated scientists, losing the structural and socialization foundations for the vocation (Hackett 1990; Laudel and Gläser 2008). Therefore, in a bureaucratic model, vocation may be left with only the inner attitude, losing its structural support. Eventually, it may be the case that most scientists do science without having the vocation, that scientific work becomes alienated labor (Hackett 1994; Hagstrom 1964; Merton 1973). Bureaucratization crushes the demon. In an only slightly less pessimistic version, we may have a situation where a small group with the vocation runs projects that involve gathering up the rest of the researchers, that is, supporting scientists in the service of the PI’s vision, leading to a hollowing out of the middle class of integrated journeymen and small master scientists (cf. Gläser, Spurling, and Butler 2004; Laudel and Gläser 2008).

However, this is not a necessary outcome. It may be possible to maintain this inner calling for science, even in the face of a science that is structured as large teams of specialists. There may be some analogy to the alienated auto worker who builds custom cars in his garage on the weekends. And, across multiple projects, a researcher may move in and out of supporting roles, with an occasional project under her control, which may help sustain the vocation (although the findings of Milojević, Radicchi, and Walsh (2018) suggest that such cases are becoming less and less common). Sustaining the vocation even among the supporting scientists may depend in part on the extent to which scientists in these roles are accepted as full-fledged members by other scientists, particularly the PIs and other integrated scientists (Bloom, Colbert, and Nielsen 2021). Bloom, Colbert, and Nielsen (2021) argue that this recognition by one’s peers that one is a called member of the “brotherhood or sisterhood” of the profession is critical for one’s identity as living one’s calling. Having supporting scientists accepted and recognized as fully called members to the “brotherhood and sisterhood” of scientists may be key to maintaining their vocation (Kruytbosch and Messinger 1968). In contrast, if supporting scientists are treated as “hired hands” (Roth 1966), both by their peers and by the organization, then maintaining the calling without this social support may be particularly difficult. Thus, scientists may still keep their vocation, even as a hyperspecialist who is part of a medium or large team, so long as they can keep an attachment to this larger purpose, see themselves as a critical component of this result, and be seen as such by their peers, that is, so long as the work context allows them to live their vocation. Lacking these may make maintaining a vocation and avoiding slipping into alienated hired-hand labor exceedingly rare.

Furthermore, this whole debate may be overly concerned about the loss of science as a vocation. Since the current generation of senior scientists may have experienced how science worked in a craft model and how science is now, in a more bureaucratic model, this transition to a new form of producing science and scientists may generate pessimistic predictions on the fate of the vocation. New generations of scientists will be born into bureaucratized science and they may grow their vocation in this new system. Even in the case that few or no scientists have the vocation, according to the Schumpeterian view on the routinization and rationalization of science, we will still be able to generate scientific advances. Schumpeter (1942) argues that industrial innovation has been more and more routinized, rather than primarily depending on an individual heroic entrepreneur. In the same way, one could imagine that scientific work is also becoming an organized and routinized activity with an increasingly bureaucratic structure. ⁵ Hence, scientific work may still advance, perhaps in an incremental, data-driven way, without having people with the skills or inner drive necessary for making substantial discoveries (what Fuchs [1992] refers to as fact-based science). ⁶ Weber (1930) makes a similar argument in Protestant Ethic, when he argues that the concept of a calling was critical in sustaining the capitalist entrepreneur at the birth of rational capitalism, but that once capitalism is fully institutionalized, it can move under its own power without the need for its participants to be driven by the compulsion of a calling.

However, reflecting this tension in his writings between a vocation as being fundamental to science and rationalized, bureaucratized systems moving under their own power without need for the support of the calling, Weber (1946b) resisted this interpretation of this trend in science:

Nowadays in circles of youth there is a widespread notion that science has become a problem in calculation, fabricated in laboratories or statistical filing systems just as “in a factory,” a calculation involving only the cool intellect and not one’s “heart and soul.” First of all one must say that such comments lack all clarity about what goes on in a factory or in a laboratory. In both some idea has to occur to someone’s mind, and it has to be a correct idea, if one is to accomplish anything worthwhile. And such intuition cannot be forced. It has nothing to do with any cold calculation. (p. 135)

In sum, the bureaucratization of science raises the following questions: Can we still have vocation in this bureaucratic structure? And if we do not, can we still have science? Based on the contrasting perspectives we speculated on above, we may predict three different plausible outcomes of the bureaucratization of science: (1) we keep the vocation (Weberian view), (2) we lose the vocation and also lose science (Marxian view), and (3) we lose the vocation but keep science (Schumpeterian view). Thus, whether this vocation can survive bureaucratically structured science is an open question. This is the core of the debate and a key focus for future research and policy and organizational interventions.

