You will be provided with a reference and some statements. Please determine whether each statement is 'supported', 'unsupported', or 'unknown' with respect to the reference. Please note:
First, assess whether the reference contains any valid content. If the reference contains no valid information, such as a 'page not found' message, then all statements should be considered 'unknown'.
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[
    {
        "idx": 1,
        "result": "supported"
    },
    {
        "idx": 2,
        "result": "unsupported"
    }
]

Below are the reference and statements:
<reference>
Remote Control: How Organizations Decide Whether to Adopt Remote Work

Rebecca Hinds
Stanford University

Aruna Ranganathan
UC Berkeley

ABSTRACT

Remote work is expected to feature prominently in the future of work. A key decision that
organizations must make is whether to adopt remote work. Some companies are adopting fullyremote arrangements, others are adopting predominantly in-person arrangements, and, still
others are adopting hybrid arrangements. We studied an organization that, despite remote work
offering cost savings, work being conducive to remote work, and strong enthusiasm for remote
work, only minimally-adopted remote work. Our 16-month organizational ethnography
revealed one important organizational process—status contests—that influenced the decision
of whether to adopt remote work. Our findings illustrate how high-status organizational actors
used a status toolkit, comprising three tools—using abstract knowledge, accessing and
allocating resources, and first-mover actions—to drive their organization’s limited adoption of
remote work. In influencing remote work adoption to meet their needs and preferences, these
high-status actors further cemented their high-status position, while marginalizing low-status
actors and thereby perpetuated inequality within the organization. Our process model
contributes to research on remote work and the future of work, organizational status and
inequality, as well as the sociology of classification.

1

INTRODUCTION
The organization of work is changing in important and fundamental ways. New
emergent technologies such as artificial intelligence, data analytics, robots, and sensors are
changing work practices (Ranganathan and Benson, 2020; Barley, 2021; Bailey et al., 2022).
These new technologies are automating and augmenting humans’ decision making and work
practices (e.g., Murray, Rhymer, and Sirmon, 2021; Lebovitz, Lifshitz-Assaf, and Levina,
2022). They are changing relationships among occupational groups in organizations (e.g.,
Barrett et al., 2012; Beane, 2019). As well, they are changing employment relationships, such
as through algorithmic management (Kellogg, Valentine, and Christin, 2020) and the
emergence of the “gig economy” (Adler, 2021; Ashford, Caza, and Reid, 2018; Caza, Reid,
and Ashford, 2021; Cameron and Rahman, 2022). All of these changes are shaping the “future
of work,” spurring significant re-evaluation of our “fundamental theories and ideas about
organizations and organizing” (Bailey et al., 2022: 2).
There is little doubt that remote work will also feature prominently in the “future of
work.” Yet many unanswered questions remain. One key decision that organizations are
grappling with is whether to adopt remote work. Here, there is significant variation. On one
end of the spectrum, there are fully-remote organizations such as GitLab and Zapier that have
always been fully remote, without a single physical office (Choudhury et al., 2020). There are
also organizations such as Airbnb, Twitter, and Dropbox that have committed to allowing their
workers to permanently engage in remote work moving forward (Smith, 2022). On the other
end of the spectrum, there are organizations such as Goldman Sachs and JPMorgan that
strongly believe in in-person work and, despite pandemic-related disruptions, are quickly
moving back to in-person work arrangements (Barrero, Bloom, and Davis, 2021). In the

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middle, there are companies such as Google and Apple that are adopting “hybrid”
arrangements, requiring that employees work from the office for a certain percentage of time,
and allowing them to work remotely for the remainder of the time (Berger, 2022). The research
question that we tackle in this paper is: how do organizations decide whether to adopt remote
work? In other words, how do organizations decide where to situate themselves in the
spectrum from fully-remote to fully in-person work?
This is a crucial question for organizations as the decision is incredibly consequential for
employees. For example, the extent to which an organization adopts remote work can impact
employee performance, output, work satisfaction, attrition rates, and promotion rates (Bloom et
al., 2015; Choudhury et al., 2022). The decision can also impact employees’ work structure, such
as how employees interact with one another, and the extent to which employees communicate
asynchronously versus synchronously (Choudhury et al., 2020; Rhymer, 2020; Ranganathan and
Das, 2022). As well, the decision can influence employees’ work relationships, such as the trust
that they develop with their managers and the extent to which they feel a sense of belonging and
identification with their organizations (Thatcher and Zhu, 2006; Bartel, Wrzesniewski, and
Wiesenfeld, 2012). The decision of whether to adopt remote work can even impact the meaning
that workers attribute to their work (Rauch and Ansari, 2022).
Existing theory illuminates three main factors that organizations are likely to consider as
they decide whether to adopt remote work. A first factor is cost, including whether the
organization stands to benefit financially from reduced office space, or the ability to hire lowercost talent globally, for example (e.g., Becker and Steele, 1995; Kiesler and Hinds, 2001). A
second factor is the nature of work, including whether jobs in the organization are amenable to
remote work and the extent to which there is supportive technology infrastructure for remote

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work (e.g., Cascio, 2000; Orlikowski and Barley, 2001). And a third factor is perceptions of
remote work, including whether workers exhibit strong optimism for remote work, or instead
associate negative perceptions with remote work (Olson, 1988; Kurland and Egan, 1999).
In this paper, we study an organization that was positioned to reap economic benefits
from adopting remote work, where the work was amenable to remote work for a large portion of
the workforce and supporting technology was available, and where there was significant
enthusiasm and minimal stigma towards the idea of remote work. And yet, the organization
decided to very minimally adopt remote work, with only 3% of the workers being fully remote
and 30% of the workforce having hybrid work arrangements, despite approximately 50% of
workers wanting to be remote, and the remaining majority wanting to adopt hybrid work
arrangements. This contrast suggests that there are likely to be other factors at play influencing
the extent of remote work adoption by organizations.
To develop new theory in service of unpacking the aforementioned puzzle, we draw on
a 16-month ethnography of an organization deciding whether to adopt remote work. We were
able to observe real-time how this organization approached its remote work adoption decision.
Our data reveal one important organizational process—status contests—that drove the decision
to minimally adopt remote work. In particular, we found that high-status actors employed three
tools from their status toolkit—using abstract knowledge, accessing and allocating resources,
and first-mover actions—to limit their organization’s adoption of remote work. In developing
this theory, we also engage with the sociological literature on classification systems (Bowker,
Timmermans, and Star, 1996; Bowker and Star, 1999), because classifying workers into remote,
hybrid and in-person work arrangements is at the heart of the remote work adoption decision.
This paper makes two important contributions to the study of remote work. First, we

4

highlight a novel organizational process of status contests driving remote work adoption that
has perhaps gone unnoticed in prior research due to literature’s narrower focus on decision
making at the team and individual levels. Second, we highlight how remote work adoption
decisions can become a site for status contests with the potential to widen the gap between highand low-status actors in organizations and thereby perpetuate inequality. We also contribute to
the literature on the sociology of classification by uncovering the more general concept of status
toolkits and highlighting the specific tools that high-status actors can employ to drive
classification even beyond the remote work context. Our findings can thus help illuminate how
organizations make decisions regarding adopting other worker classifications related to the
“future of work” as well, such as gig-worker and essential worker classifications.

REMOTE WORK ADOPTION IN ORGANIZATIONS
Over the course of history, several different state, national, and global events and trends
have galvanized organizations to adopt remote work.1 For example, in the 1970s when
Organization of Petroleum Exporting Countries (OPEC) enacted an embargo that cut oil exports
to the United States and spurred a need for energy conservation, organizations began to adopt
remote work to meet this external mandate (Avery and Zabel, 2001). Then, after the Americans
with Disabilities Act was passed in 1990, companies began to adopt remote work so that they
could hire individuals who were “mobility impaired” in an effort to better comply with the Act
(Stone and Colella, 1996). As states and countries have issued mandates to reduce air pollution,
organizations have also developed extensive remote work programs (Betts, 1994; Kurland and

1

Amid considerable ambiguity in the definition of “remote work” in the literature and in practice, we define remote
work broadly as “work performed away from a central work site” (Olson and Primps, 1984: 98). This definition
encompasses terms such as “telecommute,” “telework,” “distributed work,” “virtual work,” and “hybrid work.”

5

Bailey, 1999). For example, after the Clean Air Act was enacted and threatened Atlanta’s ability
to secure federal funding for city highways, the Atlanta Chamber of Commerce urged local
companies to reduce the number of employees commuting to downtown Atlanta, which drove
greater adoption of remote work (Siha and Monroe, 2006). More recently, the COVID-19
pandemic has accelerated the rise of remote work and resulted in most organizations reevaluating whether to adopt remote work (Barrero, Bloom, and Davis, 2021).
Prior work has revealed three primary factors that influence whether an organization
adopts remote work. The first factor relates to costs savings (e.g., Becker and Steele, 1995).
Organizations stand to realize cost savings as a result of adopting more remote work, especially
in light of rising real estate costs (Baruch, 2001; Narayanan et al., 2017; Choudhury, Foroughi,
Larson, 2020). For example, Rank Xerox adopted remote work largely in an effort to cut
expenses associated with its London office facilities (Daniels, Lamond, and Standen, 2001).
Organizations may capitalize on cost savings associated with remote work during mergers and
acquisitions, wherein the high expense of moving employees to a central headquarters may not
be economical (Hinds and Kiesler, 2002). As well, organizations may opt to adopt remote work
due to the cost savings associated with human capital and, for example, being able to tap into
lower-cost labor supplies in developing countries (Hinds and Kiesler, 2002). Some statistics
suggest that cost savings can be significant. IBM, for example, has saved 40 to 60% per site
annually by eliminating offices for all employees, with the exception of those who need to come
to site (Cascio, 2000).
Second, organizations may decide to adopt remote work on account of the nature of work
and technology infrastructure. For example, specific jobs (such as customer service) may be
performed more productively remotely, which can spur organizations to adopt remote work

