Latina Data-Symbolic Language Brokers

By Luis Contreras, M.A., PhD student at Rutgers School of Communication and Information.

This research proposal was recognized as a Top Paper in the Latina/o Communication Studies Division and La Raza Caucus at the 111th Annual National Communication Association Convention, 2025.*

Abstract

This research proposal examines the future study of eldest Latina daughters who act as data-symbolic language brokers, individuals who translate, interpret, and navigate the semiotic structures of the internet on behalf of their immigrant families. Combining technical skill with fluency in digital symbols, icons, and interface cues, these daughters perform critical yet invisible labor that sustains household connectivity and access to essential services. Framed through the lens of immaterial and affective labor (Hardt, 1999), their work includes not only troubleshooting and document submission, but also the emotional labor embedded in supporting non-native English-speaking parents through digital bureaucracies.

Drawing from scholarship on infrastructural action (Nguyen, 2016), ghost work (Gray & Suri, 2019), and intersectionality (Crenshaw, 1989), this proposed study explores how their expertise is devalued due to the racialized and feminized domestic spaces in which it occurs. Using qualitative methods, including semi-structured interviews and digital ethnography, the project will investigate how eldest Latina daughters navigate dual literacies of technical skill and symbolic translation. It will also explore the implications of this hidden knowledge work on their identity, visibility, and social mobility. This proposal contributes to ongoing conversations on labor, race, and technology by making visible the affective and infrastructural dimensions of domestic digital labor. Ultimately, it seeks to reframe how we define technical expertise by centering the lived experiences of women of color in everyday technological life.

Keywords: data-symbolic language, Latina digital labor, immaterial work, infrastructural action, intersectionality

Introduction

A generation of data-symbolic language brokers, a role often designated to the eldest daughters of Latino households, possess not only the technical skills required to access, navigate, and interface with the Internet and internet technologies, but also the crucial data-symbolic language literacy needed to render the digital landscape readable. By “data-symbolic language,” I refer to the ability to interpret and translate digital signs, symbols, icons, and interface cues, nonverbal elements that structure how users experience and move through digital environments (Nakamura, 2013; Benjamin, 2023). Engaging in tasks such as translating, filing official government forms, and submitting tax and medical documents online, eldest Latina daughters balance a form of immaterial knowledge work (Hardt, 1999) when assisting their immigrant and non-native English-speaking parents with various tech-related matters.

Despite the significance of this digital knowledge work, the labor of data-symbolic language brokering often remains unseen. Parents tend to perceive the technical and web skills of the eldest daughter as second nature, assuming that her proficiency in navigating the Internet comes effortlessly. In contrast to the less visible knowledge work, the material labor performed by eldest Latina daughters is more conspicuous, yielding tangible and immediate results for household members. This includes instances like restoring a parent’s favorite soap opera stream on Netflix after executing a wireless router reboot. Consequently, the invisibility of the knowledge work makes it susceptible to inadvertent exploitation (Gray & Suri, 2019). Data-symbolic language brokering involves translating the intricate array of non-alphabetic symbols and icons that users decipher to navigate the Internet and interact with mediating technologies. Beyond the realm of internet signs and symbols, data-symbolic language extends to encompass knowledge of the UI (user interface) and UX (user experience) design universe (Nguyen, 2016). This layer of labor adds complexity to the duties performed by bilingual, often English-second language-speaking children of immigrants. It is critical to explore the implications of this exploitation of the immaterial knowledge work carried out by Latina daughters within the context of digital navigation skills and the digital divide.

The Dual Literacy of Eldest Latina Daughters

In the skills of eldest Latina daughters, a unique proficiency emerges as technical expertise blends seamlessly with a command of data-symbolic language. I focus on eldest daughters specifically because, within many Latino households, the role of caretaker, translator, and digital intermediary often falls to them, not merely by chance, but by deeply gendered expectations. This labor reflects what contributors in “This Bridge Called My Back” (Moraga, 1981) articulate as “the burden of being first,” where eldest daughters, particularly in immigrant families, are expected to shoulder both familial and cultural responsibilities. These expectations render their immaterial and affective labor both essential and invisible, a dynamic reinforced by their intersectional position as women of color navigating multiple systems of power. This skill set extends beyond the tangible act of interacting with interfaces, encompassing the intricate technical connectivity aspects.
For example, when a parent or household member encounters internet service issues, it is the eldest daughter who undertakes the task of resolving the problem, leveraging her knowledge of how to reboot the wireless router. In their role as data-symbolic language brokers, eldest Latina daughters also function as informal IT technicians, Wi-Fi internet servicers, streaming subscription customer service representatives, and more. As Nakamura (2014) suggests, this kind of racialized labor is often seen as a “labor of love,” making the digital care work of eldest daughters appear natural rather than skilled or technical.

