Measurement is important. Recognizing that fact, and respecting it, will be of great benefit to you\u2014both in research methods and in other areas of life as well. If, for example, you have ever baked a cake, you know well the importance of measurement. As someone who much prefers rebelling against precise rules over following them, I once learned the hard way that measurement matters. A couple of years ago I attempted to bake my wife a birthday cake without the help of any measuring utensils. I\u2019d baked before, I reasoned, and I had a pretty good sense of the difference between a cup and a tablespoon. How hard could it be? As it turns out, it\u2019s not easy guesstimating precise measures. The cake was inedible.<\/p>\r\n
Just as measurement is critical to successful baking, it is as important to successfully pulling off a social scientific research project. In sociology, when we use the term measurement we mean the process by which we describe and ascribe meaning to the key facts, concepts, or other phenomena that we are investigating. At its core, measurement is about defining one\u2019s terms in as clear and precise a way as possible. Of course, measurement in social science isn\u2019t quite as simple as using some predetermined or universally agreed-on tool, such as a measuring cup or spoon, but there are some basic tenants on which most social scientists agree when it comes to measurement. We\u2019ll explore those as well as some of the ways that measurement might vary depending on your unique approach to the study of your topic.<\/p>\r\n\r\n
The question of what social scientists measure can be answered by asking oneself what social scientists study. Think about the topics you\u2019ve learned about in other sociology classes you\u2019ve taken or the topics you\u2019ve considered investigating yourself. Or think about the many examples of research you\u2019ve read about in this text. In we learned about Melissa Milkie and Catharine Warner\u2019s study (2011) [1] of first graders\u2019 mental health. In order to conduct that study, Milkie and Warner needed to have some idea about how they were going to measure mental health. What does mental health mean, exactly? And how do we know when we\u2019re observing someone whose mental health is good and when we see someone whose mental health is compromised? Understanding how measurement works in research methods helps us answer these sorts of questions.<\/p>\r\n
As you might have guessed, social scientists will measure just about anything that they have an interest in investigating. For example, those who are interested in learning something about the correlation between social class and levels of happiness must develop some way to measure both social class and happiness. Those who wish to understand how well immigrants cope in their new locations must measure immigrant status and coping.<\/p>\r\n
Those who wish to understand how a person\u2019s gender shapes their workplace experiences must measure gender and workplace experiences. You get the idea. Social scientists can and do measure just about anything you can imagine observing or wanting to study. Of course, some things are easier to observe, or measure, than others, and the things we might wish to measure don\u2019t necessarily all fall into the same category of measureables.<\/p>\r\n
In 1964, philosopher Abraham Kaplan (1964) [2] wrote what has since become a classic work in research methodology, The Conduct of Inquiry (Babbie, 2010). [3] In his text, Kaplan describes different categories of things that behavioral scientists observe. One of those categories, which Kaplan called \u201cobservational terms,\u201d is probably the simplest to measure in social science. Observational terms are the sorts of things that we can see with the naked eye simply by looking at them. They are terms that \u201clend themselves to easy and confident verification\u201d (1964, p. 54). [4] If, for example, we wanted to know how the conditions of playgrounds differ across different neighborhoods, we could directly observe the variety, amount, and condition of equipment at various playgrounds.<\/p>\r\n
Indirect observables, on the other hand, are less straightforward to assess. They are \u201cterms whose application calls for relatively more subtle, complex, or indirect observations, in which inferences play an acknowledged part. Such inferences concern presumed connections, usually causal, between what is directly observed and what the term signifies\u201d (1964, p. 55). [5] If we conducted a study for which we wished to know a person\u2019s income, we\u2019d probably have to ask them their income, perhaps in an interview or a survey. Thus we have observed income, even if it has only been observed indirectly. Birthplace might be another indirect observable. We can ask study participants where they were born, but chances are good we won\u2019t have directly observed any of those people being born in the locations they report.<\/p>\r\n
Sometimes the measures that we are interested in are more complex and more abstract than observational terms or indirect observables. Think about some of the concepts you\u2019ve learned about in other sociology classes\u2014 ethnocentrism, for example. What is ethnocentrism? Well, you might know from your intro to sociology class that it has something to do with the way a person judges another\u2019s culture. But how would you measure it?<\/p>\r\n
Here\u2019s another construct: bureaucracy. We know this term has something to do with organizations and how they operate, but measuring such a construct is trickier than measuring, say, a person\u2019s income. In both cases, ethnocentrism and bureaucracy, these theoretical notions represent ideas whose meaning we have come to agree on. Though we may not be able to observe these abstractions directly, we can observe the confluence of things that they are made up of. Kaplan referred to these more abstract things that behavioral scientists measure as constructs. Constructs are \u201cnot observational either directly or indirectly\u201d (1964, p. 55), [6] but they can be defined based on observables.<\/p>\r\n
Thus far we have learned that social scientists measure what Abraham Kaplan called observational terms, indirect observables, and constructs. These terms refer to the different sorts of things that social scientists may be interested in measuring. But how do social scientists measure these things? That is the next question we\u2019ll tackle.<\/p>\r\n\r\n
Measurement in social science is a process. It occurs at multiple stages of a research project: in the planning stages, in the data collection stage, and sometimes even in the analysis stage. Recall that previously we defined measurement as the process by which we describe and ascribe meaning to the key facts, concepts, or other phenomena that we are investigating. Once we\u2019ve identified a research question, we begin to think about what some of the key ideas are that we hope to learn from our project. In describing those key ideas, we begin the measurement process.<\/p>\r\n