Bureaucratization and Training

A key insight from the discussions above is that scientific training increasingly takes place in a bureaucratized structure, one very different from the craft-based training model that science has traditionally followed (Johnson 2017; Walsh and Lee 2015). Since scientific teams are charged with both producing knowledge and training young researchers, this new organization of the work raises a variety of challenges. As Hackett (1994) and Johnson (2017) point out, the highly bureaucratized setting of contemporary labs may push young researchers into premature specialization, leading to stunted training (cf. More 1980). Similarly, Teich (1982) argues that the participation of graduate students and young postdoctoral researchers in large, bureaucratically organized teams in research centers focused on applied research can limit their development as independent researchers. As counter evidence, Feldon et al. (2019) find that this “cascading mentorship” structure is associated with greater skill development among PhD students. Hence, it is an open question how bureaucratization changes the training function of academic science. This change in training models also raises the question of new forms of inequality in science. It may include the creation and reinforcement of hierarchical rankings of different forms of knowledge and different types of contributions to the collective project, for example, between technical and theoretical knowledge (Hong 2008). The result might be a two-tier structure, with some on the integrated scientist path and others on the supporting scientist track, which can create invidious comparisons and other tensions in science teams.

Bureaucratization and Motivation

The traditional model of the scientist driven by internal motivation (Weber’s “calling”) and the Mertonian model based on recognition (Merton 1957) depend heavily on both the work of science being intrinsically interesting (task motivation) and on a tight link between the credit assigned to a scientific finding and the personal recognition accruing to the scientists who created it (recognition motivation). However, the main goal of supporting scientists is providing their specialized skills to accomplish a PI’s project rather than building their own academic reputation (Gläser, Spurling, and Butler 2004; Hagstrom 1964). The growth of teams of supporting scientists also uncouples the links between authorship and the reward structure of science, creating problems of control and of incentives (Jabbehdari and Walsh 2017; Biagioli 2003; Merton 1973; Gläser, Spurling, and Butler 2004), which is the domain of the organizational behavior and human resource scholars. These employee scientists become more and more similar to employees in corporations, creating the need to design structures and incentives that align employees’ goals with their organizational goal, for example, productivity, and where contributions to the organizational goal become the basis for career success, either within their organization or through being recruited at higher salaries by rival organizations (as in many bureaucratic professions, such as engineering or journalism).

Bureaucratization and Alienation

As suggested above, one concern is that bureaucratization may also generate alienated scientists (Hackett 1994; Merton 1973). With the increasing specialization of scientific work, and the increase in supporting scientists who do not themselves direct the research trajectory, scientists may more and more see their work as external to themselves (Marx [1844] 1959) and treat their work as simply the fulfillment of assigned tasks rather than as a concretized expression of their vocation (Roth 1966). While there is an extensive literature on the alienation of factory work (e.g., Chinoy 1955; Walker and Guest 1952) and of service work (Hochschild 1983; Leidner 1993), there is much less work in this tradition examining how academic scientists view their work and the relation between their self and their work products. A calling for science may be unsustainable in the face of a bureaucratized work structure, that is, there is no scientific exceptionalism. However, like the work redesign studies of an earlier generation, perhaps we can find new ways of organizing the work (job rotation? more holistic training?) that would sustain that craft ethos, maintaining the scientist’s calling. It is an empirical question as to whether one or the other outcome is more likely, or, put differently, what structural characteristics of the work and of careers make alienation more or less likely?

Bureaucratization and Team Performance

In addition to the implications for training, motivation, and alienation, the discussion above suggests a variety of other potential implications related to the outputs of science. The bureaucratization of scientific work is the result of a self-reinforcing mechanism related to increasing team size and competition for funding. The contemporary academic system rewards speed and productivity, and hence there are benefits from bureaucratic structuring of scientific teams. Murayama, Nirei, and Shimizu (2015) show that the separation between the managerial role in the project and the person primarily responsible for executing the research is positively associated with research productivity and the impact gets larger as the team becomes larger. Shibayama, Baba, and Walsh (2015) find division of labor (separation of conception from execution) is associated with greater lab productivity for applied fields, although in more basic fields, a more integrated, overlapping task allocation (more craft model) is associated with greater productivity.

However, if we consider creativity as the goal, bureaucratic structures may have a more mixed effect on performance. Lee, Walsh, and Wang (2015) find division of labor is associated with greater novelty of scientific outcomes but at a decreasing rate. However, Murayama, Nirei, and Shimizu (2015) find that hierarchy is associated with less serendipity (see also Shibayama, Baba, and Walsh 2015). Hence, while there is some evidence that bureaucratization increases productivity (number of publications), the effects on creativity (novelty, serendipity, and basic research findings) are more mixed. Increased bureaucratization associated with larger team size may be one explanation for the relation between larger team size and producing more incremental science (Milojević 2015; Wu, Wang, and Evans 2019).

Furthermore, even if the bureaucratic structure of science is superior for productivity, in an environment that incentivizes speed and productivity, this structure may have an unexpected downside, that is, sacrificing caution and accuracy to the demands of productivity (Walsh, Lee, and Tang 2019; Warren 2003). This dilemma from the conflicting goals of bureaucratized productivity versus craft quality is not limited to scientific work but is also common in other collaborative work settings such as construction work or hospitals (Goodman et al. 2011; Riemer 1976). This prior work shows that different collaborative structures (e.g., task isolation vs. redundancy) can be more or less pathogenic (Goodman et al. 2011; Walsh, Lee, and Tang 2019). At the same time, rationalization and standardization may improve the reproducibility of scientific findings (National Academy of Sciences, Engineering and Medicine 2017). Hence, the effects of bureaucratization on the reliability of science becomes a key open question.