Pushing beyond translation, this skill requires a keen ability to read and interpret data-symbolic language. The calculation and navigation necessary for even seemingly menial digital tasks demand a literate understanding of data-symbolic language and technical skills. Yet, amidst their capabilities, the data-symbolic language brokering skills of eldest Latina daughters remain less visible than their technical support skills. Their expertise in navigating the Internet across various domains is not readily apparent, and often inadvertently exploited. This exploitation is compounded by intersectionality, contributing to the erasure of Latina identity as valuable knowledge and technical workers. Despite being well-qualified for Silicon Valley career paths, they face challenges due to their intersectional identity. Intersectionality, as coined by Kimberlé Crenshaw (1989), highlights how overlapping systems of oppression, such as race, gender, class, and language status, combine to shape the unique experiences of women of color. In the case of eldest Latina daughters, their digital labor is often rendered invisible precisely because it exists at the crossroads of racialized, gendered, and familial expectations. These intersecting structures not only obscure their technical expertise but also limit recognition and access to formal pathways into tech industries.

 

Immaterial Labor and Affective Impact

Data-symbolic language brokering surpasses the tangible, embodying a distinctive blend of immaterial and affective labor. Framed by Hardt’s (1999) concept, this role is not merely a transaction of symbols but a profound engagement in two distinct yet intertwined realms of labor. Data-symbolic language brokering serves as a form of immaterial knowledge labor that provides translation of tactical information. Data-symbolic language brokering also involves more nuanced aspects in the type of languages it translates (interface and technical designs) along with affective results. The act of translating symbols and navigating interfaces by eldest Latina daughters is more than a technical chore; it provides an infrastructural need required by most households for economic survival (Nguyen, 2016). Simultaneously, the affective labor aspect, rooted in Hardt’s (1999) framework, permeates the emotional fabric of family interactions. The joy sparked by a resumed HBO MAX stream, the relief intertwined with completed financial forms, and the overall sense of well-being associated with successful document submissions are examples of the affective dimension associated with the technical and knowledge labor performed by eldest daughters. This demonstrates more than just technical proficiency, highlighting the emotional impact these daughters’ actions have on their family members. Moreover, affective labor extends inward, as the laborer shoulders the weight of digital tasks out of a genuine sense of love and care for her family. This intersection of immaterial and affective labor in Latina data-symbolic language brokering, as conceptualized by Hardt (1999), not only underscores their technical prowess but also the emotional intricacies interwoven into the digital and familial relationship.

The Unseen Expertise of Eldest Latina Daughters

The data-symbolic language brokering performed by eldest Latina daughters unveils a tale of expertise concealed amidst struggles for visibility. Their proficiency in deciphering the language of symbols and icons remains largely overlooked, a silent force guiding the digital interactions of their families. This expertise in data-symbolic language brokering, crucial for navigating the digital landscape, often goes unnoticed. While their technical support skills may shine through, the subtleties of their data-symbolic language literacy remain concealed. The invisibility of this expertise becomes a double-edged sword, as their labor is performed in the shadows, inadvertently exploited, and undervalued. This mirrors what Gray and Suri (2019) term “ghost work,” the hidden human labor that underpins systems presented as fully automated. Remarkably, this undervaluation is especially acute when the labor is performed by eldest Latina daughters, whose domestic settings are far removed from the expected professional sites of tech labor like Apple, Microsoft, or Samsung.

The exploitation of these invisible skills is particularly evident in navigating the Internet. Tasks like troubleshooting connectivity issues, recognizing phishing scams, and researching government benefits require a blend of linguistic, cultural, and digital literacies. Vicki Katz (2014) describes how children of immigrants often serve as brokers, not only of language but of institutional and media systems, filling critical gaps that adults in their families cannot navigate alone. For eldest Latina daughters, this brokering extends into digital infrastructures, where they construct pathways through bureaucratic and technical systems with little recognition. Nguyen (2016) introduces the concept of infrastructural action to describe the everyday, socially embedded labor involved in forging connections to global systems from positions of marginality. Like Vietnamese users who jailbreak phones to access digital networks, Latina daughters’ actions, resetting routers, filling out online applications, or managing benefits portals, are performances of technical care that sustain their families’ connectivity. Rather than transgressive tech-savviness, their digital labor is routinized, relational, and precarious. As This Bridge Called My Back (Moraga & Anzaldúa, 1981) reminds us, women of color are often expected to serve, and that service includes the often-invisible domain of technical navigation.

