Programmatic Shifts in Technical Writing from 1965-2012: A Genre Analysis of Job Postings in the MLA Job Information List

The Modern Language Association (MLA) has published job postings of academic positions in the humanities since at least the 1960s. The Job Information List (JIL) available on the MLA website provides an archive of postings in .pdf format from 1965 until 2012 when MLA began using a database for postings. Jim Ridolfo downloaded all PDFs in 2014, used OCRkit to make them searchable, and generously shared a .tar of the OCR’d files online. This data presents an incredible corpus for understanding job market trends, changes in academic cultures, organizational values and practices, and disciplinary shifts.

Genres can both restrict power and simultaneously invest audiences with power. Genres do change, and individuals are afforded with a degree of agency in shaping those genres over time. Following the work of Swales and Rogers (1995), I am “…interested in genre development as an ‘embedded social process’, and one which concomitantly both shapes and reflects organizational attitudes and behaviors” (p. 225). An analysis of job postings, then, requires careful consideration of this genre as one that represents a core set of values and practices within academic contexts in the humanities. The JIL tells just one of many different stories, and my analysis of this genre will reveal just one of many stories told the field over a period of decades. Further, Carolyn Miller (1984) has argued that arguments about genre have too long been focused on substance and form as opposed to rhetorical action. Through an analysis of the JIL, I hope to reveal the evolution of the job post and the way writing program administrators, hiring committees, and professors have asserted a degree of agency in articulating needs, characteristics, and desired traits of potential faculty members.

Through this project, utilized the OCR’d files to investigate shifts and changing emphases in technical and professional communication job postings. This analysis, I hope, will reveal more about the changing market contexts for professional and technical writing, pedagogical responses to those shifts, and the evolution of programs that seek to prepare professional and technical writers to be proficient and rhetorical in the industrial and academic workplaces they serve. Further, this analysis also has the potential to reveal more about the place of technical and professional communication instruction within English departments.

To explore these phenomena, I first exported the OCR files into .txt files (with one text file per year from 1965-2012). My next step will be to use a command line to identify set terms (i.e., technical writing, professional writing, business writing, document design, information design, interaction design, and visual rhetoric) for each year, quantify that data, and represent the data in the form of histograms. While these methods will expose patterns and trends of terms and their use temporally, I do not wish to ignore the broader context and environments that influence the use and deployment of jobs that include such terms.To provide a stronger contextual background, I used bibliometric data from three technical communication journals from 1975-2015. This data set allows me to draw comparisons between the job market and published research over time.

In this post, I present this work in progress to gain valuable feedback and learn from others about the tools, skills, methods, and approaches that will truly enrich this study and objectively represent the data collected.

 

Research Questions

  • How can tracing genres over time tell more about cultural values and practices in the field of technical communication?
  • How have writing program administrators, hiring committees, and professors asserted a degree of agency in articulating needs, characteristics, and desired traits of potential faculty members?
  • To what degree has academic research in the field of technical writing impacted desired traits in faculty members?

 

Tools

 

Part 1: Using Voyant with MLA Job List Data from 1965-2012

My first corpus was gathered from OCR’d PDFs of the MLA Job List. Jim Ridolfo OCR’d these files and made them freely available, and I’m working from those texts here. I then converted these PDFs into text files. Unfortunately, the older text files (namely 1990 and older) required substantial time to be cleaned up (there were a number of spaces, unusual characters, and formatting that did not match up to the PDF). To remedy this issue, I worked through each posting and learned up the text files manually so those files looked as close to the PDF file as possible in the original.

A job post (1968) for an assistant professor at the University of Michigan College of Engineering.

A job post (1968) for an assistant professor at the University of Michigan College of Engineering.

 

A text file that was exported from the same job post above. Unnecessary spaces are placed between several characters and the word rhetoric is misspelled.

A text file that was exported from the same job post above. Unnecessary spaces are placed between several characters, several words have been omitted, and the word rhetoric is misspelled.

I selected one job post from each year’s version of the MLA job list that included the term “technical writing.” These posts were selected randomly, and whenever possible, I chose to include job titles that were specifically for assistant professor positions in professional and technical writing.

I created a text document that was essentially a master file of one technical writing job posting from 1965-2012. I uploaded this document to the browser-based text analysis tool, Voyant (http://voyant-tools.org). Voyant allows for the creation of text clouds, key terms in context, and the creation of graphs.

