Needed Methodological Emancipation: Qualitative Coding and the Institutionalization of the Master’s Voice

Colonizing Research Practices in Action

A particularly telling example is presented in an episode of the TED Radio Hour podcast in which journalist Jad Abumrad relates an encounter between some Hmong residents of Vietnam who maintained that their community had been sprayed by chemical agents, resulting in the death of some family members. A Harvard science professor maintained that their story could not possibly be true as there were no facts to support their truths (Zomorodi, 2020). The scientist focused on facts such as a lack of contamination in soil samples from the area in question and a lack of connection between sightings of planes and the spraying of chemicals. The Hmong family responded that no one had shown any interest in their stories until this point, that members of their families had in fact died due to exposure to chemicals, and they had only come forward since they were invited to do so. Further, as expected, they had received only ridicule and would therefore withdraw from the conversation. One of us played the audio track of this encounter to a qualitative research methods class, to which a student responded that he did not know what to do with this information, as he did not know how to do research that took people’s feelings into consideration.

The novice researcher of our pair remains aghast by the voluminous quantity of research studies presented, approved, and endorsed as a cure-all that proclaim to fix or solve inequities in urban schools and disenfranchised educational settings. What is missing from these “studies” is true cultural and contextual vetting of promised practices and adequate researcher training about what ethical research practices might look like in such vulnerable contexts. Rather, researchers continue to peddle and push culturally insensitive curriculum and practices to students who need educational emancipation the most. Such practices include the well-intentioned fix-it stewards from the local educational nonprofit or university parading in for a barrage of “best practices” professional development, but the disappointing lack of contextualize applicability or follow up when additional resources were requested afterwards. In both situations, we must ask ourselves how we esteem and acknowledge the traditions and collective consciousness of these populations while still gleaning insight into their lifeworld.

Rebuking Academic Imperialism

Unlike the opinions of our aforementioned positivist-centered graduate student, we would suggest that the moral issue here is far greater than feelings. Chilisa (2019) denounces such practices as academic imperialism both in terms of the arguments put forward such as pitting “facts” against storied memories and “evidence” against anecdote, or as Mika (2017) has called it, different senses of “worldedness,” but also in the results of the encounter where dismissal and implicit mockery led to withdrawal, erasure, and the ultimate devaluing of human lives. J. T. Johnson and Murton (2007) have described similar conflicts as representing the tension between Western ways of knowing which separate human beings from their natural surroundings and indigenous systems that instead emphasize the connections between the two. The unfortunate result of this conflict is often to classify those who do not make the requisite separation as objects of study themselves, rather than to explore ways in which to understand perspectives that differ from that of the researchers (Koster et al., 2012). As Smith (2012) has bemoaned, whereas local knowledges have often been denigrated, they have just as often been exploited for commercial reasons.

The processes of meaning making and understanding within the Western world are well understood to be situated cultural practices. For example, most of the preservice teachers we teach for example are quick to pronounce themselves to be constructivists in that they believe that children should be allowed to create meanings and understandings for themselves as opposed to being “spoon-fed” information through direct instruction. Whereas, outside of those boundaries local knowledges are often quickly dismissed as “backward, uncivilized, superstitious, and/or absent, only to be replaced by the supposedly better, Eurocentric colonizing discourses” (Bhattacharya & Kim, 2018, p. 1). Adjepong (2019) has characterized practices where researchers flood the spaces of the researched with unexamined and entrenched meaning making practices as invading ethnographies. Similarly, Gullion and Tilton (2020) suggest that “the will to know” that drives most researchers, qualitative and otherwise, can sometimes bulldoze its way into sacred spaces, where knowledge is not meant to be shared. As Visweswaran (1994) pointed out, “the will to know” in research must always be balanced with the recognition of what cannot be known within the boundaries of the paradigm being espoused which can result in the opening of new possibilities for how research is done. As these perspectives collectively suggest, meticulous attention must be paid to all aspects of the apparatus of the research to reconstitute/decolonize it.