6

(Olson, 1988). Andersen Consulting found that its consultants spent 25% more time face-to-face
with customers when they did not have permanent offices (Cascio, 2000). In other cases,
organizations may adopt remote work because a job can be performed more effectively when it
is conducted around-the-clock outside of non-traditional work hours, such as through 24-hour
customer support or 24-hour product development (Gordon, 1988; Roitz and Jackson, 2006). As
well, organizations might adopt remote work to enhance product distribution. For example, LM
Ericsson decided to adopt remote product development teams, located across multiple different
continents, so that they could collaborate on actual designs “on the ground” where products were
being distributed (Hinds and Kiesler, 2001).
Yet some jobs may be less amenable to remote work and this may limit the amount of
remote work that an organization adopts. For example, when work is not decomposable and
predictable, it is less likely to be amenable to remote work (e.g., Olszewski and Mokhtarian,
1994, Guimaraes and Dallow, 1999). Work is also less conducive to remote work when it
involves significant face-to-face contact with colleagues (Duxbury and Neufeld, 1999), and
when it demands on-site access to special equipment or materials (Fitzer, 1997). Additionally,
work may not be amenable to remote work due to a lack of technology infrastructure and
equipment. As Orlikowski and Barley (2001: 157) note, “sheer technical feasibility is usually
seen as the most significant constraint on the spread of telecommuting.”
Third, organizations may decide whether to adopt remote work as a result of different
perceptions of remote work, either positive or negative. On one hand, there might be strong
optimism around remote work. When prospective employees want to adopt remote work, an
organization’s decision to adopt significant remote work can aid recruiting efforts (Earle, 2003;
Offstein, Morwick, and Koskinen, 2010), and also enable organizations to hire from any location

7

(Allen, Golden, and Shockley, 2015). By adopting remote work, organizations may also be able
to fulfill the desires of parents and other workers who prefer, or for whom it is only feasible, to
work from home (Duxbury, Higgins, and Neufeld, 1998; Orlikowski and Barley, 2001). Remote
work can help organizations fulfill workers’ interest in achieving greater work-life balance
(Maruyama and Hopkinson, 2009; Sullivan, 2012), reduce or eliminate commute time (Baruch
and Nicholson, 1997; Bloom et al., 2015), or to respond to workers’ desire to realize productivity
gains (Bloom et al., 2015; Choudhury et al., 2021).
On the other hand, individuals might have negative perceptions of remote work and fall
prey to stigmas such as those related to “flexibility biases” (Munsch, Ridgeway, and Williams,
2014), which can limit organizational adoption of remote work. Organizations may hesitate to
embrace remote work if they perceive remote workers to be less committed to their organizations
(McDonald, Bradley, and Brown, 2008). This is especially likely if organizational leaders are
inclined to use “face time” as a “de facto measurement of productivity and commitment”
(Gajendran, Harrison, and Delaney-Klinger, 2015: 354). In this environment, remote workers’
lack of face time may lead organizational leaders to perceive them as less dependable and less
committed. Consider the sentiments of business magnate, Jack Welch:
Companies rarely promote people into leadership roles who haven’t been consistently
seen… People who get promoted…[are] present and accounted for. And their presence
says: Work is my top priority. I’m committed to this company. I want to lead. And I can.
(Welch and Welch, 2007: 92).
As Kurland and Egan (1999) explain, managers’ negative perceptions about remote work may
also relate to control. Managers may believe that it is more difficult to control workers and
coordinate their work when work happens remotely (e.g., Kurland and Egan, 1999; Cascio,
2000). As well, managers might be unwilling to overcome their past approach of rewarding
workers based on performance, rather than physical presence. Mayo et al. (2009) found that

8

managers’ willingness to reward workers based on performance, rather than on physical
presence, can be an important factor in the adoption of remote work policies. Ultimately,
managers may not agree on the value of remote work and may be reluctant to embrace flexibility
(Tomaskovic-Devey and Risman, 1993; Kurland and Egan, 1999; Bailey and Kurland, 2002;
Bailyn, 2006).
In this paper, we studied an organization that prior literature would predict would be
likely to embrace remote work. The organization was positioned to reap economic benefits from
adopting remote work, the nature of work for a large portion of the workforce was amenable to
remote work and supporting technology was available, and there was significant enthusiasm and
minimal stigma towards the idea of remote work after the pandemic had “jolted” the organization
out of inertia. And yet, the organization decided to very minimally adopt remote work, with only
3% of the workers being fully remote and 30% of the workforce having hybrid work
arrangements. This contrast indicates that there may be additional factors that influence an
organization’s decision to adopt remote work.
In particular, most research detailing how organizations decide to adopt remote work
focuses on the team and individual levels, rather than the organizational level, thus perhaps
overlooking broader organizational processes that might be influencing the adoption of remote
work. To date, the decision making process to adopt remote work at the organizational level has
not been studied in sufficient depth, likely because, prior to the pandemic, organizations did not
support much remote work and the decision to adopt remote work was not often salient at the
organizational level. Thus, middle managers and supervisors have more often made
determinations about whether to support remote work (Gordon and Kelly, 1986; Katz, 1987;
Christensen, 1992; Fitzer, 1997; Hopkins, 2005; Beham, Baierl, and Poelmans, 2015). For

9

example, prior work has shown how managers may “dole” out remote work possibilities as
rewards to high-performing workers, or as “quid pro quo[s], in return for superior performance”
(Kelly and Kalev, 2006; Kelly and Moen, 2007: 490).
In contrast, our 16-month organizational ethnography is able to shed light on broader
organizational processes that could influence remote work adoption. Indeed, a long-standing
sociological literature on classification—with remote work ultimately being a classification
problem—has highlighted that classification systems are the result of organizational processes
(Bowker, Timmermans, and Star, 1996; Bowker and Star, 1999). Organizations must decide
which workers to “allocate” to the remote work “category” and which ones to allocate to other
categories such as “on-site workers.” Prior research has shown how classification systems can be
manipulated by organizational actors, and also how they can result in inequalities (Bowker and
Star, 1999). Using this insight that remote work is a classification system, we draw on the
sociology of classification to shed light on our empirical puzzle and develop new theory.
The Sociology of Classification Systems
Classification systems are ubiquitous in organizations. We follow Bowker and Star
(1999: 10) in defining classification systems as “[sets] of categories into which things are
separated and divided to create a form of knowledge production.” This definition encompasses
both the formal classification structure, as well as the knowledge production and social processes
through which classifications are made. Classification systems are ubiquitous in organizations
because they have high utility, as they are imbued with “ideals of rationality” and can enable fast
and simple ways to differentiate among actors and entities in seemingly objective and unbiased
ways (Espeland and Stevens, 2008: 432; Dobbin, Schrage, Kalev, 2015; Rivera and Tilcsik,
2019). Organizations use classification systems to classify workers, such as whether they are

10

part-time or full-time, or whether they are employees or “independent contractors.”
Classification systems impact workers’ opportunities for advancement, how they are perceived
by others, and how included they feel in their organizations (e.g., Katz and Kahn, 1978; Morrow,
McElroy, and Elliott, 1994; Allen and Russell, 1999).
Scholars have argued that classification systems are socially constructed (e.g.,
Pescosolido and Mendelsohn, 1986; Bowker and Star, 1999; Strand, 2011; Garsten and
Jacobsson, 2013). Classification systems may, on the surface, appear to advance functional aims
of legitimacy, practicality, and control, but, in actuality, may be shaped by different actors’
strategic moves. Bourdieu (1984: 477) wrote that “classificatory systems are…the stake of
struggles between the groups they characterize and counterpose, who fight over them while
striving to turn them to their advantage.” Far from advancing functional aims, classification
systems may be created by individuals in ways that align with their specific viewpoints and
vested interests. As Bowker and Star (1999: 50) described, the builders of classification systems
achieve “quiet victories” in “inscribing their politics into the systems.” Bourdieu (2019: 73)
notes that the creation of classification systems is imbued with “classificatory struggles,” and
these struggles are ultimately about power.
As Bourdieu and Boltanski (1981: 149) note, organizational classifications such as
occupation or salary-scale classifications are “at every moment produced by…power relations.”
Importantly, organizations can manipulate classification systems by infusing certain biases and
preferences into the systems and, thus, contribute directly to inequality. For example, amid the
rise of the gig economy, organizations have been accused of classifying—or misclassifying—
workers as “independent contractors” as a cost-cutting tool so that they can allocate fewer

11

resources—including wages, job security, and benefits—to their workers, thereby introducing
significant inequalities into their organizations (Moran, 2009; Hill, 2015; Clark, 2021).
Bourdieu and other scholars help us understand that classification systems are imbued
with social dynamics, but we do not understand how the process of classification unfolds, and
with what consequences for inequality. In this paper, we unpack the process through which one
scientific organization that we studied decided whether to adopt a remote work classification. In
particular, we found that, over time, this classification became a site for status contests and in
particular, high-status actors achieved “victories” in influencing the classification system to align
with their interests (Bowker and Star, 1999: 50). We further found that high-status actors
employed three tools from their status toolkit—using abstract knowledge, accessing and
allocating resources, and first-mover actions—to drive the decision process in ways that
perpetuated inequality at an organizational level. We expect that our process model of how highstatus actors influence the creation of a remote work classification system and, in turn, whether
remote work is adopted by their organization will be important for explaining why organizations
have varying adoption levels of remote work, as well as for explaining how other worker
classification processes related to the “future of work” (such as contractor, gig worker, and
essential worker classification systems) can perpetuate inequality in organizations.

