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“Learn to Code”: How One Meme Reveals Coding Literacy’s Gatekeeping Powers 
by Sophie Morgan, York University

Approximately 86% of individuals are literate around the world (Roser and Ortiz-Ospina). That is roughly six billion people who possess some basic reading and writing skills, such as being able to sign their name, read a sign, and understand a menu. Now imagine six billion people possessing a similarly basic knowledge of coding. Imagine a world where you had to sign your name using code. Imagine a world where everyone had to successfully complete a coding literacy test to graduate high school or even vote. Imagine a world where you are only free and powerful if you can program, and captive and powerless if you cannot (Rushkoff).  

This world is well on its way to becoming a reality, and some of the building blocks to do so are already in place. Dialogues about coding literacy began at least as early as the 1960s when several prominent computer scientists argued that coding should be taught like writing studies (Vee, “Programming as Literacy” 446). Now, contemporary calls for coding literacy are only increasing in volume and frequency. Apple has launched and expanded its “Everyone Can Code” curriculum, and Scratch and Code Academy work to teach children how to code through their mobile apps and games (see figs. 1 & 2).  


On trend with these efforts, journalists have been covering government efforts that encouraged coal miners and other blue-collar workers to “learn to code” as an alternate career path since 2014 when media attention focused on the decline of the Rust Belt (Don, “Learn to Code”). At this time, the statement “learn to code” was a coding literacy movement with the backing of governments, companies, and educators that promised economic success and an alternate career path. 

But, the catchphrase “learn to code” took a sinister turn after the massive journalist layoffs at Buzzfeed and Huffington Post in late January 2019. The phrase had made its way to 4chan—an anonymous online forum especially notorious for extremism, harassment, and trolling. More specifically, the phrase was widely shared on 4chan’s /pol/, or “Politically Incorrect,” message board, known for promoting extreme political ideologies. 

At this point, “learn to code” was no longer genuine. It became a text-based meme, similar to “Come at me, bro” or “Take my money!,” because it carried complex ideas as a unit of cultural transmission (Shifman 37-38). “Learn to code” was now used to mock journalists because many found it ironic that journalists were suggesting that coal miners learn to code as an alternate career path when they couldn’t do so themselves (see figs. 3, 4, & 5). The constant use of this meme in the form of text and images eventually developed into an anti-media harassment campaign beyond 4chan, and Twitter soon labelled any reference to “learn to code” as harassment (Don, “Learn to Code”). 


It’s easy to brush the “learn to code” meme off as the work of regular Internet trolls. However, when we examine it through the lenses of writing and literacy studies, we see that it is, in fact, a cultural artifact that reflects the changing definition of literacy. “Learn to code,” whether understood as a genuine literacy movement or a meme, acknowledges coding as a good and socially valuable skill that reflects the ideology of many discourse communities. It suggests that journalists, who are proficient in “old” reading and writing literacy, are losing their power in the job market and must adapt by learning a “new” literacy.  

In this article, I explore the social and cultural powers of literacy as it behaves in the context of coding and coding culture. By looking at the “learn to code” meme through writing and literacy scholarship, I show how what began as a real effort to help blue-collar workers morphed into online conflict about competency and literacy, inclusion and exclusion. First, I review the current scholarship surrounding literacy and coding. I then apply that scholarship to analyse two different examples of the “learn to code” meme and examine how they illustrate literacy’s gatekeeping powers. Finally, I discuss the future implications of my research.  

Literature Review 

Literacy Studies 
Traditional literacy, often known as reading and writing, is still very dominant in Western society. However, by broadening our view of literacy to incorporate activities beyond reading and writing, such as coding, we can better reflect current everyday skills and practices in contemporary society. This is a “Multiliteracies” perspective that recognizes that, “although the printed and written literacy is important, it is only one kind of literacy that makes meaning in a narrowed area” (Sang 17). In other words, individuals do more than read and write; they navigate between and benefit from traditional and coding literacies (among many other forms) in various social contexts. 

