The plans patriarchal imposition prevents ephemeral bonds of trust

Reflecting on how we might stand against neoliberalism and the colonial expectations of productivity, the third author of this paper reflected in our DH Unbound panel (Social Justice Oriented Critical Design Pedagogy in Urgent Times) that she finds that qLab is a space where we support each other in these ways as we root for slow and meaningful community-based scholarship rather than number-based quantitative evaluations. A simple statement at first, but if we reflect on the burden of these pressures, it may no longer seem so simple. Certainly, given the scarcity of tenure-track positions, the increasing precarity of teaching-focused lecturer positions, and the expectation that everyone including graduate students publish more (and these are only to name a few academic pressures), the competitive nature of academic becomes all the more clear, where people maintain the highest of expectations of themselves and of others. For us, embodying slowness is not equal to being unproductive. Rather, it requires a re-structuring of what “productivity” means, focusing on giving the time and care to our work and to our bodies. For example, during the COVID-19 pandemic lockdowns, one of our lab members was editing a book on World Islam. As the submission time drew nearer, she observed that more than half of the book contributors who were women had to withdraw their chapters from the book. Nature and other science-based journals, at the very beginning of the pandemic, already had the statistics that women were publishing less than men, and that this was expected to continue over the pandemic (Minello 2020). We strongly believe that it is not just that women are taking more responsibility for the children and the home, but that women and other marginalized genders, racialized scholars, and queer scholars are giving more care at work and to their research in order to ensure that it work is meaningful for themselves and for their students, and to ensure that the work is of high quality that lives up to the community’s expectations. As Kathy Hytten writes, “slowing down is good for us as individuals, colleagues, and knowledge producers. Slow does not mean idle; rather, it provides a space for meaningfulness and for genuine inquiry” (Hytten 2017, 159). While recognizing the labour that goes into such care, qLab advocates for that space of slowness, to allow us the space to show care with each other as we seek to normalize this kind of consideration within our broader academic ecosystems, and we call for others to do the same.

Crucially, this trust within our lab and in our research is built slowly, especially because within feminist, Indigenous, and community-based methodologies, trust is and should be slowly built, focusing on relationship building and nurturing. Often, in reflecting on such research, academics agree that in these research settings trust and relationships should come slowly, and that, given Canada’s history of settler colonialism, it is unfair and, frankly, impossible to ask marginalized and targeted communities to immediately trust researchers. And yet, in practice, the hidden curriculum of constant publishing and fast-paced researching dictates otherwise. If we agree that taking time and care, that emphasizing slowness, should be considered when working with community members, we must consider why we do not use the same mentality when working with other colleagues and students. Why force ourselves to rush into work with each other without the foundational relationship building? Regardless of intent, saying “trust me” when trying to make sense of the bureaucracy of the university, of the pandemic, of new motherhood or future motherhood means very little, and it does not come naturally or easily to racialized women. Trust must come slowly, and it must come from a place of genuine support, care, and active listening. Adding our voices to the important work within fields of feminist digital humanities and feminist geographies on care, trust, support, and slow scholarship (e.g., Adams-Hutcheson and Johnston 2019; Caretta and Faria 2020; Livio and Emerson 2019; Pawlicka-Deger 2020; Smyth, Linz, and Hudson 2020), we urge other labs to reflect on how this might be possible for their lab, research, and scholarly communities.

MAKE: Creating digital feminist interventions

Given our commitments to thinking about the feminist orientations that guide our lab and talking about the care and support that fuel our spaces and the feminist shadow networks that underpin them, the “making” work of Feminist Think Tank embraces embodied methods and values the largely ephemeral, personal, intimate digital practices of feminist social media users. In keeping with Livio and Emerson’s contention that “contemporary labs, as spaces of collective and interdisciplinary thinking and doing, require their own consideration as sites for feminist methodology” (Livio and Emerson 2019, 287), our projects are predominantly concerned with embodied small data feminist methodologies that can engage what cannot be captured by large-scale, computer-generated web capturing. This is true for us across our data jams, social media interventions, and archival work—three projects that seek to interrogate the hidden questions, biases, and systems of power that undergird our technological and digital artifacts from embodied and feminist perspectives.