SETTING
Our setting is Particle (a pseudonym), a scientific organization located in the Bay Area of
California. Scientists at Particle work to produce world-renowned research. This research spans
many applications, including developing sustainable energy sources, developing medications for
HIV and even COVID-19, and developing new materials to produce computer chips. At the time

12

of our observations, the lab employed more than 1,500 people. When our observations began,
Particle was grappling with the decision of whether to adopt remote work at an organizational
level. Our initial access to Particle was through the Director of Strategic Planning, a senior
management team (SMT) member. The Director saw the shift to remote work incited by the
COVID-19 pandemic as an opportunity for Particle to leverage remote and hybrid work to
realize new opportunities such as accessing new global talent pools, and wanted to establish
practices and policies for hybrid and remote work after the pandemic. Shortly after our
observations began, the Director created a task force of Particle employees, including himself, to
be part of a “future of work” taskforce, which aimed to determine how Particle should adapt its
remote work posture and policies moving forward, including the extent to which it should adopt
remote work, and how it should think about developing a remote work classification system.
Our observations spanned from July 2020 to October 2021 when we became participantobservers in the future of work taskforce. From July to November 2020, we collected baseline
data, observed meetings of several different occupational groups, interviewed various
employees, and participated in meetings, including those attended by senior executives for whom
we prepared updates based on our observations. During these initial months of our observations,
we spent approximately 30 hours per week “on-site” as participant observers. From December
2020 to September 2021, we collected more extensive data. During this time period, we spent
approximately 50 hours per week “on-site.” We were asked to join SMT meetings, working
group meetings where policies were formally reviewed and changed, and became active across
the lab, supporting many different groups’ initiatives. For example, we supported the
administration of numerous surveys, including an extensive network survey within one
department, helped develop training material for managers, helped vet different remote work

13

technologies, assisted in setting up new processes, and helped draft and edit employee memos.
While we were active participants in the field, we were careful to make sure that our own
opinions about remote work were not voiced to influence remote work decisions. From
September 2021 to October 2021, we concluded our observations and prepared our final reports
and recommendations, which involved approximately 15 hours per week on-site, on average.

Motivations for considering remote work
Particle’s decision making related to whether to adopt remote work was, in part, driven
by the factors outlined in prior literature: cost savings, the nature of work (including whether
jobs in the organization are amenable to remote work and the extent to which there was
supportive technology infrastructure for remote work), and perceptions of remote work. Based
on these factors alone, Particle was rather bullish about remote work and this was reflected in its
establishment of the future of work taskforce, which was specifically aimed to help Particle
decide how to most effectively adopt remote work.
In terms of cost savings, although the SMT members explicitly said that their decision
making was not primarily driven by cost, cost savings did play a role on several occasions. For
example, SMT 14 described how remote work was “expected to reduce costs for Particle.” As
another example, in one meeting, the CIO (SMT 19) described:
If left to my own devices, my job, from an IT perspective is to lower the cost of the
technology burden as low as I possibly can, so as to free up…as much resources…for the
Science Mission—do what I can as efficiently as possible. And so, in my mind, flexible
work is a godsend because I can hire web developers and ERP admins from Idaho and
Mississippi, and Kansas, and I can lower my staff costs tremendously.
Cost savings were also implicit in the strong desire to more effectively use space. Particle’s
executives had come up with a list of eight “guiding principles” to inform its decision making

14

around remote work. The principle of “maximize effective use of space” underscored the
benefits of leveraging remote work to promote more effective use of space, which would likely
lead to cost savings.
Second, much of Particle’s work could effectively be conducted remotely. For example,
SMT 19 had determined that 53% of positions in his divisions could be conducted fully remote,
and 29% of positions only needed periodic on-site presence. Many scientific roles could also be
performed remotely, or with minimal on-site presence. SMT 10 had already been running an
entire team fully remotely at a scientific research organization in Europe; the lab had invested in
new video conferencing and other technologies to support remote work. SMT 7 outlined how his
divisions had been “recently augmented by [a] new suite of tools, including 'cyborg headsets',
mobile robots, ‘NoMachine’ controls, etc.” and how these technologies “have demonstrated a
high level of functionality” for hybrid work.
Third, there was significant enthusiasm for remote work and minimal associated stigma.
Throughout our observations, including at the end of our observations, approximately 50 percent
of workers had wanted to be fully remote given the nature of their jobs, with the majority of the
remaining workers wanting to be “hybrid.” At the height of the pandemic, the vast majority of
Particle’s workforce had needed to adopt remote work, so nearly everyone had developed a
“taste” of remote work. There was also widespread recognition that Particle had been productive
during the pandemic. There was enthusiasm around the opportunities to improve diversity, as
underscored by the guiding principle for the future of work taskforce of “Stay true to our values
and recognize diversity, equity and inclusion.” There was also a commitment to developing
manager training aimed at minimizing resistance to remote work, as evidenced by the guiding
principle of “Develop our managers to be able to effectively lead flexible/distributed work

15

organizations.” As well, the principle of “Monitor, assess and continuously improve” suggested a
commitment to continual improvement and avoiding inertia. Although there were concerns about
how scientists’ sense of belonging would be negatively impacted by adopting significant remote
work, there was minimal stigma associated with remote work throughout our observations.
In the end, despite the fact that Particle was positioned to reap cost savings from adopting
remote work, that jobs were amenable to remote work for much of the workforce and supporting
technology was available, and there was significant enthusiasm towards remote work, the
organization decided to very minimally adopt remote work. In the end, only 3% of the workers
ended up being fully remote, while 30% of the workforce adopted hybrid work arrangements,
despite roughly half of workers wanting to be remote, and the remaining majority wanting to
adopt hybrid arrangements. Our findings explore what other factors might be at play in
influencing the minimal extent of remote work adoption.

Analytic approach
We inductively analyzed our data through multiple stages. We followed a grounded
theory approach when analyzing our data (Glaser and Strauss, 1967; Charmaz, 2014) and coded
our data in NVivo. In our very first weeks of observations, we started to recognize that the status
moves of SMT members were important and influential. As we wrote initial memos describing
our early findings, we noted how high-status members influenced decision making and
conversations related to remote work throughout various interactions, including team meetings,
SMT meetings, and presentations to their teams. We theorized how various status moves
influenced remote work adoption decisions and wrote several memos describing this. Our initial
round of coding involved coding various status moves that each SMT member made, such as
“urging others of the need to revert back to traditional forms of working for the greater good of
16

the lab.” These status moves were especially prevalent early on in our observations during a twoday SMT retreat that we observed. We coded each SMT member’s statements during this retreat
(including as part of rich breakout rooms conducted via Zoom) and began to see patterns among
high- and low-status actors. It was during this retreat that we first recognized scientific SMT
members’ use of abstract scientific knowledge to influence conversations and decision making.
Our second round of coding involved grouping status moves into different second-order
codes. For example, the codes “emphasizing that the lab is very heterogenous” and “not wanting
to put stress into the system” were aggregated into the second-order category, “comparing
change to a science process or phenomenon.” Throughout our first and second rounds of coding,
we began to explore the concept of “framing contests” and we iterated between our data and
relevant literature (e.g., Kaplan, 2008). Yet, as our observations went on and we observed how
high-status actors influenced others through their actions and behaviors, we began to realize that
what we were observing was not limited to framing. We began to explore the concept of status
contests to encompass not only the cognitive influences of high-status actors (e.g., through the
use of abstract knowledge), but also the behavioral ones as well. We reflected on Swidler’s
(1986) conceptualization of “cultural toolkit” and Kellogg’s (2011) conceptualization of
“political toolkit” as we explored how status toolkits were being employed.
We engaged in a third round of coding, which focused on coding all the different
resources (e.g., office space, equipment, and technology) that were enacted by the SMT members
over the course of our observations, as well as the specific change strategies adopted by each
directorate (e.g., “moving prematurely back to site”). We again aggregated first-order codes
(e.g., “wanting to take best advantage of the space pilot”) into second-order codes (“creating
workspaces for more effective collaboration”). We ultimately converged on three higher-order

17

categories: the use of abstract knowledge, accessing and allocating resources, and making firstmover actions. As we wrote additional memos, we realized that these were the main tools that
high-status actors employed as part of their status toolkit to influence the classification system.
At this point, we began to sketch an initial process model for how high-status actors’ status
moves influenced remote work adoption.
While our initial rounds of coding were focused on understanding status moves along the
scientific versus non-scientific status dimension, as we engaged in in-depth coding, we
recognized that there were two important status dimensions: the scientific SMT member versus
non-scientific SMT member status divide, which was our initial focus, and an additional
important status divide—executive status—that was at play in influencing the remote work
adoption decision. We engaged in additional rounds of coding focused on this second status
dimension and realized that the high-status executives used similar tools to those of the scientific
SMT members, although they enacted them differently. We then began to formalize our process
model (Figure 2) and the process of how each tool was used by high-status actors as they
engaged in status contests and emerged as “winners” by significantly influencing the (lack of)
adoption of remote work.
At the end of our observations, it became very apparent that remote work adoption
decisions had created significant inequalities in the organization. We returned to our data and
coded for instances of equality and inequality. It became clear, through this process, that, while
the organizations had prioritized equality issues at the start of our observations, this focus on
equality waned throughout our observation and, in the end, the remote work adoption decision
was riddled with inequalities that disadvantaged lower-status actors.

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FINDINGS
We begin by first describing the end state of Particle’s remote work adoption decision.
The end state of the remote work adoption decision
At the end of our observations, the remote work classification system encompassed three
types of classifications: “remote,” “hybrid,” and “on-site”. Employees who would regularly work
from Particle’s campus between two and four (inclusive) days per week would be classified as
“hybrid.” Employees who would work on-site one day per week or less would be classified as
“remote.” And those employees who would perform their work on-site five days a week would
be classified as “on-site” workers.
While the initial goal was to transition a significant percentage of the workforce to
remote and hybrid work, only about three percent of the workforce ended up being fully remote
(when we followed up six months after our observations ended, this number had modestly
increased to six percent). As SMT 13 lamented, “I would have to say I was kind of disappointed
that only 3% [of employees] would be remote. It seems like we probably had about 3% before
the pandemic.” As well, only about 30% of workers ended up being classified as hybrid workers
(many of these workers had hoped to be fully remote). As one HR professional explained to us:
A lot of those [workers classified as] hybrid… are of the opinion that we can probably do
our jobs quite nicely as remote and come on-site as needed…Us sitting in front of a
computer all day on-site makes zero sense to us….Getting that through to someone like
[SMT 18], it’s hard.
There was also minimal consistency in terms of how employees were classified into
different work arrangements, with many of the same roles classified differently across the
different directorates. As well, although the lab-wide policy guidance related to the classification
system included suggestions for which classifications (e.g., remote versus hybrid versus on-site)
would receive specific space (e.g., dedicated office space) and equipment packages (e.g.,

19

portable keyboards), SMT members differed widely in terms of how they structured resources
across different classifications.