Numerous scholars have also explored the dynamic nature of literacy and how it tends to shift, develop and transition through stages over time (e.g. Baron, Brandt). Among these scholars is Annette Vee whose perspective on literacy is particularly valuable because she aptly compares reading and writing literacy to coding literacy through a historical lens and illustrates how coding is currently expanding to become an everyday skill. Through her discussion, we can better understand how traditional and coding literacies coexist and the role of literacy as a whole. Vee defines literacy as “widely held, socially useful and valued sets of practices with infrastructural communication technologies (Coding Literacy 27). She adds that literacy is a morally good, undefined concept that is attached to power, driven by ideology, and reflective of world views (27). In other words, she argues that an activity can be considered a literacy if it is perceived to be socially and ideologically good and valuable within a particular discourse community. Because literacy is also attached to power, those who are literate are also often powerful. 

While some literacy scholars have been invested in literacy’s promises of social and economic advancement as an unquestioned good, others have interrogated this function, arguing that this promise can be a myth (Graff) or even a force of exclusion, discrimination, disenfranchisement, and injustice (Stuckey). In Writing as Punishment in Schools, Courts and Everyday Life, Spencer Schaffner argues that “across a wide array of social domains, acts of writing and written text itself are seen not only as empowering, but also as imbued with power to discipline, shame, and control others” (1-2). He argues that if literacy has the ability to do good, then it also has the ability to do bad. One particularly powerful example of this is the racial disenfranchisement of Black voters through obscure voting literacy tests (Jones and Williams) and the discrimination against those not “fluent” in Standard Written English. Just as literacy can give someone power, it can just as easily take it away and be used to exclude. 

Just like “literacy,” coding is also a difficult word to define; it’s with good reason that writer and programmer Paul Ford was unable to contain his definition within a few pages (“What Is Code?”). Vee describes programming as the constellation of abilities to break a complex process down into small procedures. Programming includes the ability to express those procedures using the technology of code that may be “read” by a nonhuman entity. So, writing code requires the expression of hyper-explicit instructions, and reading code requires the translation of said hyper-explicit instructions (Coding Literacy 22). Vee affirms that coding is a form of literacy because it is a “socially situated, symbolic system that enables new kinds of expressions” (3). Coding is also socially inflected, built on textual literacy, and is currently perceived to be a social and ideological good that is connected to power (48, 52). 

Currently, coding promises individuals power, and social and financial success. But, since it is an emerging literacy, it can do good for those who possess the literacy and do harm to those who don’t. To code and achieve what coding promises, individuals must re-imagine their writing in hyper-explicit terms for a non-human audience because coding encompasses new ways of reading and writing that involve restructuring thought and writing processes. If individuals are unable to accomplish this, at its most extreme, they risk being ostracized, ridiculed, and potentially not being able to participate in society as others who are code-literate can (Rushkoff). 

Through an understanding of coding literacy’s dynamic relationship with traditional literacy, we are better prepared to question and examine how they cohabit, how coding literacy expands as a literacy, and how it is both taught and perceived. Through these steps, we can potentially avoid recreating past injustices and exclusionary practices. 

“Learn to Code” Case Studies 

The Uncomfortable Relationship Between Elitism & Coding Literacy 
One instance in which the “learn to code” meme reveals coding literacy’s gatekeeping power is in a crossover meme with Evil Kermit (see fig. 6). 

Fig. 6. Good Kermit represents coders’ outward appearance and beliefs while Evil Kermit reveals the true sentiments of toxic coding culture.

The image for this meme is from the 2014 Muppets Most Wanted movie in which Kermit meets his evil, cloaked doppelganger, Constantine, who frames him for Constantine’s crimes (Don, “Evil Kermit”). For a wide range of topics, this meme depicts a dialogue between Good Kermit and Evil Kermit, which represents the tension between the “good” and “evil” sides of an individual’s conscience. Evil Kermit can be used any time an individual has an internal moral conflict (see figs. 7, 8 & 9.). 


Good Kermit states a positive perception while Evil Kermit reveals the uncomfortable truth or desire. For instance, @aaannnnyyyyaaaa, who was the first to use Evil Kermit as a meme, outwardly suggests that they simply like the fluffy dog, but their desire to steal the dog is the uncomfortable, secret truth.  