In the fall of 2021, MacDonald and Wiens developed a series of data jams to explore low-tech, collaborative ways into collecting and analyzing digital feminist content, drawing on the work of Data Feminism to ground these jams (D’Ignazio and Klein 2020). In their book, Catherine D’Ignazio and Lauren Klein define data feminism as “a way of thinking about data, both their uses and their limits, that is informed by direct experience, by a commitment to action, and by intersectional feminist thought” (D’Ignazio and Klein 2020, 8). The intersectional feminist lens taken by D’Ignazio and Klein prompts the argument that “power is not distributed equally in the world” and therefore, “in a world in which data is power,” a feminist perspective helps researchers to “understand how [this] can be challenged and changed” (D’Ignazio and Klein 2020, 14). From a data feminist perspective, we sought to locate the reliance on big data in digital research as a particular area of power to address. And this is because, as Shawna Ross argues, “‘big data’ is itself gendered, both in terms of the constellation of theories and concepts that underpin its authority and in terms of the day-to-day realities in which [it] is collected, analyzed, and used for an ever-increasing variety of purposes” (Ross 2018, 212). Ross advocates for DH to employ feminist and intersectional approaches to mitigate the “imperialist [and masculinist] knowledge structures” of big data (Ross 2018, 212). As if speaking directly to Ross, the introduction to Uncertain Archives: Critical Keywords for Big Data supports this call, adding the need for arts-based research methodologies as a counterpoint. This counterpoint provides “embodied, imaginative, and speculative approaches to the challenges that big data archives pose” (Thylstrup et al. 2021, 8). Inspired by these calls for imaginative and embodied feminist methods, Feminist Think Tank sought to make our own located, small data alternative to big data, which has informed much of FTT’s research design. and the mobilization of the feminist shadow networks to conceptualize, organize, and bring into being such efforts.

In our data jam “Everything but the Kitchen Sink,” we invited participants to share idiosyncratic everyday collections they save and carry with them on their phones, and to put those collections in conversation with other people’s collections. The data jam collecting methods are interested in born-digital Internet artifacts, which we treat as “media events” that reveal new ways of collectively and communicatively “doing feminism” (Rentschler 2019; Rentschler and Thrift 2015). Reading feminist memes, hashtags, and videos in these collections as media events acknowledges that they are archivable, analyzable objects and highlights their value as digital sites of analysis. This approach aims to “thicken” data via both “manual data collection” and “long-term online observation” (Latzko-Toth, Bonneau, and Millette 2017, 199) that indexes the embodied and affective investments of participant researchers. This allowed us as researchers to think about how data come together, what they afford researchers, and how various forms of data “speak” to each other. We foregrounded personal data collections that included a greater set of under-represented voices. In doing so, we sought to (1) respond to urgent calls in the digital humanities to address concerns of data ethics, sexism, and racism in research methods from intersectional feminist perspectives; and (2) demonstrate to participants that talking about our own practices, how they rub up against dominant practices, and what these spaces then open for us as we reflect on our own positionalities, news feeds, and feminisms all matter for the creation of our own communities and networks.

A second data jam, held in February 2022, was scheduled as a pre-event for a talk delivered at the University of Waterloo by Wendy Chun on her recent book, Discriminating Data: Correlation, Neighborhoods, and the New Politics of Recognition, as part of the Critical Tech Talk series hosted by the Critical Media Lab. Feminist Think Tank gathered Arts and Engineering students together to contemplate the following quote from Chun’s book: “[I]f we think through our roles as performers and characters in the drama called ‘big data,’ we do not have to accept the current terms of our deployment” (Chun 2021, 170); “we are characters, rather than marionettes” (Chun 2021, 248). In groups, students were prompted to make memes in response to the conversations they had around the quote. The result was a series of memes generated within the event that count as a small dataset in itself. These are context specific but offer insights into how different communities of students are making sense of texts and data in their everyday mediated lives. In the spirit of the critical ethos of the talk, this Data Jam aimed to unsettle the end-goal of polarization within machine learning and big data by providing alternative ways to engage and, indeed, play with data. How we play and make sense of data from within seemingly rigid systems is an important lesson for examining how power operates in and through its construction in order to conceptualize, produce, and analyze more equitable, inclusive, and actionable data.