The Role of Status Contests
When we were observing the organizational process of decision making around remote
work, we found that different actors within the organization had different preferences related to
remote work. Importantly, we noticed that these actors differed on various status dimensions.
These different preferences of high- and low-status actors created fodder for status contests
(Sutton and Hargadon, 1996). While there are many definitions and conceptualizations of status
contests in prior work (e.g., Maclay and Knipe, 1972; Sutton and Hargadon, 1996; Kaplan,
2008), we define status contests as attempts to influence others, with the aim to advance one’s
own interests, or those of the status group that one belongs to. Below, we will argue and show
how status contests played an important role in ultimately influencing the organization’s decision
to minimally adopt remote work.
Throughout our data collection, two main types of status2 dimensions were highly salient:
occupational status and executive status. Here, we provide an overview of these status
dimensions and how the groups differed in terms of their interests pertaining to remote work.
The occupational status dimension
Particle is broadly divided into several science-focused subunits that are referred to as
“mission” subunits because they are viewed as contributing directly to Particle’s scientific

2

Although we focus on occupational status and executive status in this paper, these status dimensions intersected
with demographic status characteristics. The SMT team was comprised of mostly white, older men who had had a
long tenure at Particle. Executives were also mostly white, older men.

20

mission, and several non-science-focused subunits such as “Facilities and Operations” and
“Human Resources,” that are referred to as “mission support” subunits.
Many of our respondents described the well-established occupational hierarchy at
Particle, with scientists at the top, followed by engineers, and “mission support” staff at the
bottom. As one mission support employee described:
The organization is a very hierarchical system with Particle scientists, then engineers,
then support staff…It feels very rigid, kind of a pecking order…Scientists are more
important than engineers, and engineers are more important than the support side of the
house….It’s unfortunate….this almost caste-like mentality.
The status hierarchy was reinforced by the funding structure at the lab—money flowed to the
mission directorates that were, in turn, “taxed” and that tax was allocated to the mission support
functions. One leader explained bluntly how the hierarchy was inherent to the funding structure:
“Mission Support is a tax on Particle’s [scientific] research dollars.” Both mission and mission
support employees were aware that the mission saw support as an “administrative burden.” Not
only did they erode the funding allocated to the mission through the administrative “tax,” but the
nature of their work also meant that they were responsible for ensuring compliance. As one
mission support employee put it:
Scientists want to put all the money in science, and want to be left alone to do their
research. And mission support people need to make sure it’s being done legally, and all
the…rules, and we cost money. And so scientists have to see some of their funding go to
indirect costs to support us. And it’s a natural tension that happens...one is the enforcer
and one does what they want to do.
The scientific SMT members did not want significant changes to employees’ on-site
presence and did not want to support significant remote work. They viewed on-site work as core
to developing cutting-edge science and believed that employees produced the best science and
felt a stronger sense of belonging when they engaged in significant on-site work. In contrast,
non-scientific SMT members were much stronger proponents of remote work. They were more
21

directly competing with companies in the Bay Area for talent as compared to the science
directorates. For instance, non-science SMT 19 described remote work as a “godsend” due to the
potential to hire IT staff from outside the Bay Area’s competitive talent market for software
developers.
The executive status dimension
The second status dimension that was salient in the organization in terms of influencing
the remote work decision was executive status, based on the formal hierarchy and as depicted on
organizational charts. The executive hierarchy at Particle was extremely structured and visible.
The lab-wide organizational chart, as well as each directorate’s organizational chart, was
publicly available on Particle’s website. In our interviews with employees, they often described
the well-entrenched hierarchy at Particle. As one employee described:
Hierarchy is very important in terms of how you get work done, or who, like who
communicates up, right? So it’s very hierarchical. And you have to follow the chain of
command…That’s just how Particle is structured.
At the top of the executive hierarchy were senior management team (SMT) members. When our
observations began, Particle had 16 SMT members who were formally at the top of the hierarchy
(one additional SMT position was added partway through our observations). Some employees
described their hesitation to speak up, or express concerns, to SMT members due to status
differences on the formal hierarchy. A main reason why we had such extensive access to our
field site was that our point of contact was the Director of Strategic Planning (SMT 3), who had
among the highest executive status at Particle as an SMT member. In our interviews with various
employees, when we mentioned that SMT 3 was endorsing our efforts, our respondents would
often become more engaged and willing to participate in interviews or other endeavors. Division
directors and department heads were below SMTs on the leadership hierarchy and were often

22

emically referred to as “leadership.” Division directors and department heads reported directly to
SMT members and were viewed as having high status. SMT members often delegated decisions
related to remote work to them and often consulted them in their own decision making. We
consider the SMT members, division directors, and department heads as high-status executives
for the purpose of our paper.
Managers and supervisors were on the next rungs of the leadership hierarchy, below the
division directors and department heads. Managers were not typically viewed as having high
status. Some SMT members would make jokes about how incompetent managers were and that
they often did not follow rules and guidance. In one example, the SMT members debated
whether all managers should be provided with a list of which of their employees were vaccinated
so that they could enforce compliance with social distancing rules, which differed depending on
employees’ vaccination status. The SMT members were unsure as to whether, even with training,
they could trust managers to avoid inappropriately chiding unvaccinated employees. As SMT18
explained:
Do we—I hate to use this word—trust the skills of our supervisors to have this
conversation as opposed to entering into the area of “why aren’t you vax, why don’t you
go get vax, you’re making my life difficult?”...I do fear it.
At the bottom of the executive hierarchy were employees. Approximately 74 percent of
Particle’s workforce were non-manager employees. Although employees typically had lower
status than their supervisors and managers, we classify employees, supervisors, and managers as
lower-status non-executives for the purpose of this paper as this was the primary dimension of
contrast along the executive status dimension.
As in the case of the other status dimension, executives and non-executives had different
objectives for the classification system. First, in general, executives were much less supportive of

23

fully remote work arrangements than their staff. None of the SMT members and, to our
knowledge, only one of the dozens of division directors and department heads intended to be
fully remote. Even within the non-science directorates where leaders wanted more offsite work
opportunities, they still typically wanted most employees to have some regular on-site presence
because they wanted to physically see them and hold them accountable for their work. In
contrast, a significant number of non-executive employees wanted to be able to adopt fullyremote classifications, which would enable them to move out of the Bay Area and avoid the
steep cost of living that was much more salient to them than to their higher-paid leaders. A
survey conducted among 106 employees in one non-scientific directorate found that 68% of
employees “strongly agreed” that they would be interested in working remotely and only coming
to site occasionally.

Status Toolkit Used by High-Status Actors to Influence Remote Work Adoption
The high-status actors drew on their status toolkit to influence Particle’s remote work
adoption decision. Our use of status toolkits is similar to the concepts of “cultural toolkits”
(Swidler, 1986) and “political toolkits” (Kellogg, 2011) used in past work. High-status actors
used tools from their status toolkit in varying configurations to “construct their action in
particular situations” (Kellogg, 2011: 483) and influence the remote work adoption decision. We
found that high-status actors’ status toolkit comprised three primary tools: using abstract
knowledge, accessing and allocating resources, and taking first-mover actions. We describe each
of these three tools, how they were employed by organizational actors along each status
dimension, and how they shaped Particle’s remote work adoption decision.
Use of abstract knowledge

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Use of abstract (scientific) knowledge by scientific SMT members. The first tool that the
scientific SMT members employed to influence the classification system was the use of abstract
knowledge to shape decision making and communication about the remote work decision, either
verbally, or via written communication. Scientific SMT members often framed decisions related
to remote work as involving high levels of complexity and frequently accused lower-status SMT
members of overlooking the complexity of what was involved in making decisions about
adopting remote work. The scientific SMT members often drew on abstract concepts from their
scientific occupations to discursively frame the change process. For example, they often
compared the change process to an experiment, or a complex system. Given that scientific SMT
members wanted to limit remote work adoption, science SMT 7 warned against “inject[ing] a lot
of entropy into the system,” by allowing too much flexibility in terms of employees being able to
work remotely. Often, science leadership emphasized complexity in order to convey the
importance of moving slowly, which stalled decision making and built inertia against remote
work adoption. Science SMT 8 explained:
Normally, you know, in a complex system like this, you'd like to do the experiment
cautiously, fully… there isn’t intrinsically an extreme urgency in this. And it’s really a lot
better to do it gradually and not go back. Because if people thought this was the way
things were gonna work, and they move [to live somewhere else], and all of a sudden you
tell them that we're going back, it’s not easy.
When this abstract knowledge was infused into conversation, it often stalled decision
making. Non-science SMT members described wanting to “bring the science along” and help
them see the value of adopting remote work, but they struggled to insert themselves into the
conversation around the complexity associated with the decision, and feared that if they were to
adopt significant remote work, it could be “pulled back.” As non-science SMT 15 said:
To [non-science SMT 19’s] point, in the absence of an overarching lab statement, it can
be hard to go strong one way or another…And so in the absence of that, I feel like I don’t