This dynamic excellently mirrors the current state of coding literacy. In general public consciousness and thanks to governments and enterprises that promote it, coding as a literacy is perceived to be inclusive, but in reality, it is exclusive; this is an uncomfortable inner conflict. This is why it is Evil Kermit, not Good Kermit, who says the elitist, unpleasant statements about coding literacy and sarcastically suggests that journalists “learn to code.” Individuals like Good Kermit may virtue signal to be perceived as good, but the unsettling conflict is that coders who are like Evil Kermit are not supportive of journalists, nor do they feel sympathy for them or want them to learn how to code. Coders who are like Evil Kermit are, in fact, intentionally excluding, belittling, and disrespecting those who traditionally cannot code, those who are not as “powerful” or “elite” because they are not fluent in a “new” literacy. 

As a result, we can interpret “learn to code” as a sarcastic statement that mocks journalists for not being able to code and silences their concerns about being laid off. “Learn to code” is an empty gesture that taunts journalists and humiliates them for their supposed lack of awareness and skill. Only proficient in “old” literacy, journalists are now ridiculed for both suggesting that miners learn to code and for being unable to code themselves.  

In addition to revealing conflict between coders and journalists, this meme points to numerous larger issues. Firstly, “learn to code” brings up questions about elitism that are related to but extend beyond literacy. Coders who share this meme are likely motivated to promote it because it offers the opportunity to question traditional sources of information that are in the form of “old” literacy and tend to influence general public opinion. These beliefs align with the “politically incorrect” ideologies pervasive on the /pol/ message board. Because these individuals are promoting a view that is not widely accepted and because great value is still placed on traditional literacy, it is Evil Kermit, rather than Good Kermit, who does the questioning. From this perspective, this phrase is more than a simple comment about literacy skill; it encompasses ideas about power structures in society, who should be considered “elite” and why, and who should be responsible for propagating information.   

Additionally, this meme points to a larger dispute between “old” and “new” literacy as perceived in public opinion. In this instance, those who are code-literate are excluding and disparaging those who are not.  

These two conflicts exist for two, interdependent reasons. First, the definition of literacy is unstable because it is starting to consider coding, in addition to reading and writing, as a socially valuable and good skill, leading to debate over who really has power. Second, because of this power dispute stemming from instability, new-literate individuals feel that this power entitles them to exclude old-literate individuals, furthering more conflict.  

However, such ideas about coding literacy are not bound to this meme, 2019, or journalism. They extend into broader coding culture and coding history. It’s important to recognize that this disempowerment and exclusion of journalists is as apparent as it is because of how coding and coding literacy have been understood and perceived historically. In the mid-twentieth century, coders were believed to be born with the gift to code well because businesses heavily relied on coders’ individual skills (Ensmenger 80-81). And not only were they chosen to code at birth, but coding itself has even been compared to the closest activity to perfection that man, who is not used to being “perfect,” can accomplish (45). These entrenched values placed coders and their technical expertise on a pedestal, creating an incentive to preserve the coding culture and to exclude others. In the next section, I build upon historically entrenched ideas of who should be a coder and how this perception affects our understanding of who should participate in coding literacy.  

The Uncomfortable Relationship Between Identity & Coding Literacy 
We can further understand the exclusionary powers of “learn to code” and coding literacy by extending and connecting this phrase to identity, status, and gender, concepts with which “The 37-Year-Old Laid Off Journo” meme (see fig. 10) engages. 

Fig. 10. This illustration depicts an imagined stereotype of a laid-off journalist according to those who posted and shared it.

Although visually different from Evil Kermit, this illustration was also a part of the 2019 anti-media harassment campaign targeting laid-off Buzzfeed and Huffington Post journalists. 

It depicts a cartoon drawing of a journalist who has not been confirmed to exist in real life and is styled to exhibit the negative, stereotypical characteristics of a “liberal” journalist. Among the obviously offensive phrases, such as “smells of cat litter,” are explicit attacks on intelligence and literacy skills. 

For instance, this meme not only suggests that journalists are code-illiterate by stating that they “can’t code,” but also that they are Internet-illiterate as they think that “all frogs are Pepe.” Their intelligence continues to be disparaged when the meme states that journalists use “Harry Potter books for life metaphors,” which proposes that journalists are not capable of any deep thought beyond what is in a children’s book. Lastly, since journalists are presented as having a “useless Gender Studies Degree,” this stereotype promotes the idea that any education that journalists might have, especially one related to social justice and equality, is insignificant. 