Aristotle and Ancient Coding History

Coding is not a device or phenomenon specific to qualitative research or even the modern research community. Rather, the roots of classification processes burrow deep to ancient Greece, or earlier, where the earliest scientists sought to unearth and grapple with the complexities of the natural world. Situated here we find Aristotle, Plato’s most famous pupil, who first began the process of using ontological logic to describe living things by “kind” and “form” using their differentiating characteristics somewhere between 372 and 287 B.C.E. (Grene, 1974). While Aristotelian taxonomies remained much more biologically nuanced and intuitively descriptive, they represent perhaps the first piloting of binomial naming of “genus and differentia” markers of coding that mirror in ways modern scientific classification systems (Granger, 1984, p. 3). Though Aristotle’s early methods of analyzing the natural world focused on ideas of “matter” and “form” instead of a large all-encompassing classification system like the 18th century Linnaen taxonomic system (Grene, 1974), Aristotle also believed in a hierarchical biology and compared all natural beings to that of his chief comparison subject, humans, creating the now termed “ladder of nature” of hierarchical fiefdom (Archibald, 2014; Nussbaum, 1991). We believe these sorting processes, and the early hierarchical ways scientists have framed the collected data and data participants, have persisted into modern research of all subjects.

Almost Modern Alternatives Presented by a “Highly Suspect Newcomer”

In the modern qualitative research discourse community, codes are essentially a tool that qualitative researchers use to simplify collected data to make it more manageable; coding data allows researchers to rise above the nitty gritty and to extract meaning from data. These precedents are well established. At its genesis, qualitative methods were pushed for answers regarding many of the established rules and conventions of quantitative research to prove both its virility and rigor as a legitimate alternative research paradigm (Howe & Eisenhart, 1990; Miles & Huberman, 1984). Put simply, researchers seemed to be faced with a blunt but vaguely defined choice “between an entrenched quantitative methodology and a highly suspect newcomer” (Howe & Eisenhart, 1990, p. 2). In the early years, when the well-established research masters were all of the positivist paradigm and qualitative methodological epistemologies were relatively unknown, there was still little assurance that qualitative researchers and their methods would “assemble accurate evidence and test hypothesis” in a way that would merit acceptance in the existing empirical research community (Glaser & Strauss, 1967, p. 16). Therefore, there was a need to scrupulously document each methodological maneuver to validate practice, chiefly considering such issues as data collection, coding procedures, and data analysis to ensure reliability, validity, and replicability (Glaser & Strauss, 1967). Problematically, this also led to the ability for the masters to lay claim to such coded qualitative data for the purposes of quantitative categorical comparison robbed of context and amorphous in meaning.

Regardless, seeking to stifle quantitative critics adamant that such methodologies were inferior, less rigorous, and less scientific than the positivist dominant paradigm, naturalistic pioneers sought a way to systematize data analysis in a way that would protect the reliability and heighten the validity of qualitative research to be as rigorous as the “canons of classical test theory” (Guba & Lincoln, 1981; Huberman & Miles, 1983, p. 293). Qualitative researchers sought to engender trustworthiness in the results of the study, and coding became a way to clarify and also legitimize the rigorous analysis sequence that naturalistic inquirers undertook (Lincoln & Guba, 1985). Even so, Glaser and Strauss, founders of grounded theory, warned of the need for such qualitative coding to remain pliable and focused on a pluralistic ways of knowing, noting that their chief aim is to “stimulate other theorists to codify and publish their own methods for generating theory” to weave a variety of perspectives in such an “age of verification” (Glaser & Strauss, 1967, p. 8).

The desire to earn a seat at the table of the quantitative patriarchy required qualitative researchers to further embody the data analysis voice of quantitative masters. Goetz and LeCompte (1981) referred to coding as solving the “problem of data reduction” commenting that data such as “field notes, narrative descriptions, behavior chronicles, or videotapes” need to be systematically “reduced and classified for interpretation and presentation” (p. 51). This manifested in the further evolvement of data analysis processes to the adoption of more formal coding protocols. In their classic work, Goetz and LeCompte (1981) have justified the use of structured coding protocols, remarking that un-coded data can be so voluminous as to become unintelligible; further, they remark that without coding, researchers may simply fall back on their own memories of data that stood out to them rather than capturing it in all its complexity when reporting on it. It is noticeable that the impetus for the use of coding seems to arise from concerns about data management, and about rendering data intelligible, not from a will to represent the stories of the participants with integrity and fidelity. This is a trend that has continued over time, and it stems seemingly from the desire for qualitative research methods to be defensible against the mis-assumedly more rigorous and scientific quantitative methods counterparts.