25

want it to get to a stage where you know we get six months down the road and [science
SMT 2] is not happy because half of [mission support] isn’t on-site.
Scientific SMT members often employed the scientific term “heterogeneity” as part of
their efforts to employ their abstract knowledge in discussions, typically to describe the
variegated nature of the work conducted at the lab and, especially, the variegated nature of the
types of science conducted at the lab. On numerous occasions, the scientific SMT members used
this word, or a variant, to emphasize the infeasibility of adopting remote work at a lab level. As
science SMT 7 explained:
This [decision making about remote work] is inherently something that cuts across every
aspect of our organization and the way we work. The process we have to go through
needs to ensure we carry that complexity and carry the inherent heterogeneity as well.
The thing I fear is that we’re too reductionist about this.
Non-scientific SMT members were seemingly faced with a “no-win” situation as they
tried to offer solutions that represented the heterogeneity of the science organizations and yet
were consistent across the lab. The non-scientific SMT members recognized the scientific SMT
members’ propensity to employ abstract knowledge in decision making and communication.
Non-science SMT 4 had created a game with non-science SMT 15 that he likened to “buzzword
bingo,” wherein they tallied how many times the scientific SMT members used the word
“heterogeneous.” Although this was comical at times, it was more often frustrating as it often
stalled active steps towards remote work adoption. The non-scientific SMT members often tried
to reduce the added obfuscation and complexity but these were only minimally effective. In one
meeting, non-science SMT 19 lamented in frustration, “I feel that the steps are pretty clear of
what we need to do and [SMT 4] has laid this out graphically quite nicely. I feel that we’re
overcomplicating it.”
The scientific SMT members added abstract knowledge into decision making and
communication as a key tool during a two-day SMT “retreat” that we attended that was aimed at
26

making important decisions related to the lab’s remote work policy and strategy moving forward.
During the retreat, SMT members were asked to submit questions that were top of mind for them
regarding remote work and the intent was to prioritize them so that decision making could be
more targeted and streamlined. Many of the questions that the SMT members submitted would
determine the extent of remote work adoption, such as: “How we would determine salary
differentials for staff that want to do full-time remote work?” The questions were then grouped
into categories and, in a debrief session, it was suggested that the SMT members vote on which
category they should prioritize in terms of their decision making. Several of the scientific SMT
resisted this attempt to prioritize and criticized it for being “too reductionist” as all categories
needed to be considered in tandem. The categories were not prioritized and, at the end of our
observations more than six months later, several of the key questions that SMT members had
submitted remained unanswered or ambiguously answered.
In this way, the use of abstract knowledge and scientific jargon stalled decision making
and inhibited the adoption of remote work. Even though non-scientific SMT members wanted to
support remote work, they did not have a lab-wide approach that they could latch on to and
feared that any local changes might be retracted down the road. Non-science SMT 19 explained:
“I don’t think I can [start allowing full-time remote work], because I don't know what the lab
strategy is, in general.” In the end, abstract knowledge influenced greater on-site work and
prevented meaningful changes to remote work presence.
Use of abstract managerial knowledge by executives. Executives also employed abstract
managerial knowledge in decision making and communication and this influenced the adoption
of remote work. Even the non-scientific SMT members—who often tried to resist the high-status
scientific SMT members’ use of abstract scientific knowledge—ironically used abstract

27

managerial knowledge when developing communications to be disseminated to their own
employees. One way that executives used abstract managerial knowledge to influence the remote
work adoption decision was through developing and then influencing different decision
structures (such as matrices, decision trees, and templates). The first salient decision structure
that the executives created and influenced was a two-by-two matrix where SMT members
mapped out specific roles according to whether they preferred them to be 100% onsite, hybrid, or
remote (Figure 1). All SMT members were asked to complete this two-by-two matrix in
consultation with their leadership teams for their directorate and then present it to the entire SMT
team. Executives drew on their abstract managerial knowledge to discursively frame how they
completed their two-by-twos and, in particular, the fact that they had positioned very few roles in
the upper right quadrant (remote work).
[Insert Figure 1 about here]
Executives also drew on their abstract managerial knowledge to influence how remote
work decisions were expected to be made. At the onset of the future or work taskforce creation,
there was a strong emphasis on giving employees choice throughout the change process in terms
of enabling them to adopt remote and hybrid work arrangements. The Director of HR, SMT 18,
frequently described the need for the determination of an employee’s on-site, hybrid, or remote
arrangement to be a dialogue and a two-way conversation between the employee and their
manager. As a non-executive HR professional explained, “It starts with a conversation between
the manager and the employee about what the new arrangements going to be.” Yet, over time,
executives applied abstract managerial knowledge to erode the amount of input that employees
would be able to provide. We tracked this erosion over time in the various iterations of the
remote work “handbook” and related resources that were available to all employees. In the first

28

iteration of the handbook, the hybrid and remote work determination involved consideration of
the employees’ preferences:
Determination of the appropriate work environment is based on the staff member’s
preference in conjunction with the needs of Particle…Staff will have input on preferred
work environments and flexible solutions to meet work-life balance goals, however, this
input must fit within the scope of the work and role.
In the next iteration, some of this autonomy was stripped away by executives adding
abstract managerial phrases such as “Divisions/Directorates may have additional guidance
on…final approval levels.” Then, in the next iteration, after the Directorate Work Agreement
Plans had been created, a “decision tree” was created by some of the executives as a supplement
to the remote work guidebook. This decision tree still included some agency on the part of
employees (see the third question below), but executives infused their abstract knowledge by
saying that the decision should first revolve around the specific guidance given by each
directorate.
•
•

•

First question of decision tree: Have you received your directorate’s guidance?
Second question of decision tree: Is there guidance for your role?
Third question of decision tree: In order to fulfill Particle’s mission, can your team’s
and cross-functional teams’ operations be effectively sustained if your work is being
performed in a hybrid or fully remote work arrangement?

In the next iteration, executives reframed the decision tree to be from the perspective of
the manager, completely stripping agency from the employees:
•
•
•

First question of decision tree: Have you received your directorate’s guidance? (e.g.,
formal Work Plan).
Second question of decision tree: Is there guidance for your employee's role?
Third question of decision tree: In order to fulfill Particle’s mission, can the
employee’s team and cross-functional team operations be effectively sustained if their
work is being performed in a hybrid or fully remote work arrangement?

29

When deciding to reframe the decision tree during this iteration, executives used abstract
knowledge. For example, non-science SMT 4 drew on “guiding principles” to influence the new
structure of the decision tree:
We do need to flip the discussion. It would be nice if everyone could get everything that
they wanted, but we should frame it back in the guiding principles that we set up
originally, where the number one principle was we got to get the mission done…it starts
with, “here’s what we need you to do to get the job done,” as opposed to well, “what
would you like to do?”
Then, in the next iteration, executives decided that the decision tree should be removed entirely,
which meant that the default was for employees to have very little say in their work arrangement.
Another example of the use of managerial abstract knowledge involved the addition of
“vignettes” to the remote work handbook. These vignettes were meant to help employees
understand their likely work arrangements. As the handbook stated:
The following vignettes are provided to help managers and staff envision how a
combination of work environments and space types are leveraged in different situations.
But far from being neutral, these vignettes painted a picture that significant on-site work would
be required or encouraged. For example, the following two vignette excerpts (one for on-site
work and one for hybrid work) were included in the guidance:
On-site work:
Sree was eager to come back onsite full time. As an extrovert, being around people is
very important. Sree not only got frustrated in the solitude of the pandemic, but found
work was harder, too, since Sree’s normal mode was to pop in on people as
needed…Sree’s manager offers a flexible hybrid solution, but Sree still prefers working
100% onsite at her regular workstation. They work on building norms on the team so
Sree can get the needed answers as quickly as before, just through other channels and
they design monthly team events to feel more connected.
Hybrid work:
Jade is a theoretical physicist. Things got done at a much slower pace during the
pandemic. Jade feels that the more theorists are together, the better. Jade also loves
30

mentoring grad students. Knowing how far the pandemic set them back, Jade wants to be
onsite to help them get back on track. While Jade loved not commuting, the discussions
with other theorists also draw Jade to the office where [her directorate] created a great
collaboration space. Jade has a dedicated space as do the other theorists. Jade will work
from home when it makes sense, but for the most part Jade will be onsite.
Through such vignettes, guiding principles, decision trees and matrices, managers used
abstract managerial knowledge to influence the remote work adoption decision.
Access to and allocation of resources
Access to and allocation of resources by science SMT members. The second tool that
the scientific SMT members used from their status toolkit to influence the adoption of remote
work involved accessing and allocating resources. By accessing and then allocating resources
that they uniquely possessed as a result of their high status, science SMT members were able to
influence adoption decisions.
Scientific SMT members invested more resources to support their employees’ on-site
work and used this to rationalize bringing their employees back to site. For example, some
scientific SMT members purchased equipment to help their employees feel comfortable
returning to site. At least two scientific SMT members purchased new mice and keyboards for all
the employees in their directorates so that they would not need to share equipment. The
following interaction illustrates:
Non-SMT HR professional: Non-science SMT 19 also talked about shared keyboards
and mice—it’s not sanitary for shared workstation, to have them sharing. He’s proposing
two sets of keyboards and mice—one for home office and one is your travel kit—that’s
an expense that we need to consider.
Science SMT 7’s Deputy: The expense isn’t that much. When we went back on-site
back in May, we invested in keyboards and mice for every single person that came onsite. It wasn’t too much – the biggest expense was creating little cubbies—we would have
to put all of these items in, but we got through it. I don’t think it’s that big of a deal.

31

The scientific SMT members also had access to the financial resources to equip the
conference rooms that their employees most often used with better technology to facilitate hybrid
meetings. Scientific SMT members described being able to “self-fund” or use their influence to
ensure that their preferred conference rooms were equipped with the best technology feasible.
SMT 9 told his leadership team to let him know where they needed resources to be able to
engage in more effective hybrid work.
Scientific SMT members’ budgets also permitted them to hold more non-work-related
social events for their on-site staff. Science SMT 7’s Directorate hosted a Taco Tuesday, which
was described as a “smashing success” and an ice cream social that was specifically designed to
“entice people” back, as science SMT 7’s Deputy described. The Deputy also explained:
It took people a while…to get comfortable coming back on-site…People won't know
what they’re missing until more people come on-site, and they realize that, you know,
things are happening on-site. We did a Taco Tuesday…I thought there was only gonna be
75 people and 125 people came.
Science SMT 7 also funded a “sushi party” to celebrate the end of an experimental “run” (a
series of experiments). Two other science SMT members organized barbecues, one of whom
(science SMT 11) funded a barbecue that was held once a week so that, given social distance
protocols, every employee could attend.
Ultimately, by being able to access and allocate resources, science SMT members were
able to create in-office environments that incentivized employees to come back to site and also
rationalized their decision to encourage workers to adopt predominantly on-site work
arrangements.
Resource access and allocation by executive versus non-executive employees.
Executives also accessed and allocated resources in ways that influenced the remote work
adoption decision. The first way that they accomplished this was in the context of physical space.