Unlike the other images circulated in the 2019 “learn to code” discourse, this meme uniquely reveals the relationship between identity, gender, and coding, which are all deeply embedded into the history of coding literacy. Although this meme reflects the current masculine culture of programming, the first programmers were, in fact, women. They were known as the original “human computers,” female machine operators who completed low-level mechanical work as per the instructions of male coders (Ensmenger 14-15). As programming became a professionalized industry, it became male dominated for many reasons, including aptitude tests that privileged male characteristics and typical male educational experiences (64, 68). This, in addition to the already historically pervasive elitism, contributed to the masculinization of computing professions and the exclusion of women (77), which are still observable today and visible in the “learn to code” conflict. As a result, this meme reinforces heteronormative gender roles and patriarchal structures present in a variety of disciplines, including coding and journalism, and privileges the experiences of white, male-gendered individuals. 

Because coding’s history is rooted in not only exclusion, but also gender, identity, and questions about who is allowed to be a coder, so is coding literacy. This largely explains why many of the attacks have been on women in journalism. Another one of these attacks was in a “Learn to Code-Virgin vs. Chad” crossover meme (see fig. 11), which was also shared during the 2019 anti-media harassment campaign.  

Fig. 11. Likely inspired from “The 37-Year-Old Laid Off Journo” meme, this spin on the “Virgin vs. Chad meme” suggests that female journalists are inferior to coal miners and cannot code because of their identity.

Typically, this meme, which also originated from 4chan, is used to disparage “virgin” men by comparing them to their more confident, masculine “Chad Thundercock” counterparts (Don, “Virgin vs. Chad”). In this case, the meme is combined with the “learn to code” conflict, and the “virgin” is a female-gendered journalist who is ridiculed as being weaker, lonelier, more sensitive, and less intelligent than coal miners. Once perceived as literate and educated, journalists, and in particular female-gendered journalists, are ridiculed for their femininity, education, status, gender, identity and supposed inability to code. Again, we see “learn to code” as a sarcastic statement meant to taunt, mock, and exclude code-illiterate women and individuals. 

In all of these memes and more, we can clearly observe coding literacy’s exclusionary and gatekeeping powers that are the result of literacy’s current instability, literacy’s inherent nature to do both good and bad, and the elitist, sexist beliefs entrenched in coding’s history. These uncomfortable ideas are revealed by Evil Kermit and result in “learn to code” being a sarcastic, unwelcoming statement toward code-illiterate individuals. “The 37-Year-Old Laid Off Journo” meme further specifies the harassment and illustrates that it is moreso targeted toward women, which in turn, also brings in questions about gender, status, identity, and who is allowed to be a coder. All while coding is emerging as a literacy, journalists are mocked by and isolated from the coding community because they are code-illiterate. Although some coders on the surface may virtue signal, in reality, they are actively participating in gatekeeping through sarcastic, passive aggressive behaviour to “protect” their literacy and prevent others from becoming code-literate. 

The “Learn to Code” meme and its historical roots show us the various sides of literacy in the context of coding culture. Although coding literacy promises personal and financial success, it also excludes and disempowers those who are code-illiterate. Knowing this, as literacy and writing studies students and scholars, we should ask ourselves: How is the definition of literacy changing? How do old and new literacies co-exist? How are we bringing our understanding of the benefits and issues of traditional literacy to new literacies? How are we promoting or challenging the idea that coding literacy is an unquestioned good? 

We must all remember and recognize the uncomfortable nature of literacy. Just as it was popular belief that traditional literacy was an unquestioned good, it is now popular belief that coding literacy is an unquestioned good. Just as individuals have experienced linguistic injustice and have been told “learn to write,” individuals are experiencing exclusion and harassment and are being told “learn to code.” Those who are not literate in a particular symbolic system continue to be disempowered. Literacy gatekeepers continue to actively seek to exclude the illiterate, and sponsors of literacy continue to “develop, exploit or suppress people’s literacy and gain economic or political advantage by doing so” (Brandt 6). The state and powers of literacy have not changed, but we can all still react to its changing definition. 

