You hear it proclaimed everywhere in writing manuals, “know your audience.” But what does this mean? It is certainly as complex, and perhaps deeply related to, the Greek proverb “know thyself.” Even knowing that only your professor is going to read your paper, you still need to consider: how much access do I have to the variety of beliefs that inform their judgment? There are the general “no no’s” we have learned from our teachers over the years – an authoritative audience who communicated their preferences with dashes and checkmarks, teaching us proper grammar and spelling, to remove passive voice, vague phrases, and unsupported assertions etc. Then there are the more subtle values which gain in prominence as we climb each rung of the education ladder: the conventions of your field, fulfilling a gap in that field, your professor’s knowledgeability regarding common terms in that field. This leads us to step out further, considering the other works for which your professor is the audience and the performer: the current trends in their field, seminal works, the valid research methods and assumptions which set the groundwork for inquiries related to their own work. The consumingly social “know thy audience” begins to rear its hydra heads in every aspect of our writing process. Our audience has an audience as well, and it is in this community of watching, relating, confirming, and denying that we attempt to speak in a way that will be persuasive to those audiences. In nervous self-consciousness, in feeling a will to somehow satisfy all those audience members that sit in the theater of our judgment, we write to persuade a group of what we want (an A+, proof of concept, social change) by appealing to what they want.

It is with these considerations in mind that leading academic composition researcher John Swales has highlighted the centrality of genre for academic writing. For Swales, “genres are [the] communicative vehicles for the achievement of goals” (1990, p. 46), the agreed upon forms (the how’s) that a community believes best achieves their goals (the what’s). They are the linguistic means to a community’s given ends. In the social sciences, the genre changes by the common goals of a discipline or subdiscipline: where the social phenomenologist may seek to explain social behaviour through interpretation (connection of the particular and general context), and the positivist sociologist attempts to reduce that behaviour to a common, functional act that is corroborated by other contexts. This results in communities of scholars who develop different methods, terms, and outlooks in learning and responding to their topic. When we “address” these scholars, we should appeal to the common goals and history which underpins their discourse, even when we seek to “redress” those very ends. It is with “know thy audience” in mind that we have decided not to only provide you a set of writing tips in general, but to direct your attention to some major communicative vehicles and purposes that validate good social science writing.

Picking the Right Genre

But before learning the subtle styles of your genre, you first have to be certain of having picked the right genre (El-Masri & Wasylyshyn, 2018). Think of the genre as the larger environmental milieu which your work intends to thrive (or survive) in. If you are attempting to get your research published, then it is important that you find the right journal for your work. Seek out a journal that highlights the same methodology (qualitative, quantitative) or topic (economic sociology) and read their guidelines. The guidelines will provide you the basic rules and word limit for their publications, but not the subtle cues involved with the style of writing they expect. Looking at other publications in the journal will help you there; but lacking a step-by-step explanation of their writing intentions, junior researchers often miss some key cues. That is where further reading into the rules of the genre can come in handy. We will attempt to highlight some while also offering references for further reading. Refer to Chapter 13 (Publishing Your Research) for more details about this process.

Quantitative Writing

This section begins by drawing on some guidelines offered by Maher El-Masri and Susan Fox-Waslyshyn (2018) -both seasoned academic editors and reviewers. Each has been responsible for many acceptances and rejections of quantitative articles received for publication, and have offered the following insights to help writers succeed:

• For quantitative articles, the methods section is usually the key grounds of contestation. That is because quantitative works emphasize establishing replicable, common facts that can be found by another researcher using the same procedure. Hence, the facts you discover hinges on the integrity of your procedure. This means that your writing must be clear and thorough in this section, able to quickly enunciate abstract procedures and situate them in the context of your study. El-Masri and Fox-Waslyshyn (2018) unpack this with a long set of solid recommendations, we suggest looking at the link in the bibliography for more.
• Unlike qualitative and interpretive research, the results section of quantitative research aims to present findings without any discussion or explanation (Pierson, 2004; El-Masri & Fox-Waslyshyn, 2018). This likewise implies that the presentation of findings ought to be as concise and straightforward as possible. At this point, you have already unpacked your procedures and hypotheses, so merely begin by stating a description of the sample characteristics before providing the findings. Any reporting of findings unrelated to your research question and hypotheses is discouraged (El-Masri & Fox-Wasylyshyn, 2018).

What this all hints at is elaborated in Fallon’s (2016) book on quantitative research writing in the social sciences: “quantitative research is a ‘top-down’ process” (p. 3). This top-down conceptualization is a vital difference between quantitative research, qualitative and interpretive research. This is especially important in the data analysis section, where you must efficiently communicate the findings and the methods used for them. The better you have clarified the constructs used in your methods (such as Pearson’s R), the clearer the plausibility and significance of your findings.