Qualitative contemporaries, Lincoln and Guba (1985), conceptualized coding as “unitizing” qualitative data or breaking it down into the smallest pieces of information that can stand alone; researchers then clustered those pieces of data into piles–the original method called for data to be unitized on index cards—and the piles of data were gradually clustered into larger units in their classic text. Similarly, in 1986 Bernard et al. commented on the need to develop efficient methods of coding as “systematic management and reduction of complexity are particularly important when dealing with verbatim recording of informants' reports in their native language.” (Bernard et al., 1986, p. X). And, coding seemed to be a tool to help researchers navigate the difficulties in qualitative data analysis, or what Lather (1991) has famously called, the “black hole” of qualitative research (p. 149). Coding thus appeared as both a utilitarian stopgap for the “data analysis problem” and master-serving—a perceived win-win at the time.

A heavy reliance on the continued adoption of the master’s voice using coding as the chief method of qualitative data analysis persisted through the dawn of the 21^st century. Bernard (1994) for example directly advocated for the echoing of the master’s voice, purporting that qualitative data be coded in ways that quantized it, suggesting that qualitative data such as responses to open ended questions be coded in a manner that allowed it to be quickly transformed into numerical data. Though qualitative purists disagreed with Bernard’s intentions, coding processes provided a common community of practice among many qualitative researchers in a field that greatly varies in topic, implementation, and theoretical grounding. Researchers like Thorne (2000) pondered a greater need to look at such practices, commenting that whereas data analysis is perhaps the most complex phase in qualitative research, it has received the least attention in the literature.

Modern Perspectives and Coding as Capitalism

Coding has advanced to the present day as the traditional practice for qualitative data analysis; however, other data analysis perspectives and methods were simultaneously proposed in the latter part of the 20th century. This range of methods encompassing post-modern, post-structural, and post-colonial perspectives is highlighted in the next section on critical discussions of coding practice. Though coding was not pushed as the singular method during this time, coding practices have undergone a renaissance in the last ten years, as qualitative research has transitioned to a mainstay of researcher methodological training.

Today coding is often viewed as a gateway method of data analysis for those with little qualitative experience or theoretical training, and coding guidebooks containing an almost step-by-step prescription are relied upon by budding researchers and advising faculty alike. While these guidebooks proffer as resources rather than prescriptions, students reference such methods like biblical verses. More nefarious perhaps are the ways coding has emboldened the master’s voice through capitalism. The various iterations (e.g., NVivo, ATLAS.ti, Dedoose, Quirkos, KH Coder, etc.) of qualitative coding computer software that promise to practically “do the coding for you” supremely profit off this master’s inflection. These software systems largely perpetuate coding methods even the most ardent supporters of coding would admonish—offering frequency counts and labels galore. Unsurprisingly, researchers and businessmen from all different fields have joined the qualitative army to advance such capitalistic coding enterprises. It appears the temporary adoption of the master’s way of thinking has persisted. This master’s way of thinking is now being perpetuated by the first generation of modern qualitative masters themselves.

In recent years, Creswell (2015) has defined coding as “the process of analyzing qualitative text data by taking them apart to see what they yield before putting the data back together in a meaningful way” (p. 156). Saldaña (2016) has defined a code as “most often a word or short phrase that symbolically assigns a summative, salient, essence-capturing, and/or evocative attribute for a portion of language-based or visual data” (p. 3). A few years later, the 2018 version of the Sage Handbook of Qualitative Research has only three chapters out of a total of 42 on analyzing qualitative data (Jackson & Mezzei, 2018; Peräkylä & Ruusuvuori, 2018; Wyatt et al., 2018) and none of these deal explicitly with the kind of coding that most qualitative researchers do. This is to some extent purposeful for as Jackson & Mezzei (2018) have said “conventional qualitative data analysis, involving technical coding and thematic extraction, has its foundation in positivism—with its emphasis on sorting, simplification, and generalizations—and is actually data organization rather than robust analysis.” (p. 1242)

As Marathe and Toyama (2018) have said, most qualitative data in some way or the other consists of “unstructured text.” Much of this data is gathered through the use of common qualitative methods such as observation, interviews, focus groups, or analyzing other written content (Bhattacharya, 2018), although there is also a variety of non-textual data that qualitative researchers also consider data such as photographs, sketches, diagrams, and performances. Elliott (2018) explains that “researchers code to get to grips with our data; to understand it, to spend time with it, and ultimately to render it into something we can report.” (p. 2851). Castleberry and Nolan (2018) elaborate that the process of analyzing qualitative data generally includes five phases: “compiling, disassembling, reassembling, interpreting, and concluding” (p. 808).