Using Voyant, I utilized the graph tool to find information for the words “writing,” “communication,” and “design.” From this, I learned that design had gained significant traction over the years, and I knew that I needed to rethink my strategy so I could learn more about this pattern.

 

A graph that represents the relevancy of the terms "writing," "communication," and "design" in the Job List corpus I gathered. This graph represents 10 plots for each term used.

A graph that represents the relevancy of the terms “writing,” “communication,” and “design” in the Job List corpus I gathered. This graph represents 10 plots for each term used.

 

A graph that represents the relevancy of the terms "writing," "communication," and "design" in the Job List corpus I gathered. This graph represents 5 plots for each term used.

A graph that represents the relevancy of the terms “writing,” “communication,” and “design” in the Job List corpus I gathered. This graph represents 5 plots for each term used.

 

Lastly, I decided to count the number of words in each job post I selected to see if there was any pattern of this genre increasing in length over time. This information will be posted soon (I need to find out how to create a useful table/graph for this representation). However, there was a steady increase in length, with 2012 representing the longest length in the job data.

 

Part 2: Using VOSviewer to reveal bibliometric data from 1975-2015

I then went to the Web of Science Core Collection database, which allows users to search journal titles, abstracts, and citations and export them into text files.

For this project, I selected the three following journals on Web of Science:

  • Technical Communication 
  • Journal of Technical Writing and Communication 
  • Journal of Business and Technical Communication

I then saved all the text files available from these results (3,761 total), with articles ranging from the years of 1975-2015. I went ahead and saved another file that contained only research articles, review articles, and conference proceedings (this corpus had 1,312 total results). Later, I used VOSviewer to visualize the corpus. VOSviewer (http://www.vosviewer.com) is an open source visualization tool created for bibliometric networks, developed at Leiden University, The Netherlands. Using the text corpus I gathered from the journals on Web of Science, I utilized VOSviewer’s features in an attempt to find patterns. The results are provided below.

 

A VOSviewer network visualization that represents terms included in the journal corpus. The terms that have more connections with others are larger (such as guide, technical writing, and student). This graphic represents the average month and year of each term's use as well. Terms used in the corpus (range 1975-2015) are represented on a color scale. Blue indicates older use, whereas red indicates recent use. The term "technical writing" is light blue, whereas "design" and "web" are closer to red. "Usability" appears to be the darkest red node in the network.

A VOSviewer network visualization that represents terms included in the journal corpus. The terms that have more connections with others are larger (such as guide, technical writing, and student). This graphic represents the average month and year of each term’s use as well. Terms used in the corpus (range 1975-2015) are represented on a color scale. Blue indicates older use, whereas red indicates recent use. The term “technical writing” is light blue, whereas “design” and “web” are closer to red. “Usability” appears to be the darkest red node in the network.

 

A VOSviewer density visualization that represents the density of terms used in the journal corpus. The terms "design" "guide" "student" and "technical writing" appear in red (high density) whereas low density terms appear to the outside in green.

A VOSviewer density visualization that represents the density of terms used in the journal corpus. The terms “design” “guide” “student” and “technical writing” appear in red (high density) whereas low density terms appear to the outside in green.

Bibliometric Set 1 (images above)

3,761 results

All article and section types

Journals Included:

  • Technical Communication
  • Journal of Technical Writing and Communication
  • Journal of Business and Technical Communication

Years of articles: 1975-2015

 

Term: design

No. of occurrences: 253

Score: 2005.39

 

Term: technical writing

No. of occurrences: 192

Score: 1989.51

 

Term: technical communicator

No. of occurrences: 134

Score: 2003.12

 

 

A VOSviewer density visualization that represents the density of terms used in the second journal corpus. The terms "technical communicator" "purpose" "student" "technical writing" and "writer" appear in red (high density) areas, whereas low density terms appear to the outside in green. The red areas appear to be much more diversified compared to the first journal corpus, is more centralized, and the areas come very close to forming a full circle of red with green inside it.

A VOSviewer density visualization that represents the density of terms used in the second journal corpus. The terms “technical communicator” “purpose” “student” “technical writing” and “writer” appear in red (high density) areas, whereas low density terms appear to the outside in green. The red areas appear to be much more diversified compared to the first journal corpus, is more centralized, and the areas come very close to forming a full circle of red with green inside it.