Top-down means that you begin writing by stating hypotheses and the constructs used to evaluate those hypotheses before gradually moving to the findings (the bottom of Fallon’s abstract knowledge pyramid) (Fallon, 2016, p. 15). It suggests the drive in quantitative research of connecting particular findings to a general theory by way of a methodological theory. Writing quantitative research therefore follows the order of deductive reasoning: it elaborates a theory and a set of hypotheses, then counts findings that validate or invalidate the general theory (top-down/theory-finding). Articulate this narrative to increase the persuasive force of your quantitative writing. Take a generalization or theory that is important to the field, clarify a population and method capable of evaluating its validity, then prove or deny the validity of that theory through your findings. By sharing a common methodology and topic area, quantitative disciplines will scrutinize the clarity of your deductive reasoning. It is your goal to surpass this scrutiny by moving from an appropriate theory to topic to method to findings back to theory.

Once the methodological apparatus is properly conveyed, then your data analysis should clearly follow. Unlike qualitative analysis, where interpretation and analysis of the findings can take place extensively (since a strict deductive logic system has not been established), it is more common in quantitative writing to be quick and concise in your findings. According to Fallon (2016), the findings section has three rhetorical goals:

1. Describe the data
2. Figure out if the variables you studied are related to the population
3. Determine if the relationship between your variable and your population is significant

Your writing should attempt to quickly offer descriptions of your data, determine if those variables are related to the population, and then determine if that relationship is significant (through a test of statistical significance that matches your study). The faster you are able to relate large swathes of data to your hypothesis the better.

As the findings section aims to be sparse, it is the discussion section where the key persuasive movement of your paper will be made: it is where you connect your findings back to the treasured theories of your discipline. But alas, the discussion is often the weakest component of the research manuscript (Perneger & Hudelson, 2004). In quantitative research, this will undermine much of the meaning of your research. El-Masri and Fox-Waslyshyn (2018) suggest that this is often because quantitative researchers are prone to overgeneralizations that are not supported by the findings. Yet, on the other hand, making generalizations is a key component of quantitative and formal methodologies in order to gauge their significance. As a consequence, quantitative researchers must find a middle-ground between humility and hubris, which is determined by close attention to the appropriate generalizability of your findings. While this will differ by the research, El-Masri and Fox-Waslyshyn (2018) suggest beginning with a clear outline of your differences from other studies and limitations. From this point, the plausibility and value of your “take home-message” (El-Masri & Fox-Waslyshyn, 2018; p. 108) will shine forth more clearly.

Qualitative Writing

Unlike quantitative writing, qualitative writing must describe social life through its qualities. This means that the qualitative writer be attentive to the variety of words formed to describe not the endless quantity of experience, but its endless distinctions. While this applies to the quantitative writers too, we highly encourage qualitative and interpretive researchers to read literature. There you will find a wealth of writers interested in “qualitative” description to make a powerful effect upon their reader. Your task is different, it deals with direct representation, not metaphor or fantasy, but many of the same tools can be applied (Jackson, 2017).

Qualitative writing moves from selected observations, analysis, themes, text discussion to the final goal of thick description (Holliday, 2012). Thick descriptions are details of the contexts of behaviours and actions as interpreted by actors so that outsiders can have a better understanding of them (Holliday, 2007). It takes fragments of a messy reality to stand in for a larger argument. Rather than just cite all the observations at random, it imposes order on the complexity of daily social life and cultivates it into a unified image (Holliday, 2007). Your hunches, values, and sincerity are not excluded from this process, but rather should inspire the fragments you take to be meaningful and ‘more’ complete (Holliday, 2013). It not only aligns a complex network of data around your argument, but seeks to achieve an articulation, a thick description, of this network (Holliday, 2013, p. 13).

A common pitfall of undergraduate qualitative writers is to merely list your data with limited commentary or thoughtful coordination. For Holliday (2013), this difficulty is worsened through the student’s cultivated passivity (one-sided lectures, reading, reiterating information), inculcating a belief that research is merely the imitation of fact. “To get over this difficulty,” Holliday suggests, “the researcher first needs to appreciate that her data is already different to the social reality it is taken from. She cannot pretend that it is a raw, true representation” (2013, p. 4). This means that when we selected Holliday’s (2013) quote, we were already performing a manipulation. We have stripped data from the context of his argument, placed it to fit a point for this manual. It is not selected at random, but according to a judgment formed by us. It is your job as a qualitative researcher to articulate the reasons behind your judgment, and if they do not exist, to make sure they do. Each quotation should be selected for the purpose of your argument, allowing the data to coordinate itself around a ‘representation’ which you have indeed partially fabricated, but for the purpose of communicating your view of a complex social situation. Thus, as Holliday (2013, p. 5) points out, the commentary around your data must always nimbly answer your readers question: “what is the point?”