32

Executives allocated resources to designing more collaborative spaces in hopes that this would
lure employees into the office. Non-science SMT 14 was eager to participate in a “pilot” office
space program in Particle’s Building Beta (a pseudonym) and wanted to allocate resources to
creating collaborative spaces that employees would want to occupy. She explained:
I was kind of thinking if Building Beta is going to be our guinea pig, there’s a kitchen
and a really nice courtyard. So how do we improve that to where it really becomes a
collaboration space? Everybody, when you invite people to your house, where do they
hang out? The kitchen counter. How do we make a kitchen counter in Building Beta?
In another example, SMT 20 explained:
I would love to see us somehow carve out a collaborative space, maybe even a bookable
collaborative space for [my directorate] as an example, if we can…because sometimes
people, right, they can’t imagine until they’re living and using it…. if we can [get out of
it a] dedicated collaboration space if you know, let’s say [one of my employees] brings in
all of his accounting team, they can go in there and work on projects.
Another way that leaders influenced the classification system involved refusing to
allocate financial resources (money) to pay for remote workers’ travel back to the lab. Particle
was legally required to pay remote workers for their travel back to site when it was required.
This meant that, by classifying workers as hybrid versus remote, executives would not be
required to pay for their employees’ travel back to the lab and, instead, employees would need to
front the travel costs themselves. As an HR employee explained, “A manager, knowing they
have to pay for travel back to the lab if they classify them as remote, might be more inclined to
classify them as hybrid.” Non-science SMT 14 explained how her unwillingness to allocate
financial resources would lead her to classify workers as “telework” (later called “hybrid”),
rather than remote. She said, “The reason you would go with telework is because my expectation
is when I want you to come to the office, I’m not paying for your travel, it’s on you.” SMT 14
went on to explain how she decided to classify one of her employees as “remote”:

33

[My employee] is a great example…he probably could have a remote work [agreement]
in Arizona. My expectation is that he is on-site on a regular basis, and I’m not paying his
travel to come.
Together, this access to, and allocation of resources, was an influential tool in executives’
toolkit for driving minimal remote work.
First-mover actions
Scientific SMT members engage in first-mover actions. The third tool that the scientific
SMT members used to influence the adoption of remote work was “first-mover” actions. These
first-mover actions involved science SMTs making decisions that pre-empted non-scientific
SMT members from making decisions of their own volition and this path dependence prevented
significant adoption of remote work.
The first way that the scientific SMT members engaged in first-mover actions was by
establishing rules dictating significant on-site presence for the roles in their directorates.
Although they did not formally have the approval of the SMT at large to set these new local
rules, their high status meant that they did not receive much pushback as they began to devise
and then implement these rules. Looking across all the roles, scientific SMT members expected
their employees to be on-site, on average, at least 75% of the time. These rules regarding on-site
presence had significant path dependence in limiting the flexibility of non-science employees,
especially those who directly served science employees as their “customers” and were formally
assessed based on the quality of their customer services. Many of the scientific employees
expected their customers from non-scientific directorates to be available on-site alongside them a
lot of the time. As one scientific leader said, “we need to be better about really forcing
people…to spend more time kind of being embedded in the domains where they're supposed to
be making an impact.” Scientific SMT members often emphasized the primacy of science and

34

implicitly and explicitly suggested that the opinions and preferences of scientific SMT members
mattered more than those of the non-scientific SMT members. As Science SMT 9 said, “I think
there needs to be that weighting of the org that is trying to get the tasks done.” Thus, remote
work determinations began to be shaped by the scientific SMT members’ swift decisions to
establish significant on-site presence, rather than the nature of the work itself. This meant that
the same or similar roles in different directorates had intertwined remote work classifications
strictly as a result of the extent to which their day-to-day work involved supporting scientific
employees as their customers.
Another way that scientific SMT members’ first-mover actions impacted the adoption of
remote work was by limiting non-scientific SMT members’ discretion over remote work
classifications. Non-science SMT members and their employees frequently described having too
little discretion over their classification due to the rules established by scientific leaders. As nonscience SMT 20 described:
As I’ve had conversations with [my] leaders, all indicate that staff want to
telecommute—come in once a month. But the other factor is what customers need and
perceive as needed. I don’t want us to get too far out of alignment…One of our
stakeholders was complaining about the lack of on-site presence from the people who
provide the services.
Non-scientific SMT members began to think in terms of not only whether specific roles could
work on-site, but also whether it was “culturally acceptable” to work offsite, or whether their
scientific customers would deem it acceptable. For example, non-science SMT 19 created a
spreadsheet with all the roles in his directorate; one column outlined the percent of on-site
presence that was needed to perform a particular job effectively, and a second column outlined a
higher percent of on-site presence that would be “culturally acceptable” for each role. Other
employees described surveying their scientific customers as a means of determining their

35

classification. One employee described wanting help in compiling such a survey. She asked:
This is my personal request for a survey … in helping me figure this part out…quite
frankly I was gonna go, “Hey, how often do you need to see my financial analysts?” or
“How often do you want to see me?”…And this is where I go, “Oh no, what's the
response going to be and am I setting myself up for a five-day-er personally by
asking?”…I also don't want to end up being here five days a week.
Ultimately, the non-scientific SMT members were limited in their ability to permit their
employees to engage in significant remote work because they recognized that their acceptable
on-site presence would be heavily influenced by the expectations of their scientific customers.
Another way that the science SMT members took first-mover actions was by physically
bringing their employees back to site. On the non-scientific side, multiple SMT members
described their frustration that the scientific SMT members had started to bring their employees
back on-site and that they had issued messaging around the importance of coming back to site,
because this messaging was trickling over to their own employees. For example, the following
interaction occurred between non-executive HR professionals who were discussing how firstmover actions by science SMT members had influenced non-science SMT members’ actions. In
this case, they observed how the HR Director had deviated from saying that employees would
have notable say in their work arrangements and that the determinations would largely be driven
by the nature of the work:
Non-executive HR professional 1: I was really surprised that she actually said, “Because
I’m on-site, you need to be on-site.” I was like, “I thought we talked about how that’s not
how it’s supposed to.”
Non-executive HR professional 2: I think she's being influenced…. I think she may be
influenced by…science SMT 2. I've heard this repeatedly from science SMT 2…They
want their people on-site so they can do drop-bys. I'm like, in my mind, I'm thinking nonscience SMT 16, if I'm Building Beta, you will never come [to see me].
As non-science SMT 18 and her direct reports began to roll out remote work training for
managers and employees, they realized that many of the science-focused SMT members had
36

already started to return to site and had already begun guiding managers on how to have
conversations with their staff regarding remote work classifications. After realizing this, the HR
professionals, led by non-science SMT 18, decided to backtrack on a lot of the training they had
developed because a lot of the training such as guidance for managers to navigate remote work
conversations had already taken place. As an HR professional explained:
I’m beginning to break it apart and modularize it so I can meet with [a science-focused
SMT member] and say, “Okay, what do your managers already know, let’s cross that off
the list and just train on what’s left.” So I just wanted to let you know that’s another little
glitch that happened…It's definitely not what everybody needs.
In the end, the HR professionals revised their training and created a checklist that would
enable SMT members to “cross off” the training that they no longer needed. This meant that
local SMT members were able to offer minimal training to their managers related to how to
support remote work, which further conveyed the message that employees were expected to have
substantial on-site presence. It also meant that each SMT member could decide how to structure
their own training. In many cases, training sessions for the scientific Directorates were shortened
from the planned two hours to one hour to account for the fact that a lot of guidance had already
been communicated and implemented locally. In the end, through first-mover actions, scientific
SMT members were able to limit the perceived acceptance of remote work within their
directorates, which resulted in limited adoption of remote work.
Executives make first-mover actions. Executives also made “first-mover” actions and
influenced the classification system through these actions. The first way they did this was by
establishing rules related to on-site coverage (i.e., when employees would need to ensure that at
least one person in their function was on-site to attend to any in-person requests). After nonscience SMT 18 decided to implement a rule that all groups in her directorate would need to
have at least one person on-site at all times, one of her employees expressed their frustration:

37

You've just cut off all these options, right? It means we have to do a two/three split [one
person on-site two days a week and one person on-site three days a week], right? So all of
a sudden a team of two and this is endemic throughout Particle….there are teams of one
or two everywhere, if we adopt that construct, that means no flexibility.
Sometimes coverage rules were driven by executives wanting to physically “see” their staff onsite. This led to frustration as employees did not think it was fair that their classification was
driven by leadership preferences. The following interaction illustrates:
HR professional (non-science non-SMT non-manager): I tried mentioning to [SMT
18] like “you know, in the past, nobody really came by, I think two days a week is, you
know more than enough”…but [SMT 18] was saying it was more for her, like when she
likes calling people in and there’s stuff for them to do.
HR professional (non-science non-SMT manager): You see, that’s the executive
trickle down. Yeah, and I’m like on the off chance you want to talk to us, you’re gonna
make us come to site, that makes zero sense
Another way that executives used first-mover actions involved adding ambiguity and
incompleteness to formal guidance around remote work, often in attempts to preempt pushback
from employees. A key way that executives did this related to the creation of a grievance policy
for employees to voice their concerns about their remote work or hybrid work classifications.
Initially, the non-SMT HR professionals included a clause in the remote work training guidebook
for managers and employees that described how disagreements related to remote work
classifications would be handled. Non-science SMT 18 decided to delete this section from the
guidebook, which created frustration among her employees as it was a decision rooted in not
wanting pushback. The following interaction unfolded:
Non-SMT professional: Did she give a reason [for deleting it]?
Non-SMT professional: [Non-science SMT 18] did not want, because it’s employeefacing, meaning they have access to it, she did not want employees to immediately go,
“Oh I can dispute this”, which, in my mind is the wrong approach...It's a fear-based
decision, and I don't like fear-based decisions.

38

Even though a grievance policy did exist, by removing this clause, it made it unclear to
employees that such a policy existed, which meant that employees were more likely to be in the
dark about resources that were available to them should they feel like their requests for more
flexible work arrangements were not fairly considered. This approach to being vague was
increasingly adopted as our observations went on. In helping to draft a whitepaper explaining
Particle’s remote work guidance, non-science SMT 18 urged executives to keep the language
vague:
I think the best thing that we can do is to help all the senior team members to use
statements that are very—I hate to say this—vague, so that there’s a little bit of an out.
In the end, through executives’ first-mover actions, employees were limited in their
ability to adopt hybrid and remote work arrangements or push back against others classifying
them as having significant on-site presence. This manifested in much less adoption of remote
work at Particle than had been anticipated.