Literacy and writing studies scholars and educators can offer a multidisciplinary approach that redefines the problem of illiteracy and re-imagines what we already know about literacy to effectively help coding transition into a mass literacy (Vee, Coding Literacy). Writing studies and undergraduate students have a role to play as well. Whether we want to be journalists, scholars, or any writer in between, we offer a unique rhetorical point of view on communication. We understand what it means to write in different modes, and we can bring our writerly perspectives, knowledge, techniques and open-mindedness to question, examine, and contribute to our workplaces, to our classrooms, and to discussions about coding literacy as it continues to transform. 

Works Cited 

Baron, Dennis. “From Pencils to Pixels: The Stages of Literacy Technologies.” Passions Pedagogies and 21st Century Technologies. Ed. Gail E. Hawisher and Cynthia L. Selfe. University Press of Colorado, Utah State University Press, 1999. 15-33. Jstor. Web. 1 June 2020. 

Brandt, Deborah. “Introduction: The Rise of Mass Writing.” The Rise of Writing: Redefining Mass Literacy. Cambridge: Cambridge UP, 2014. 1-15. Print. 

Don. “Evil Kermit.” Know Your Meme. Know Your Meme, 2017. Web.  6 June 2020. 

______. “Learn to Code.” Know Your Meme. Know Your Meme, 2019. Web. 20 May 2020.  

______. “Virgin vs. Chad.” Know Your Meme. Know Your Meme, 2017. Web. 24 August 2020. 

Ensmenger, Nathan L. The Computer Boys Take Over: Computers, Programmers, and the Politics of Technical Expertise. Cambridge: The MIT Press, 2010. Print. 

“Evil Kermit Image Gallery.” Know Your Meme. Know Your Meme, 2017. Web. 6 June 2020. 

Ford, Paul. “What Is Code?” Bloomberg 11 June 2015. Web. 24 May 2020. 

Frank’s Laboratory (@code_laboratory). “Check out my latest #creativecoding video where we learn #HTML5 canvas basics and build simple vanilla #JavaScript project 🙂 #generativeart #learnjavascript #learntocode #codingisfun #codeart #FrontEndFriday #FrontEnd  #100DaysOfCode #CodeNewbie #html.” 17 August 2020, 7:16 AM. Tweet. 

Graff, Harvey J. The Literacy Myth. New York: Routledge, 1991. Print. 

Jones, Natasha N. and Miriam F. Williams. “Technologies of Disenfranchisement: Literacy Tests and Black Voters in the US from 1890 to 1965.”  Technical Communication Online: Journal of the Society for Technical Communication 65.4 (Nov. 2018). Web. 10 Aug. 2020. 

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Rushkoff, Douglas. Program or Be Programmed: Ten Commands for a Digital Age. New York: OR Books, 2010. Print. 

Sang, Yuan. “Expanded Territories of ‘Literacy’: New Literacies and Multiliteracies.” Journal of Education and Practice, vol. 7, no. 7, 2018, pp. 16–19. ISSTE, 

Schaffner, Spencer. Writing as Punishment in Schools, Courts & Everyday Life. Alabama: The University of Alabama Press, 2019. Print. 

Shifman, Limor. MIT Press Essential Knowledge: Memes in Digital Culture. The MIT Press,  

Stuckey, J. Elspeth. The Violence of Literacy. Boynton/Cook Publishers, 1991. 

Vee, Annette. Coding Literacy: How Computer Programming Is Changing Writing. MIT Press, 2017. Print. 

______.“Programming as Literacy.” The Routledge Companion to Media Studies and Digital Humanities. Taylor and Francis, 2018. Web. 

[u/deleted]. “virgin laid off journalist vs Chad laid off coal miner.” r/virginvschad. Reddit. 2019. Web. 24 August 2020.< _chad_laid_off_coal/>. 

Sophie Morgan is a fourth-year Professional Writing and French Studies student at York University in Toronto, Canada. Since 2019, Sophie has worked as a research assistant and a Peer-Assisted Study Session Leader for courses in the Writing and French Departments. Her research interests include applied linguistics, literacy studies, and writing studies. Most recently, she has presented major research projects examining embodied writing experiences and the role of virtual resources in second-language acquisition. Next year, Sophie hopes to begin her Master’s degree in Education to further her understanding of her research interests and pursue her scholarly passions. 

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