 

The red group, centered on the nodes "technical communicator" and "purpose" represent the research process and research methods in the field. Nodes in this network include "participant," "study," "data," "survey," and "user," among many others.

A VOSviewer network visualization that represents terms included in the second journal corpus. The terms that have more connections with others are larger (such as technical communication, technical writing, and student). Using color (blue, green, and red) his network represents groupings of the terms based on their connections to nodes in the network.

Bibliometric Set 2 (images above)

1,312 results

Research articles, proceedings, and review articles (no book reviews, front matter, editorials, or other pieces)

Journals Included:

  • Technical Communication
  • Journal of Technical Writing and Communication
  • Journal of Business and Technical Communication

Years of articles: 1975-2015

 

Term: technical writer

No. of occurrences: 33

Score: 1992.24

 

Term: technical communicator

No. of occurrences: 117

Score: 2003.51

 

Term: technical writing

No. of occurrences: 107

Score: 1987.50

 

Term: technical communication

No. of occurrences: 151

Score: 1999.76

 

Conclusion/Analysis

I unfortunately haven’t gotten to the analysis phase of this project. However, as the data shows, use of the terms technical writing and technical writer peaked in the late 1980s and early 1990s. They haven’t fallen out of use, however. The use of technical communicator and technical communication have seen more recent use, with them peaking in the late 1990s and early 2000s. A significant question the data raises is why the word design did not appear in the second journal data set, especially after seeing such an increase in use in both the first journal data set and the MLA Job List. I will need to go back and look at the bibliometric data and the articles included in that data set to learn why this has occurred. However, this could be a very important finding. This could indicate that design is a term more often used in the practice and teaching of technical writing, while the research in the field of technical writing has not emphasized design.

I think the most significant finding from my research thus far is represented in the final VOSviewer network visualization of the second journal corpus. Each group in this network, to me, represents a very different emphasis and influence in the discipline. For instance, the blue group with the term “student” is surrounded the pedagogical and programmatic nodes in the network, such as “course,” “instructor,” “professional,” and “discipline.” The green group, centered on the node “technical writing,” is surrounded by nodes like “rhetoric,” “style,” “reader,” “book,” “writer,” and “narrative.” I suggest that this group represents the influence of English Studies and textual criticism on the field of technical communication. The red group, centered on the nodes “technical communicator” and “purpose” represent the research process and research methods in the field. Nodes in this network include “participant,” “study,” “data,” “survey,” and “user,” among many others. This network illustrates the ways that terms and language, throughout the history of technical writing pedagogy and research since 1975, are often associated (or not associated) with others. For instance, this network can illustrate not only disciplinary influence and history, but also be a call for more research that is connected to technical writing pedagogy (though nearby, the research process and pedagogy groups appear to have few connections according to the visualization).

Another finding worth mentioning is how the job post has seen a steady increase in word count from 1965 to 2012. This could very well indicate how the field has steadily gained legitimacy as a field in its own right as opposed to a teaching obligation of English faculty. Foucault noted that disciplining is a process aimed at limiting freedoms of individuals and also a way of constraining discourses. In other words, disciplines are barriers to free thinking and place a significant burden on subjects. Working within the discipline of English Studies, it seems clear to me that technical writing has slowly progressed to legitimize itself within that discipline, and even gain traction to some as a discipline in its own right. Like English, it has benefited from the rich perspectives of other disciplines, like cultural studies, cognitive psychology, and science and technology studies. More research is needed to respond to the question of agency. The job postings may represent how hiring committees have asserted a degree of agency, but they may also tell a story of struggle and legitimacy.

 

References

Foucault, M (1988). Technologies of the Self, in: L.H. Martin, H. Guttman and P. Miller (eds), Technologies of the Self, Amherst, MA: University of Massachusetts Press.

Lauer, C. (2013). “Technology and Technical Communication Through the Lens of the MLA Job Information List 1990–2011.” Programmatic Perspectives, 5(1), 4-33.

Miller, C. (1984). Genre as social action. Quarterly Journal of Speech, 70, 151-167.

Rude, C. & Cargile Cook, K. (2004). The academic job market in technical communication, 2002-2003. Technical Communication Quarterly, 13(1), 49–71.

Swales, J., & Rogers, P. (1995). Discourse and the projection of corporate culture: The mission statement. Discourse & Society, 6(2), 223-242.