A Process Model of Remote Work Adoption
We now theorize a process model that illuminates the organizational process of status
contests that we found to be salient in influencing remote work adoption. Figure 2 visually
depicts our process model. Overall, the process model shows how high-status actors use tools
from their status toolkit to influence the extent of remote work adoption. The process begins with
two groups of actors (high-status and low-status). High-status actors have access to a status
toolkit, which their lower-status counterparts lack access to. In our study, high-status actors drew
on three main tools as part of their status toolkit.
[Insert Figure 2 about here]

39

The first tool that high-status actors drew on as part of their toolkit was the use of abstract
knowledge, including the use of scientific knowledge and the use of managerial knowledge. We
found that high-status actors’ use of abstract knowledge frequently stalled decision making and
impaired communication. Ultimately, this inhibited change and resulted in minimal remote work
adoption. The use and impact of this abstract knowledge align with the conceptualization of
abstract knowledge in the professions literature. Abbott (1988: 8) noted that abstract knowledge
is used as a form of control and that, by developing an abstract system of knowledge, professions
can generate practical techniques and also redefine the tasks and problems that underlie a system
of knowledge. The high-status actors in our study frequently used their abstract knowledge to
define the problems that were involved in the remote work adoption decision (e.g., the need to
represent the heterogeneity of the science directorates) and also the practical techniques used to
influence this decision (e.g., the use of decision trees and matrices).
The second tool that high-status actors drew on as part of their toolkit involved access to
and allocation of resources. By allocating valuable and often scarce resources, high-status actors
encouraged workers to come back to site and created environments that were conducive to onsite work and this influenced limited remote work adoption. This use of resources by high-status
actors aligns with resource dependence theory in that the actors who were able to control critical
resources (such as keyboards, mice, and money to fund on-site events) had power relative to
other actors (e.g., Pfeffer and Salancik, 2003).
The third tool that high-status actors drew on from their toolkit to influence the
classification system was first-mover actions. In making swift decisions, high-status actors
preempted many of the decisions of lower-status actors and, in turn, shaped the minimal adoption
of remote work. In part, this aligns with the concept of first mover advantage (FMA) in prior

40

management research (e.g., Suarez and Lanzolla, 2007). A key mechanism underlying FMA is
the preemption of scarce assets, which was evident in our study as well (e.g., related to the space
pilot).
Taken together, high-status actors’ use of their status toolkit shapes adoption of remote
work. In our case, the use of the tools underlying the toolkit shaped minimal adoption of remote
work, although we expect that in different organizational contexts, the use of these tools could
shape significant remote work adoption (e.g., if high-status actors allocate resources to create
supportive remote work environments for employees such as coworking spaces, home office
setups, generous travel reimbursements, and on-site bonding events). Actors used their status
toolkit to influence others, with the aim to advance their own interests and those of the status
group that they belonged to. These status contests endured throughout our observations.
Although low-status actors attempted to influence the remote work adoption decision through
various status contests, their efforts were largely unsuccessful, as represented by the dotted line
in Figure 2. In the end, high-status actors “won” and low-status actors “lost” the status contest.

Implications for Inequality
We found that the organizational process of status contests and its influence on Particle’s
remote work adoption had important implications for inequality.
First, in influencing remote work adoption to meet their needs and preferences, highstatus actors further cemented their high-status position. For example, in presenting his “hybrid
work strategy” to his directorate, SMT 7 explained his intent for his on-site approach to
“translate down the organization,” thereby cementing his high-status position. SMT 9 similarly

41

described this intended “trickle down” effect: I’m setting [rules] at the senior leadership level
and I’m expecting the teams to propagate [them] down.”
Additionally, as a result of the status contests, high-status actors’ actions ended up
marginalizing low-status actors, thereby perpetuating inequality within the organization. We
found that there were three key dimensions in which inequality was perpetuated: work schedules,
decisions of where to live, and office space. In terms of work schedules, by dictating that there
be coverage during operating hours, the high-status actors’ actions negatively impacted work
schedules for actors with lower status. SMT 18 expressed her concerns around work schedules:
In two separate areas, I have strong performers who are working remotely out of state. In
both of these areas, their roles are required to work on-site about 40-60% of the time. This
will include a rotation of providing coverage on-site amongst three people. In one of my
work teams, there are people who have offered to cover this rotation, allowing the person
to remain remote but is this considered fair to those employees who live in the Bay Area?
What if the team dynamics change and there is no longer this commitment to cover, then
what? In the other [team], I'm not so sure there will be a willingness to provide coverage
for the person out of state?
Meanwhile, in the IT department, SMT 19 decided to create a “secondary market” that would
enable employees to select amongst themselves which days they would be on-site. He decided
that (unless employees had caregiving responsibilities) more senior employees would get to
select their on-site days before more junior employees (even though junior employees were more
likely to have longer commutes due to being unable to afford nearby housing). Ultimately, this
contributed to inequalities in ways that did not exist before the remote work adoption decisions
had been made.
A second way that high-status actors’ actions ended up marginalizing low-status actors
related to decisions on where to live. Particle’s leadership had much higher salaries than the
average employee and tended to live closer to Particle because they could afford local area

42

pricing. In general, leaders had shorter commute times because they could afford local area
housing prices. Some even were able to live out of state because they could afford to frequently
commute to the lab via airplane and stay in a nearby upscale hotel. Thus, being classified into a
specific arrangement did not generally influence where executives planned to live. In contrast, a
significant proportion of lower-status employees did not have the financial wherewithal to afford
to live near Particle. It meant that the decision to have limited remote work severely impacted
where and how they could live and their commute times. One science employee explained to us
in vivid detail:
The house I can afford is 400 miles away and sometimes [I] sleep in my car. That's the
situation that I’m in is…I’d be sleeping in my car. I was already figuring out how to
rearrange things so that I could sleep in my car. But it's not something I want to do. …My
office space ends here [points to spot next to him]. My daughter’s space starts
there….We live in a two-bedroom…her bed’s right here. So it’s like, we don't have much
space—all storage is underneath my desk.
Another non-scientific employee explained:
There's a ton of people who are commuting, you know, two-and-a-half, three hours a day.
You know, because people can’t afford a three million dollar house to live in [a
neighboring city]. When I moved to my neighborhood…approaching four years ago…
everybody told me I was nuts because of how far I was commuting and now there are
three different people on my street that work for [an organization nearby Particle].
The third dimension of low-status actors being marginalized through limited remote work
adoption related to office space. When we visited the lab in person after our observations had
formally ended, we saw a mission support employee carrying a stack of boxes back to her office.
One of the future of work taskforce members asked her why she was carrying the boxes and she
explained that she would probably need to give up her office space to a scientist even though she
expected to have significant on-site presence. In contrast, several science SMT members refused
to give up their office space—even some who expected to adopt hybrid classifications. Multiple
science SMT members had more than one office. Science SMT 9 decided to take over a second

43

office in a different building where some of his employees were located and where he planned to
spend half a day a week so that he could get more “face time” with them. Science SMTs’
resistance to give up their space seemed to be driven, in part, by the fact that dedicated physical
offices were “such a measure of…self-worth and achievement,” as one employee put it.
Ultimately, high-status actors’ rather liberal appropriation of space perpetuated inequalities.
The further marginalization of low-status actors is especially ironic given that the remote
work adoption decision was seen by some as an opportunity to redress pre-existing inequalities
in the organization. SMT 18 explained how she wanted to use the shift to remote work as an
opportunity for a reset in terms of equity: “I want to make sure we’re being equitable. We should
use this as a reset.” Non-science SMT 4 reiterated this goal of equity:
As we start identifying groups, just like we do with compensation…we should be looking
across functions to see what, you know, equity situations might exist or might end up not
be…[where we] might accidentally create inequitable situations.
Yet, this focus on equity was eroded throughout our observations. In the end, equity issues
seemed to be more of a nuisance and a distraction. Non-science SMT 15 compared employees’
voicing concerns about equity to “squabbling”: “We start to get into equity questions and you get
squabbling about this group is doing it this way.”

DISCUSSION
In ethnographically and inductively studying an organization navigate its decision
pertaining to remote work adoption, we uncovered a perplexing empirical puzzle. Despite remote
work offering cost savings, work being largely amenable to remote work, and significant
excitement for remote work—at the organizational level, as well as among individual workers—
the organization only minimally adopted remote work, with a mere 3% of workers adopting fulltime remote work arrangements when our observations concluded. We found that high-status

44

actors significantly shaped the organization’s remote work classification system in ways that
furthered their own interests and perpetuated inequalities—even as the classification system was
intended to minimize inequalities. Theorizing our findings, we develop a process model that
outlines the organizational process of status contests, which involves high-status actors' use of
their status toolkit comprising three tools—using abstract knowledge, accessing and allocation
resources, and first-mover actions—to influence the organization’s remote work adoption
decision. Our findings contribute primarily to research on remote work and, secondarily, to
research on classification systems.

Contributions to research on remote work
We center our contributions in the research related to remote work. First, we develop new
understanding of how an organization decides whether to adopt remote work. Most prior
research that has studied the decision of whether to adopt remote work has centered on the team
and individual levels, rather than the organizational level. This research has tended to overlook
broader organizational processes that might be influencing remote work adoption decisions. In
some ways, this lack of focus on broader organizational processes is understandable because, in
the past, organizational inertia has often hamstrung organizations from adopting remote work,
which has meant that, often, adoption decisions happen at individual and team levels, rather than
at the organizational level. Yet understanding the organizational processes of remote work
adoption has become more important as decision making about remote work is now happening at
an organizational level (Dropbox Team, 2020; Golden, 2022; Lufkin, 2022) with much greater
frequency, and with much greater salience, than in the past. We uncover new insights by
theorizing the organizational process of status contests, which influence organizations’ decisions

45

regarding whether to adopt remote work. In doing so, we extend prior literature by implicating
status as a key dimension that influences the adoption of remote work.
We also outline the specific tools that high-status actors drew on as part of their status
toolkit—abstract knowledge, access and allocation of resources, and first-mover actions.
Whereas abstract knowledge has only been applied in the context of professions to date (Abbott,
1988), we show how it can also be meaningfully applied to executives and perhaps other highstatus actors as well. 3 Additionally, while research on resource allocation has overwhelmingly
focused on financial and, to a lesser extent, human and financial resources (e.g., Pfeffer and
Salancik, 2003), we highlight office space and technology as resources that are critical in the
context of remote and hybrid organizations (Lovallo, Maritan, and Wu, 2022). Finally, although
some first mover advantage (FMA) scholars have focused on how FMA can result in cognitive
switching and habit formation (Suarez and Lanzolla, 2007), in contrast, in our case, first-mover
actions involved high-status actors’ influence on low-status actors’ behavior through
interdependencies and associated path dependence (e.g., the perceived need for on-site presence).
Ultimately, these three tools were used by high-status actors as part of their toolkit. We expect
that in other contexts, high-status actors might have access to more or fewer tools. We also
expect that in non-scientific settings where work is less tied to the physical location (such as onsite laboratories), the specific ways in which high-status actors use their status toolkit to
influence the adoption of remote work will likely vary.
We also contribute to research on remote work and inequality. Our study shows how
organizational processes and the organizational context ended up further marginalizing workers

3
We theorize that this use of abstract knowledge was particularly effective because it was employed by high-status
actors; if low-status actors were to infuse their abstract knowledge into decision making and communication, it
might have been more likely to be conceived as “foot-dragging” (Brayne and Christin, 2021) or lead to
organizational sanctions.