It is the ‘point’ of your representation which will motivate the thematization of your data. The point goes back to our chapter on the research question: what is the gap that you want to fulfill? What is the meaningful question that you have asked, and how does this data answer that question? While this research question may be met by data that surprises your assumptions with new and interesting complications, the data you finally present in the paper must always adroitly answer your (interesting, evidential, and operational) research question. With this in mind, it is also vital that this ‘point’ complements and not betrays fidelity to the data (Jackson, 2017). The reader has come to you as a researcher out of trust for your accurate representation of reality, and thus the point of any academic genre comprises respect and integrity in representing the data accurately. Without strict methodology, your method for selecting data may appear arbitrary (without articulation of their purpose, methods-heavy papers also commit this folly), so it is even more important that you remain straightforward about: (1) the limitations of your data, and (2) the reasoning for selecting the final data that you did (why are most of your observations being left ‘back-stage’?).

After you have carefully analyzed your data and derived a coherent and interesting point (see Chapter 9), then it is time to consider the right balance between evidence and argument. A great qualitative researcher will be able to represent their data so vividly that narrative will be developed without the logical straightjacket of argument (hence, therefore, subsequently etc.). If the ‘point’ of your data exists clearly in your descriptions and sparse unpacking of that data, the reader will gain a sense of their connection without noticing you ‘forcing’ the argument crudely. On the other hand, if the point of the connection between your data is recluse, the reader may grow suspicious of their connection. Your job as a qualitative writer will then be to subtly show the themes that emerged from your data without extensive analysis. There is always a delicate balance between what is explicit and implicit to communication. This balance is especially important for qualitative writing, where data fragments are presented to make a theme explicit and other data fragments are neglected either because the point is considered not important enough or implied (Holliday, 2013).

Notice how unlike the quantitative writer, whose findings seek to confirm the presence of a predefined variable, the qualitative writer tends to present their findings as a narrative. What the qualitative writer is concerned with is the emergence of themes that draw together a set of descriptions about social life (Holliday, 2007). The quantitative writer, on the other hand, has already deduced these themes through the operationalization of quantitative variables. Thus, in your qualitative research, writing of your findings section can take on a larger narrative, showing a connection of events that you discern important to describing the phenomenon at hand.

Theoretical Writing

The final type of writing we overview is wielded by all the social science genres. Theory is perhaps the most daunting and important of the discursive purposes in the sciences. It involves the strange act of looping the causes and consequences of particular situated evidence into a summative statement: a narrative which is sophisticated and generalizable to many different contexts, and able to effectively unify various particular situations under a robust concept. Due to the ambition of this task, it inherently falls prone to conceit as researchers exaggerate the importance of their findings and absolve the distinctions between many concrete experiences under a single reductive label. Such statements as ‘Foucault is a post-modernist’ or ‘the present day economy is neoliberal’ can easily indicate to us that theory is often used stereotypically: as a commonly used, shallow narrative, that is easily generalized and more useful in conversation than in understanding. While terms like ‘neoliberal’ may have begun as a helpful insight to explain a particular trend towards economic rationalism and the shrinking power of the state, their wide application and misuse often leads to the dilution of the term, turning them into terms that are issued mindlessly, explaining everything and nothing in one lazy utterance.

But these criticisms, afterall, are only directed to the theories that are not doing their work. Many theories perform vital tasks within the social sciences, either helping us to explain or discover the reality of a phenomenon by pointing us in the right direction. This direction may not (and likely does not) perfectly describe what it is pointing at, but they are important because new theories begin with the authority of the old, and much theoretical work has to do with amending the meaning of theories (like neoliberal) in order to make them more useful. Every theoretical researcher, whether they are inventing a brand new theory or amending an old one with new evidence, therefore engages in a collaborative practice of developing the most useful theory for our current context. By useful we understand theory that is able to:

1. Be accurate: is a useful tool for helping us to think about many contexts in a way that allows us to comprehend their complexity (we say this in the heuristic, not representative sense).
2. Be relevant: help to make the theory easier to use in both academia and beyond for responding to important social issues.
3. Be pedagogical: Simplify the theory (while maintaining its robustness) to expand its usage.

It is important to note that good theoretical research does not need to conform to all three; but while your focus may be on only one aspect of this three, it is good to keep all components in mind (a good theory tends to be effective at representing what it discusses, relevant to the people it is communicating to, and clear enough to have its significance readily understood).

References

El-Masri, M. M., & Fox-Wasylyshyn, S. (2018). Writing for quantitative research publication: A brief outline. Canadian Journal of Nursing Research, 50(3), 107-109. https://doi.org/10.1177/0844562118769202

Fallon, M. (2016). Writing up quantitative research in the social and behavioral sciences. Sense Publisher.

Holliday, A. (2007). Doing and writing qualitative research (2nd ed.). SAGE.

Jackson, M. (2017). Writing With Care. In Pandian, A., McLean, S., (eds.), Crumpled paper boat: Experiments in ethnographic writing. Duke University Press