Decoding Data-Symbolic Language and the Functional Aesthetic

These dynamics reveal how technical expertise is not just undervalued but shaped by structures of race and gender. Lisa Nakamura (2013) has discussed how technologies can perpetuate racial biases, discrimination, and inequalities. Her work is crucial to understanding how the digital labor of Latina data-symbolic language brokers is devalued, not because it lacks skill, but because it is performed by racialized and feminized bodies in domestic, informal settings. Technologies, in this sense, do not operate neutrally; they mirror and reinforce existing hierarchies, making the invisibility of Latina labor a consequence of both social and technical design. She asserts that terms such as: online, file compression, hypertext link, and downloading are now part of the Internet user’s everyday vocabulary since they describe practices or virtual objects that lack analogues in either offline life or other media. The new modes of discourse enabled by the Internet require new descriptive terminologies and conceptual frameworks.

In the digital experience, not understanding this vocabulary has implications for everyday Internet usage, which manifests in the form of inaccessibility to the language and spaces of the digital for non-native speakers. This is not to say that Spanish-language instructions for installing, programming, interfacing with and navigating digital technologies do not exist. Instead, the implicit and underlying assumptions of digital maneuverability are not visible to readers who struggle due to a cultural-generational knowledge gap. An important aspect of the digital experience is that data-symbolic language communicates silently through a play of symbols and meanings. Symbols like the “x,” “+,” and “-,” which indicate the functions of maximizing, minimizing, and exiting a window are seamlessly integrated into web browsers. To complicate things further, these functions are represented as the colors: red, yellow, and green in the Mac operating system, adding another layer of complexity to the symbology of datafied media. Although the magnifying glass symbol on MacBook keyboards represents the search function, its meaning is not immediately obvious to those unfamiliar with this design language. An apt example is the ‘power’ button on the latest MacBooks, an unassuming symbol devoid of a clear function, relying on implicit knowledge of Apple’s design philosophy and broader technical and interface design principles.

 

Ruha Benjamin’s (2023) work in “Race After Technology” critically examines how emerging technologies perpetuate and amplify racial biases and inequalities. Benjamin argues that new technologies, and their design and functions, are not neutral but are embedded with social, cultural, and political values that often reinforce existing power structures and discriminatory practices. She discusses various examples to illustrate how algorithms, artificial intelligence, and other technological systems can encode and reproduce racial bias. As such, it is safe to assume that since inception, digital technologies have emerged and evolved without much consideration for English-second language and non-digital native readers. Another instance of emergent technologies that even further complicate matters is the surgency of haptic interface systems. Haptic systems play a crucial role in interfacing with smart technologies, extending their influence even to unexpected domains like cooking equipment and electric kitchen devices. Notably, the emergence of haptic technologies in the domain of the kitchen cannot be overlooked as a neutral phenomenon. As stated by Nakamura (2014): racialized labor is often portrayed as the “labor of love.” In this sense, the naturalization of intertwined nature of the affective labor of cooking is presented as an innate fit for Latina eldest daughters, all while at the convenience of their fingertips.

In the matrix of visual, audio, haptic, and aural experience that makes up the language of the Internet, understanding user-design aesthetic knowledge is utmost. This language, rich in symbols and meanings, lies at the core of user interactions, mediating experience. Thus, intuitively knowing the locations of minimize, maximize, and exit buttons across diverse web browsers and operating systems, interpreting icons, symbols, and emojis, and understanding data-privacy rights are embedded in the literacy skills of data-symbolic language brokers. Decoding data-symbolic language extends to understanding symbols like “🔋” or “🪫,” unscrambling their meanings and functions, providing data about the operational status of devices. Data-symbolic language literacy involves deciphering signs necessary for Internet exploration on various devices, operating systems, and interface features. In the context of language abstractions, this decoding includes interpreting weather icons to provide data about the user’s geo-temporal state and understanding English language abbreviations of months and days (e.g., “Sat Dec 19 ‘23”) as representations of the intricacy of this language. Decoding data-symbolic language requires unraveling this interplay of symbols, both aesthetic and functional, guiding users through the digital landscape with a nuanced comprehension of their meanings and contextual significance. However, it is this deeper comprehension that excludes non-digital natives, in this case the immigrant parents of Latina data-symbolic language brokers, in the first place.

