1. Introduction

The Language of Science

All scientists employ jargon—special words that are used by a profession or group—in the course of their work. By reading and discussing each other’s work, scientists ensure the quality and relevance of their research. Using a shared language, in turn, helps create a strong scientific community that can draw on a common identity and common set of perspectives—the basis for a constructive dialogue.

It’s important for students new to a scientific field to know its terms and how they are appropriately used. A critical and occasionally prickly bunch by temperament, scientists may dismiss outright the views of people who are unfamiliar with their lingo and traditions. To help you familiarize yourself with the language of science, we’ve listed some key terms used virtually everywhere across scholarly and scientific fields. Note that not everyone agrees on the meaning of these terms—or any of the terms used in this book, frankly—so perfectly respectable scientists may disagree with what we say here (but hopefully not.)

Scholars, researchers, scientists. “Scholar” can be used as a synonym for words like “researcher” and “scientist,” although it typically refers to a person who engages in research for its own sake (rather than for a practical purpose, as we’ll discuss later). A college professor would be a scholar. Nonscientists who are academics (such as a literature professor) would also be scholars.

Disciplines, fields, subfields. Scholars do their work within an academic “field” or “discipline.” Sociology is an academic field. Each discipline has its own traditions, philosophies, and research methods. Sometimes the distinction seems arbitrary—for instance, “history” is a particular research method (the historical method), whereas “political science” focuses on a specific domain of human activity. Additionally, there is plenty of overlap between fields: sociologists study politics, anthropologists study social ties, economists study culture, and so on. That said, because advances in knowledge within a field often happen through interactions between scholars within a particular field, it’s important to understand and appreciate these disciplinary boundaries. Each field also has subfields—for example, economic sociology and social psychology are two subfields within sociology.

Phenomenon. Scientists are typically interested in studying phenomena, a catchall term for things, events, and processes that (1) can be observed and (2) raise interesting questions for scientists about how the world works. Sociologists and other social scientists study social phenomena, which have to do with human beings and their interactions.

Observation. Scientists don’t just sit in an ivory tower and ruminate about the world (or at least ideally, they don’t). They draw upon actual experiences seeing, hearing, or otherwise documenting the reality around them, which should be the basis for any knowledge they produce. These observations can be the researcher’s own or those of other people, but in either case, the observations must be conducted in a systematic and credible way.

In addition to this general meaning, the word “observation” has more specific uses in the social sciences. As we will discuss in Chapter 9: Ethnography, it can refer to ethnographic observation—a researcher’s direct observation of social spaces as a method of gathering qualitative data. As we’ll talk about in Chapter 12: Experiments, scientists also distinguish between experimental data—information collected under experimental conditions, where researchers can control the conditions under study—and observational data, which scientists gather in the real world from surveys, in-depth interviews, ethnographic observation, and other methods that don’t use an experimental design.

Data, datum, data point, dataset. We’ll use the word data quite a bit in this textbook. It refers to facts, details, statistics, and other information used to understand some phenomenon of interest. Ideally, data is collected through a scientific process of the sort described in this chapter, but any information could be considered data—what matters for the strength of a particular study is often how the scientist uses the data. You’ll notice that we have referred to “data” as a singular noun. This is a matter of great controversy among scientists. (Did we mention scientists are a bit judgmental?) Regularly, they refer to “data” in the plural form (“The data are quite conclusive”), even though no normal people ever do this. They point out, pedantically, that “datum” is the singular form of data. At the risk of alienating our colleagues, we will refer to “data” in the singular form. In doing so, we follow the lead of many mainstream news publications (Rogers 2012), and since one theme of this book is the importance of connecting research to the real world, we humbly suggest this simple way of making your writing more accessible to nonscientists. That said, when talking to other social scientists, you may find it helpful to code-switch and show you are a card-carrying scientist by using “data” as a plural noun (we forgive you).

In the scientific community, researchers use the term data point to refer to a specific statistic or other piece of information (“That data point is an outlier”). Now let’s consider the opposite case: lots and lots of data. All the data relating to a specific survey or study can be grouped together into a database, or what scientists call a dataset. For example, think about a list of students in your class, which includes information about their names, ID numbers, and email addresses. That would be a (small) dataset, but social scientists regularly work with datasets that contain information about thousands of people, with specific details about each individual’s personal background and attitudes on a variety of subjects. Note also that the data in datasets doesn’t have to deal with individuals per se: as we will describe later, it can be about anything—from books and movies, to families and relationships, to organizations and countries.

Literature. Science always builds on existing knowledge. Even if their scientific research overturns parts of that accumulated knowledge, scientists should always know what previous studies have been done on their subject area, and they need to connect their own work to that body of knowledge. Literature is the name we give to the existing scientific knowledge relating to a particular phenomenon. Here, we’re not talking about the “literature” you read in your English classes—novels and poetry and the like. The scientific literature amounts to all the articles, books, and other material written by scholars on a specific topic. Scientists (and scholars more broadly) care so much about literature that they bog down their writing with endless parenthetical citations (a topic discussed in Appendix A: Presenting, Writing, and Publishing). Their intention is not to bore their readers, but rather to precisely source their information and be clear about whatever intellectual debts they owe to other scholars.

Popular culture often depicts scientists as antisocial loners and mad geniuses (which, to be honest, is not always an unfair assessment). But the fact that they are deeply rooted in the scientific literature on their subject ensures that they are contributors to a grand tradition of learning, rather than just unwashed crackpots toiling away in their garage laboratories. “If I have seen further it is by standing on the shoulders of Giants,” the physicist Isaac Newton famously said (Turnbull 1959:416). Reading and connecting your work to the existing literature on your topic is how you, as a scientist, stand on the shoulders of the scientists who came before you.