46

and perpetuating inequality. A long line of research has shown that remote workers are conferred
lower status in their organizations, are disrespected and devalued, and struggle to feel a sense of
belonging and identification with their organizations (Nilles 1994; Wiesenfeld, Raghuram, and
Garud 1999, 2001; Thatcher and Zhu, 2006; Blake, 2010; Bartel, Wrzesniewski, and Wiesenfeld,
2012). Prior research has overwhelmingly studied the downstream inequality outcomes of being
classified as a remote worker. We highlight a process whereby pre-existing inequalities in the
organizations (i.e., differences between high- and low-status workers) influence inequalities. We
show how remote work adoption decisions can be sites where pre-existing status dimensions can
become exacerbated. We urge future research to examine how high-status actors may influence
remote work classification systems in ways that shape inequalities along additional intersectional
status characteristics, such as those experienced by individuals who are remote workers and also
members of marginalized groups such as women, mothers, or racial minorities (Hancock, 2016;
Wingfield and Chavez, 2020).
Also pertinent to research on remote work and inequality, we contribute to research on
worker voice. Research suggests that workers are becoming more vocal in their organizations
and organizations increasingly need to garner support for organizational decisions from their
workers (Turco, 2012; Turco, 2016). We would expect that, especially for an organization that
wanted to give workers choice in deciding their remote work arrangements, the organizational
decision-making processes related to remote work adoption would be more substantive and
rational. However, this was not the case, as the decision-making process involved covert tools
that were often concealed from workers’ purview. Our study, thus, presents a cautionary tale of
how organizations can express a desire to prioritize worker voice and how this worker voice can
be gradually eroded over time. This more gradual dissipation of worker voice might be

47

especially detrimental because it is less likely than more abrupt and visible restrictions on worker
voice to trigger collective action (e.g., as in Turco, 2012).
Contributions to research on organizational status
This study focuses on status as the key salient dimension of difference across
organizational actors that influenced the remote work adoption decision. Status is determined by
the social worth that others confer to individuals or a group and is thus driven by others’
judgments and evaluations (Blader and Chen, 2012). One of the key reasons why high-status
actors were able to use their toolkits to influence the remote work adoption decisions was due to
their high social worth. Lower-status members were reticent to question high-status actors’ use
of abstract knowledge, their use of resources, and their first-mover actions because of the high
social worth that had been conferred to them.
By introducing the concept of a status toolkit, we show how high-status actors’ access to
this toolkit enabled them to significantly influence their organization’s decision to adopt remote
work. As in the case of “cultural toolkits” (Swidler, 1986) and “political toolkits” (Kellogg,
2011), we theorize how status toolkits were employed to shape action. Our conceptualization of
status toolkit aligns with Swidler’s conceptualization of “cultural toolkit” in that status (like
culture) shapes action through the repertoire of tools that are employed. However, whereas
Swidler’s cultural toolkit is conceptualized as limiting the available range of strategies of action,
we show how one’s use of a status toolkit can both limit (for low-status actors) and expand (for
high-status actors) the range of action strategies (in our case, to be able to influence the remote
work adoption decision in new ways). We theorize that this difference in the use of status
toolkits to also expand the range of action strategies relates to the fact that, unlike Swidler’s
(1986: 275) toolkit, which was shaped by “styles” and “habits,” the enactments of status toolkits

48

were influenced by actor preferences. We theorize that, because (high-status) actors’ preferences
impacted how they used the tools in their status toolkit, they were able to employ their toolkit
more agentically in ways that advanced their preferences. Similar to Kellogg’s (2011)
conceptualization of “political toolkits,” our conceptualization of status toolkits foregrounds the
relational context within which the toolkits are used. However, the actors in our study used status
toolkits to defend the status quo, not to challenge defenders of the status quo as in Kellogg’s
(2011) case. Taken together, we extend theory of toolkits by showing that toolkits need not be
exclusively composed of material systems (Kellogg, 2011) or immaterial aspects (such as habits,
skills, and styles per Swidler (1986)), but a combination of material (e.g., resource access and
allocation) and immaterial aspects (e.g., use of abstract knowledge and first-mover actions).
We also contribute to the research on status contests (Sutton and Hargadon, 1996) and
framing contests (Kaplan, 2008). We took inspiration from Kaplan’s (2008) conceptualization of
framing contests in our theorizing pertaining to status contests, and view the enactment of the
specific tool of using abstract knowledge as a framing contest. However, we extend Kaplan’s
important work on framing contests to also look at how resources and first-mover actions (noncognitive aspects) influence organizational dynamics and processes. We also extend Sutton and
Hargadon’s (1996) conceptualization of status contests. As Gardner (2010: 1) describes, status
contests (e.g., Sutton and Hargadon, 1996) are often conceptualized as “overt status
rivalries…typically focusing on battles for the top positions.” We show how status contests can
be much less visible and covert and not always enacted in public forums such as meetings, but
also in more private spaces (e.g., through local first-mover actions).

Contributions to the sociology of classification

49

Our study also contributes to research on classification systems. Over the past three
decades, research on classification systems has experienced great strides, so much so that
classification is now considered to be a distinct sociology (Bowker and Star 1999; Espeland and
Stevens, 2008; Berman and Hirschman, 2018). In particular, this research has highlighted how
classification systems often result in inequality (Rubineau and Kang, 2012; Mau, 2019;
Mennicken and Espeland, 2019; Adler, 2021). Yet despite these important theoretical
developments that have produced new understanding of outcomes of classification systems,
research on the processes through which classification systems are created has not kept pace.
In this paper, we drew on the sociology of classification, taking seriously the idea that
remote work adoption is likely to be a socially-constructed classification system. This theoretical
grounding enabled us to understand the impact that high-status actors, along multiple
dimensions, were having on the adoption of remote work. However, rather than merely
describing that high-status actors may influence classification systems, we outline the process
whereby they do so. The fact that we observed the development of the remote work classification
system in real-time enabled us to develop deep understanding of the creation process, whereas
most prior research studies classification systems after they have been created, often through
archival data. Notably, the tools that we found were used as part of the organizational process of
status contests were relatively covert in nature and were often employed without significant
lobbying and explicit debate. Thus, the three tools that were implicated in our findings contrast
with prior work on classification systems that have shown how high-status actors may shape
classification systems through relatively visible tools, such as legitimizing and lobbying for
changes to classification systems (e.g., Bowker and Star, 1999; Powell, 2000; Strand, 2010).

50

Although we expect the three tools we uncovered to be generalizable to classification
systems (including non-worker classification systems such as classifications of customers or
services) in most organizational settings where high-status actors are involved in the creation
process, we encourage future research to investigate whether other tools may arise in other
contexts. We also expect there to be boundary conditions associated with our process model. In
particular, we expect that our process model will not apply to classification systems that rely on
expert determinations, for example, where a group of professional experts such as in-house legal
experts needs to interpret a classification system that has already been developed at the state or
national level. We also theorize that the use of the tools employed by high-status actors was
particularly effective because they were used to influence the classification system of remote
work, a classification system that was rife with ambiguity. In contests where classification
systems are less ambiguous, our findings may be less applicable.
We further contribute more broadly to research and work at the intersection of
classification systems and the future of work. There are a plethora of new worker classification
systems being developed amid the shift to remote work and the rise of the “gig” and “creator”
economies (e.g., “independent contractors,” “essential workers,” “contract workers”) (Spreitzer,
Cameron, Garrett, 2017; Ashford, Caza, and Reid, 2018; Caza, Reid, and Ashford, 2021).
Organizations are increasingly becoming “blended workforces,” wherein different classifications
of workers work alongside one another, sometimes performing very similar jobs (Davis-Blake,
Broschak, and George, 2003). Our study underscores the importance of scrutinizing new
classification systems—especially ones that are developed within organizations where there may
be likely less oversight than at the state, industry, or professional levels— for the hidden status
moves that may be at play. In the words of Burawoy (2019: 27), those subjected to worker

51

classifications can be likened to “fish in water, unable to see the classifications we take for
granted, arbitrary classifications that are the basis of an arbitrary domination.”

Practical implications
As organizations grapple with how to establish new classification systems around the
future of work, our study encourages leaders in organizations to critically reflect on how they are
designing their classification systems. It urges executives to reflect on whether the systems they
are creating are advancing their own aims and perpetuating inequalities. This is particularly
salient in the context of hybrid work classification systems because, moving forward, most
organizations plan to adopt hybrid work, although the extent to which they adopt hybrid work
will differ significantly.
Our study also urges organizations to proactively design systems that minimize
inequalities. For example, it is incumbent on organizations to be on the lookout for attempts to
add abstract knowledge, to perform audits to understand discrepancies in terms of how resources
are allocated along different classification dimensions, and carefully scrutinize how first-mover
actions by organizational actors may have preempted other lower-status actors from having a
meaningful say in the creation of classification systems that fundamentally impact them.

52

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[The evaluation harness truncated this reference: showing the first 120000 of 123848 characters.]
</reference>

<statements>
1. Algorithmic management systems execute real-time behavioral tracking, dynamic task allocation, and automated performance grading.
</statements>

Begin the assessment now. Output only the JSON list, without any conversational text or explanations.