As such it may be that coding is perceived as a practice to be deconstructed and perhaps resisted rather than to be practiced. Nevertheless, it continues to be widely practiced and clear-cut prescriptions for how it should be done are now widely available (Miles et al., 2020). In this section, we will first present an overview of some of these entrenched coding practices and then move to summarize existing arguments that have problematized those practices. In the final section, we will offer some decolonial possibilities for coding qualitative data, since there is little existing scholarship on what decolonial practices for coding might look like.

Certainly, numerous other forms of coding have evolved. However, as Miles et al. (2020) have commented, most forms of qualitative coding retain certain core features, namely: (a) reading through qualitative data such as field notes and transcripts of interviews and coding it in some way; (b) further searching through those codes for similarities in terms of patterns or themes; (c) using those commonalities identified in step 2 to guide subsequent data collection; (d) incorporating the use of analytic memos or other forms of reflective notes into the data analysis process; (e) pulling together all the analytic steps described to arrive at various abstracted categories or themes that purport to represent the data the most fully; and, (f) relating those abstracted themes to the literature to question/problematize/propose theories or concepts. We would suggest that this approach to coding has now become part of the collective “how to” of qualitative research and consequently are what we would like to examine more fully in this paper as it starts to take on the semblance of the Master’s voice.

Miles et al. (2020) have explained that the process of qualitative data analysis essentially comprises of three processes, namely, data condensation, data display, and drawing and verifying conclusions. In their view, the process of data condensation, mostly done through coding, is a process of strengthening the data, as it “sharpens, sorts, focuses, discards and organizes data” into a form that supports the core tasks of researchers, that is, to draw and verify conclusions (Miles et al., 2020, p. 8). In turn, data display, too, is a critical part of qualitative data analysis in that data must be assembled in a way that is conducive both to reflection and to action.

Finally, the process of drawing and verifying conclusions involves testing the meanings derived from the data for “plausibility, sturdiness and confirmability” (Miles et al., 2020). Lester et al. (2020) have commented that one of the reasons that qualitative data analysis schemes have become more tightly defined over the years has to do with the explosion of approaches to qualitative research that we referenced earlier on. Conversely, this heterodoxy has been accompanied by even more stringent demands for transparency in regards as to how data was collected and analyzed to verify that the data was indeed collected and analyzed rigorously. Qualitative research has long been faulted for what Lester et al. (2020) have termed “insufficient transparency” (Lester et al., 2020, p. 102) and multiple evaluation criteria that have been recently established for qualitative research include a focus on rigorous data analysis procedures (Anderson, 2017; Rocco, 2010; Storberg-Walker, 2012).

Knowing, Capitalism-Colonialism, and Reconciliation

Research itself is framed around such colonial artistry effusing the view that the world is knowable, and the act of reducing the sweeping landscape of the world to smaller pieces makes it more knowable than ever (Cannella & Viruru, 2004). Knowability is thus accepted as requiring the construction of an enterprise dedicated to the business of knowing. That self-promoting and sustaining enterprise then separates itself from the world it is trying to know and produces its own version of the world in the form of data that Kitchin (2014) has defined as “material produced by abstracting the world into categories, measures and other representational forms . . . that constitute the building blocks from which information and knowledge are created.” (p. 1). To extend this metaphor further, coding data then becomes the process of rearranging the blocks to form structures or create narratives that only vaguely resemble their origins. Yet, since those reconstructions are done by those who are in the business of knowing, those versions are accorded more credibility than the originals.

As Couldry and Meijas (2019) caution, data has become the new fodder for capitalist-colonialism to where human life is already being restructured in ways that continually generate data (such as when friendships are commodified and redefined through social media platforms, or when health and well-being go from practices defined by communities to metrics that are kept track of by a variety of apps and other devices). We would add that in such a framework coding presupposes the data; for example, the number of steps we take per day are quantified only to classify our efforts into predetermined categories. We return to Maclure’s (2013) warning that it is critical to recognize if we are coding something that is already coded to begin with and act accordingly.