In May 2022, we hosted a third data jam, “Ecologies of AI: Materializing Labour, Power, and Production,” that corresponded with another Critical Tech Talk on Artificial Intelligence at the University of Waterloo. Here, we brought together arts, engineering, and math students and invited them to take apart sections of Kate Crawford’s Anatomy of an AI System, enlarge them, and print them out for further analysis. At this jam, we asked the overarching question: what are the networks of people, technology, and corporations that make up an AI system? Participants explored the ecologies and multiple networks of popular technologies like Alexa and Siri to think through our techno-corporeal relationships and the ways in which these relationships affect human and nonhuman bodies—areas of research that deserve critical attention as the technological reach of multinational corporations becomes global in scope. We considered questions like: how do different kinds of technologies, especially smart home technologies and virtual assistants like Alexa or Siri, change our family and friend relationships? What kinds of relationships do we have with virtual assistants? What kinds of relationships exist between us and tech corporations and humans? Who makes our technology? And what gets forgotten or laid to waste in the process of producing AI-powered systems? In small groups, students took up aspects of the mapped AI ecosystem to dissect and then make a visual response of their choosing. Fundamentally, students worked to identify some of these hidden costs of these technologies, unpacking and then materializing AI systems and the networks and ecologies they are part of in order to highlight the product of labour (including general public perception), the means of production, the labour power, and the waste that is produced through the process.

Throughout each data jam, what was uncovered for participants was the hidden narratives and histories that exist, if we look with meaning and thought, within any data space or platform—often to the detriment of women, queer, and racialized community’s histories. Speaking from the perspective of archival work, Lauren F. Klein suggests that

carework is the source of some of the most meaningful stories embedded in our archives…. [T]his belief is what we “digital antiquarians” might bring to the digital humanities writ large. Our attention to the margins of texts, to the gaps in our archives—we must ensure that these features are acknowledged, if not always fully reconstituted, as we chart the shift from physical to digital archival form. (Klein 2015)

In our making, we have taken this commitment very seriously to ensure that our research designs embrace practices of care that not only pay attention to but centre care work. Our attention to small data within feminist spaces is, for us, a method of care, in that it helps us get at the affective, embodied, everyday, undervalued practices that spaces often document and enable.

As a final example of making, we come to FTT’s first and longest-standing project: our Instagram account, @Aesthetic.Resistance, which is a direct response to this commitment. Positioned as a design intervention into prevailing Instagram culture (Wiens et al. 2020), the account offers a database of feminist historical and contemporary media practices and seeks to amplify perspectives and work that have been pushed to the margins. The project was designed with the intent of co-opting the functions of Instagram through a mode of creative research that “reflect[s] new social … realities either marginalized or not yet recognized” (Barrett and Bolt 2013, 4). Our research collective collaborates on the scope and focus of content produced for the account, taking turns as moderators who post on our areas of expertise and interest. Before posting we invite peer feedback from the group. This collaborative dimension of the project sets out a useful research model where joint responsibility for content creation requires us to reflect on our own positionalities, while also understanding our relationships to each other and our audiences. As a practice-based social media research project, our work with @Aesthetic.Resistance has built a collaborative community (and was the catalyst for the formal creation of Feminist Think Tank, which the account is now named). The act of creating and maintaining a social media presence as a collaborative group was powerful in developing a sense of connectedness—it is within these group dynamics that the research team found support and stepped up to be that support for others. In the face of dominant forms of social media that are attached to large corporate models of content production and capitalism, finding ways to intervene in small-scale, low-stakes projects is a key form of culture-jamming and counter-cultural practice.

Across the data jams and @Aesthetic.Resistance, we have sought to explore different approaches to “materializing data” (Wiens et al. 2020, 1) in order to advance a set of research encounters that encourage researcher collaboration and that, through such collaboration, slow down the miasma of online flows of information. A shared principle of qLab and FTT is to re-imagine what data can be from a social justice design perspective. For us, this includes producing small data-oriented research and methods that are grounded in iterative, embodied, collaborative thinking, talking, and making. We play with ways of materializing data so that we can reflexively engage with it in relational ways. Moreover, each of these projects are done in collaboration—with students, with each other, and with larger audiences. Ultimately, these data jams offered us space to speak with students about the influence of technology on their lives, which led to discussions of the increasingly faster pace of the university and the importance of the everyday relationships and conversations that can help us to remain tethered. This approach to the “everyday of data” is tied into our thinking on social media interventions, where (1) data can be anything and anywhere, but some types are privileged over others; and (2) there is always data that less valued and thus made invisible or erased. Both the data jams and @Aesthetic.Resistance demonstrate ways of developing intentionally feminist research practices that are located in the research scene and that index and archive data and digital media interventions over time. It takes a keen awareness of the guiding orientations of relationality and care to do this work, because it recognizes that personal and private spaces are as much sites of knowledge as public ones, and centres the aesthetic and the visual as vital to the study and representation of larger structural and cultural discourses of the digital. This sentiment around personal, public, and structural echoes across all our projects and research spaces and is the driving force behind the feminist shadow networks that keep us grounded.