Research Design

This study aims to explore the experiences of eldest Latina daughters functioning as data-symbolic language brokers, shedding light on the intersection of technical skills and data-symbolic language proficiency in their lives. Hence, this study will investigate the following: how do eldest Latina daughters navigate the dual literacy demands, integrating both technical skills and data-symbolic language proficiency, in their role as data-symbolic language brokers within their households? What are the implications of the exploitation of immaterial knowledge work, particularly in data-symbolic language brokering, on the intersectional identity and social mobility of eldest Latina daughters? Utilizing qualitative research methods, specifically face-to-face interviews, and digital ethnography, will provide a nuanced understanding of their roles and challenges. Conducting in-depth, semi-structured interviews will be central to capturing the rich narratives of eldest Latina daughters. These discussions will focus on unraveling their experiences, emotions, challenges, and proficiencies related to data-symbolic language brokering.

Additionally, exploration of their perceptions of visibility and the intersectionality of their identity will be a key aspect. Utilizing digital ethnography will enable observation and documentation of online interactions and activities associated with data-symbolic language brokering, particularly within group chats, social media platforms like WhatsApp, Instagram, or TikTok, and browser-based tasks such as navigating healthcare, educational, and government service portals on behalf of family members. This method will shed light on the digital spaces where these daughters operate, contributing to a comprehensive understanding of their technological engagement. Engaging in participant observation will provide valuable insights into the daily lives of participants. By immersing in their routines, this study aims to observe firsthand the tasks they perform, such as translating, navigating interfaces, and addressing technical issues. This approach will also facilitate the documentation of affective impacts on familial interactions. Purposeful sampling will guide the selection of participants, ensuring diversity in backgrounds, such as socioeconomic status, geographical location, and acculturation levels.
The goal is to achieve a sample size that allows for a deep exploration of individual experiences. Thematic analysis will be the primary method for identifying recurring themes and patterns in the interview transcripts and digital ethnography data. An iterative approach will be adopted, enabling ongoing refinement of themes and the emergence of new insights. Ensuring ethical research practices is paramount. Obtaining informed consent will be a priority, and participants will be made fully aware of the research goals and potential implications. Maintaining participant confidentiality and anonymity, especially concerning sensitive familial information, will be a core ethical commitment. This research design anticipates offering a nuanced understanding of how eldest Latina daughters navigate dual literacy demands and the affective and immaterial dimensions of their labor. Insights into the implications of the exploitation of their expertise on identity and career aspirations will be explored, providing a foundation for empowerment recommendations.

Empowering the Unseen Experts

In the intersection of technical proficiency and data-symbolic language literacy, a generation of unseen experts emerges: the eldest daughters of Latina households. These young women are entrusted with the role of guiding their families through digital systems, translating forms, submitting official documents, troubleshooting technology, yet the expertise they wield is often rendered invisible. While tasks like rebooting a router may yield immediate, visible results, the deeper work, interpreting digital cues, managing bureaucratic platforms, and safeguarding against online financial scams, remains overlooked. This labor constitutes a form of immaterial and affective labor (Hardt, 1999), entangled with care, emotional responsibility, and familial obligation. As Katz (2014) reminds us, immigrant youth often serve as vital brokers of complex systems, a role eldest Latina daughters take on in the digital realm. Their work echoes what Nguyen (2016) describes as infrastructural action, a set of delicate, ongoing practices that maintain socio-technical connection in the face of systemic gaps. This digital labor is not incidental; it is performative, relational, and essential.

The erasure of their contributions is further compounded by intersectionality (Crenshaw, 1989), where race, gender, class, and language converge to limit recognition and opportunity. As Moraga (1981) writes, women of color are often the first to break barriers, but also the first to carry the burdens of those breakthroughs. The expertise of Latina data-symbolic language brokers challenges dominant notions of who counts as a technical worker, pushing back against the assumptions that technological fluency belongs solely to professionals in corporate or academic spaces. To empower these unseen experts is to recognize their labor as legitimate, skilled, and vital. Their everyday actions build the digital infrastructures of their households and communities. Making their work visible is not only an act of acknowledgment, it is a necessary step toward dismantling systems of exploitation and reimagining who we consider agents of technological knowledge.

 

📧: luis.contreras@rutgers.edu

 

References