In stark contrast, Anzaldua and Keating (2015) have talked about how meaning making can be a process of reconciliation with oneself, and name this process as

the “Coyol xauhqui imperative”: a struggle to reconstruct oneself and heal the sustos resulting from woundings, traumas, racism, and other acts of violation que hechan pedazos nuestras almas, split us, scatter our energies, and haunt us. The Coyolxauhqui imperative is the act of calling back those pieces of the self/soul that have been dispersed or lost, the act of mourning the losses that haunt us. (p. 2)

The possibilities that emerge when one adopts such a purpose are exciting and reveal multiple possibilities for what doing research can be but also cautions about the road ahead. For example, Anzaldua and Keating (2015) speak of how as they grappled “half-unconsciously” with the creation of new methodologies that consciously rebuke existing modes of practice they realized that

to bring into being something that does not yet exist in the world, a sacrifice will be required. Sacrifice means “making holy.” What will you give up in making holy the process of writing? You make a commitment, un compromiso, to create meaning. A commitment to add to the field of literature and not just duplicate what’s already there. A commitment to explore untrodden caminos—which means turning over all rocks, even those with worms underneath them. (p. 97)

Postcolonial scholars have long illustrated how the modification of social and economic arrangements for economic benefit was a foundational principle of the colonial enterprise (Mir et al., 2003) and recognized the need for “new forms of cultural and political production that operate outside the protocols of metropolitan traditions and enable successful resistance to, and transformation of, the degradation and material injustice to which disempowered peoples and societies remain subjected” (Young, 2001, p. 69). And as Couldry and Meijas (2019) have said, in response to the criticism that it is absurd to be highlighting colonial practices in the lands of the colonizers: “But what if the armory of colonialism is expanding? What if new ways of appropriating human life, and the freedoms on which it depends, are emerging?” (p. x). To return to Anzaldua and Keating’s (2015) metaphor, we must continue to turn over rocks and find the worms underneath.

Scholarly Directions in Decolonized Praxis

In this final section of the paper we will intersperse the perspectives of decolonial scholars with our own suggestions for how to think about coding.

Couldry and Meijas (2019) offer a fascinating account of modern forms of data colonialism that we would like to first highlight. Their main contention is that whereas historical forms of colonialism operated through forcibly grabbing control of territories and their resources (including human resources) contemporary forms of colonialism can be found in the machinations of data colonialism in which data about human experience is the ultimate currency that is being sought, so it can be subsequently bought and sold. While Couldry and Meijas are speaking more in the context of how human interactions in digital spheres are both coveted and used, we believe that the cautions they offer apply in this context as well, particularly since most qualitative data is either collected in digital form from the beginning (e.g., typed as opposed to handwritten field notes) or quickly digitized thereafter (as in when interview notes are transcribed). Couldry and Meijas caution us for example to be mindful of the term “raw” for as they put it, rawness is a colonial construct that “means available for exploitation without resistance rather than a substance that needs no processing” (p. xvii). The parallels to qualitative data and the management of its rawness are immediately apparent and we hope will lead to the exploration of how we deal with rawness when we center its completeness, power, and wholeness rather than its vulnerability and potential.

Couldry and Meijas (2019) have further summarized colonialism as centering around four practices: taking control over resources, the development of exploitative practices that made the process of appropriation smoother (e.g., slavery and other equally morally bankrupt practices that are one-sided in their benefits), the restriction of the benefits of such labor to a select few, and finally the development of ideologies that justified unethical practices. Once again, the parallels to the process of research rise forcibly to the top, hence our caution that we must, as an imperative, when faced with situations in which benefits accrue unequally, take a step back and see how we can do better. When we look at coding in particular, which is so instrumental in how we as researchers tell the stories of our participants, can we ask questions such as: how can we involve participants in this process without adding to their emotional burdens? How would we make coding an activity that benefits participants as well as researchers? Is there a form of compensation that would both make the activity more attractive as well as mutually beneficial?

Grosfoguel (2007) as well as Couldry and Meijas (2019) have put forward three entry points through which decolonizing works can enter/disrupt conversations that continue to represent the Masters voice, namely (a) the seeking of sources from outside traditional Western sources, (b) the fostering of dialogue that supports the development of a “pluriversal rather than a universal worldview” (Couldry & Meijas, 2019, p. 80), and (c) through thinking “from and with subalternized racial/ethnic/sexual spaces and bodies.” (Grosfoguel, 2007, p. 46).

Sources Outside the Western Canon

Seeking sources from outside the Western canon is not, of course, a new idea and one particularly relevant to decolonial thinking given that one of the criticisms of postcolonial theory is that it has not sufficiently disengaged from Western modes of thought (Couldry & Meijas, 2019). As Moyo (2021) has said, the hidden Eurocentric curriculum that pervades ways of being and knowing can “can only be unmasked through decolonial epistemological labor that seeks cognitive justice and a truly inclusive multicultural theory in the field.” (p. 153).

An example can be found in the work of Gandhi (2019) who has identified non-injuriousness as an important feature of decolonial movements, rooted in an understanding of suffering and exploitation, and writes that if there were to be a manifesto for postcolonial thinking, prioritizing non-injuriousness would be an important part of it. We would suggest that the principle of non-injuriousness is an important consideration while both doing research and coding qualitative data. Moreover, one must position non-injuriousness against the backdrop of the long history of how injuries and suffering created through colonialism have been dealt with, that is, mostly as regrettable incidents, that “register in the mode of affect—specifically the affect of sentimentality” rather than as fundamental violations of sovereignty or rights (Rijswijk, 2021, p. 77). For example, Rijswijk describes how abhorrent practices such as separating Native children from their families in Australia are often conceptualized as narratives of personal injury and suffering. These “incidents” are then addressed through actions such as fostering dialogue around reconciliation and healing that leave unaddressed issues such as assimilationist policies that created the issue to begin with.

Thus, while we believe that non-injuriousness is a place to begin thinking about looking at one’s data differently, it is also a place to begin to think about injury itself, a place of remembrance and reconciliation and revival and a place from where to call for justice. Even as we write this paper, communities who are the most vulnerable and have been injured the most grievously by the COVID-19 crisis are being researched the most to “understand” the manifestations and impact of the virus, while simultaneously communities of privilege are denying those same communities the resources to fight back. First and foremost, such forms of exploited injury must be avoided. Further, to transform human tellings of their own stories into data itself is a form of injury; to unitize those stories injures the teller even further.

As part of a qualitative study aimed at understanding the social construction of motherhood in Qatari society, one of us attempted to interview a teacher in a school whose husband had all but abandoned her to raise their children by herself. As she herself noted, although she was financially well taken care of, that was the only form of support she received (Viruru & Nasser, 2017). Her pain was, however, so evident in her story that it spilled over into much more than words; her eyes flashed as we spoke, her voice was loaded with contempt and she only spoke for a few minutes as her disgust was so strong that it prevented her from speaking. Whereas at one level, she withheld data from us (by not speaking), the data she did provide was deeply imbued with meaning and context. Further it was not data that could be unitized as the words could not be separated from the way in which she said them and thus demanded that the entire interview be reported as a whole, rather than as fragments interwoven into other narratives.

Across the world in a university setting, a female participant divulged a stomach churning tale of their participation in a military preparation program, recounting that they had been sexually assaulted by a peer in their organization and that their female military leadership had not only practiced abhorrent inaction, but also questioned the validity of the victim’s claims. The participant was told that “this is what happens when you play with the boys” by her female military leader, and that she would be “punched in the c**t” by her male “buddies” if she told anyone outside of the organization about the incident. As the participant bravely recounted this simultaneous example of gaslighting, slut-shaming, and victim-blaming, they urged this emergent researcher to share their full story with the world. This participant fiercely offered to send numerous other peers who had experienced such atrocities to tell their vulnerable tales of besmirched survival as well. Both emotionally and methodologically underprepared for such a weighty task, this study was actually left abandoned, as the researcher feared a disservice to the stories of injury survived by these women. The researcher couldn’t bring herself to shatter these stories into various shards and reposition them into a stained glass window of the master’s creation; this seemed to be a horrible inequity of narrative representation both too harmonious and too horrendous to admonish. But, without more knowledge of how to proceed and honor the courageous voices of these co-participants, it did not seem fair to play renovation architect to the harrowing masterpieces of their own shared experience.

We ask if perhaps such incidents can serve as guideposts for our community as we search for ways in which to better honor our participants voices. As Evans-Winters (2019) has said, the voices and ways of participants are often obliterated by the time they are processed through the academic mill, so there is a need for data analysis processes to both “synchronously armor and humanize” participants (p. 140). Because of this, Evans-Winters (2019) urges, it is essential we honor the richness of multiple participant identities in the data analysis process, remembering that “identity, location, words, ideas, and even disposition itself, even when recorded as text, are never static or permanent, but malleable and flexible, depending on context and time, and one’s ‘location’ in life” (p. 140). How can we honor the rich nuance of our participants’ voices and avoid truncating and bastardizing their stories?

Fostering Dialogues and Ways of Being That Support Pluriversity

If our goal is to foster dialogues that support a pluriversal rather than a universal worldview, we ask why it is that the goal of coding qualitative data has been to allow us as researchers to assume at least an approximation of the Master’s voice to speak coherently and with authority rather than to present our findings as tentative, transient, and incomplete. Must the goal of the researcher be to arrive at rigid conclusions? Gandhi (2019) has suggested that another principle of the manifesto for postcolonial thinking can be that it offers an ethic of departure. As Gandhi explains, whereas postcolonialism is famous for its “disciplinary hospitality” and inclusivity, as evidenced by its foregrounding of concepts such as hybridity and interstitiality (Bhabha, 1994), it also espouses a strong commitment to disobedience, non-cooperation, and non-alignment and a “strong belief that every social contract incorporates the option of running away to forge a better social contract” (p. 191). We ask what it would like to run away from the conventions of qualitative coding to forge other options. An example is to be found in the work of Bhattacharya (2020) and how she employs post-intentionality and Deleuzoguattarian lines of flight to “incorporate absurdity as a legitimate form of imagination, freedom, resistance, and flight” while analyzing textual data (p. 524).

Ulmer (2017) has also commented on the possibilities that can be found when one replaces “McMethodologies” with “slow” methodologies, particularly when confronted with the telling of challenging stories (p. 543). As she elaborates, engaging with slow methodologies calls for “untraining” and unmooring oneself from conventional wisdom and entering playful spaces where data can be visualized (often through medium other than text) anew (Ulmer, 2018). Moyo (2021) urges us to use spaces of education not only as places where knowledge can be transmitted or even more detrimentally as “transmission sites for Western theory” but rather as “sites of production” where theories can emerge (p. 162). What if then, in our qualitative methods courses, rather than instructing our students on acknowledged methods of coding data, we invited them to enter into a dialogue with a rich variety of sources from outside the canon and use those to make sense of their data?

Privileging Subalternized Bodies and Spaces as Being and Thinking Locations

Finally if we support the idea of subalternized bodies and spaces as places, from which and with whom to think with, there are a host of possibilities that emerge from community based participatory researchers and their work. For example, Levy et al. (2020) offer the possibility of drawing from neo-indigenous and hip-hop cultures to enrich community based counseling practices. Ninomiya et al. (2020) draw on the work of Smith (2012) to argue for the creation of practices such as institutional ethnographies, that “reveal how particular peoples’ everyday experiences are connected to observable social relations that are mediated by institutional work” (p. 223). Such studies map the ways in which everyday experiences are controlled by what they term “ruling relations” practiced by institutions; methodological flexibility is a key tenet as well. Halkort (2019), while agreeing with the spirit of community based participatory research, encourages qualitative researchers to engage in what she terms as “data activism” (p. 325). Drawing from her work in Palestinian refugee campus, and much in the manner of Couldry and Meijas (2019), she cautions against the easy adoption of known data collection and analysis strategies, given their potential for exploitation. For example, maps created to identify areas of need in refugee camps can be repurposed to control the distribution of resources by those in power. This is akin to the problematized issues of variable labeling in quantitative research, namely the existence, exclusion, and over-emphasis of specific variables in quantitative research situates problematically for holistic and authentic sweeping analysis of a phenomena or complex human being. As Holkort cautions, divorcing data from the contexts in which it lives, and separating it into an element that lives by itself, rather than as living entity empowers “ontologies of the social that rigidly separate knowledge about things and power over people and ensure they can be managed in different places.” (p. 325).

Rijswijk (2021) urges us not to be too quick to dismiss the injuries that subaltarnized bodies have endured, as dominant spaces continually deny those bodies rights to which they are entitled. She raises the salient example that although indigenous women continue to experience violence at disproportionately high rates, disclosing that violence often leads to more state violence. As she tellingly reminds us, the hashtag #metoo movement has yet to acknowledge the subaltarnized bodies that have long endured this supposedly modern injustice. As researchers Rijswijk encourages us to consider “methods that think of critique as a ‘problem of genre’ where genre is understood not merely as an aesthetic device but as a structure that constitutes and reveals worlds” (p. 81). We would extend this metaphor to the genre of qualitative research and ask what structures and worlds does it constitute and reveal? Where do subaltrnized bodies belong in those worlds?