Let\u2019s say that our research question is the following: How do new university students cope with the adjustment to university? In order to answer this question, we\u2019ll need to some idea about what coping means. We may come up with an idea about what coping means early in the research process, as we begin to think about what to look for (or observe) in our data-collection phase. Once we\u2019ve collected data on coping, we also have to decide how to report on the topic. Perhaps, for example, there are different types or dimensions of coping, some of which lead to more successful adjustment than others. However we decide to proceed, and whatever we decide to report, the point is that measurement is important at each of these phases.<\/p>\r\n
As the preceding paragraph demonstrates, measurement is a process in part because it occurs at multiple stages of conducting research. We could also think of measurement as a process because of the fact that measurement in itself involves multiple stages. From identifying one\u2019s key terms to defining them to figuring out how to observe them and how to know if our observations are any good, there are multiple steps involved in the measurement process. An additional step in the measurement process involves deciding what elements one\u2019s measures contain. A measure\u2019s elements might be very straightforward and clear, particularly if they are directly observable. Other measures are more complex and might require the researcher to account for different themes or types. These sorts of complexities require paying careful attention to a concept\u2019s level of measurement and its dimensions. We\u2019ll explore these complexities in greater depth at the end of this chapter, but first let\u2019s look more closely at the early steps involved in the measurement process.<\/p>","rendered":"
Measurement is important. Recognizing that fact, and respecting it, will be of great benefit to you\u2014both in research methods and in other areas of life as well. If, for example, you have ever baked a cake, you know well the importance of measurement. As someone who much prefers rebelling against precise rules over following them, I once learned the hard way that measurement matters. A couple of years ago I attempted to bake my wife a birthday cake without the help of any measuring utensils. I\u2019d baked before, I reasoned, and I had a pretty good sense of the difference between a cup and a tablespoon. How hard could it be? As it turns out, it\u2019s not easy guesstimating precise measures. The cake was inedible.<\/p>\n
Just as measurement is critical to successful baking, it is as important to successfully pulling off a social scientific research project. In sociology, when we use the term measurement we mean the process by which we describe and ascribe meaning to the key facts, concepts, or other phenomena that we are investigating. At its core, measurement is about defining one\u2019s terms in as clear and precise a way as possible. Of course, measurement in social science isn\u2019t quite as simple as using some predetermined or universally agreed-on tool, such as a measuring cup or spoon, but there are some basic tenants on which most social scientists agree when it comes to measurement. We\u2019ll explore those as well as some of the ways that measurement might vary depending on your unique approach to the study of your topic.<\/p>\n
The question of what social scientists measure can be answered by asking oneself what social scientists study. Think about the topics you\u2019ve learned about in other sociology classes you\u2019ve taken or the topics you\u2019ve considered investigating yourself. Or think about the many examples of research you\u2019ve read about in this text. In we learned about Melissa Milkie and Catharine Warner\u2019s study (2011) [1] of first graders\u2019 mental health. In order to conduct that study, Milkie and Warner needed to have some idea about how they were going to measure mental health. What does mental health mean, exactly? And how do we know when we\u2019re observing someone whose mental health is good and when we see someone whose mental health is compromised? Understanding how measurement works in research methods helps us answer these sorts of questions.<\/p>\n
As you might have guessed, social scientists will measure just about anything that they have an interest in investigating. For example, those who are interested in learning something about the correlation between social class and levels of happiness must develop some way to measure both social class and happiness. Those who wish to understand how well immigrants cope in their new locations must measure immigrant status and coping.<\/p>\n
Those who wish to understand how a person\u2019s gender shapes their workplace experiences must measure gender and workplace experiences. You get the idea. Social scientists can and do measure just about anything you can imagine observing or wanting to study. Of course, some things are easier to observe, or measure, than others, and the things we might wish to measure don\u2019t necessarily all fall into the same category of measureables.<\/p>\n
In 1964, philosopher Abraham Kaplan (1964) [2] wrote what has since become a classic work in research methodology, The Conduct of Inquiry (Babbie, 2010). [3] In his text, Kaplan describes different categories of things that behavioral scientists observe. One of those categories, which Kaplan called \u201cobservational terms,\u201d is probably the simplest to measure in social science. Observational terms are the sorts of things that we can see with the naked eye simply by looking at them. They are terms that \u201clend themselves to easy and confident verification\u201d (1964, p. 54). [4] If, for example, we wanted to know how the conditions of playgrounds differ across different neighborhoods, we could directly observe the variety, amount, and condition of equipment at various playgrounds.<\/p>\n
Indirect observables, on the other hand, are less straightforward to assess. They are \u201cterms whose application calls for relatively more subtle, complex, or indirect observations, in which inferences play an acknowledged part. Such inferences concern presumed connections, usually causal, between what is directly observed and what the term signifies\u201d (1964, p. 55). [5] If we conducted a study for which we wished to know a person\u2019s income, we\u2019d probably have to ask them their income, perhaps in an interview or a survey. Thus we have observed income, even if it has only been observed indirectly. Birthplace might be another indirect observable. We can ask study participants where they were born, but chances are good we won\u2019t have directly observed any of those people being born in the locations they report.<\/p>\n
Sometimes the measures that we are interested in are more complex and more abstract than observational terms or indirect observables. Think about some of the concepts you\u2019ve learned about in other sociology classes\u2014 ethnocentrism, for example. What is ethnocentrism? Well, you might know from your intro to sociology class that it has something to do with the way a person judges another\u2019s culture. But how would you measure it?<\/p>\n
Here\u2019s another construct: bureaucracy. We know this term has something to do with organizations and how they operate, but measuring such a construct is trickier than measuring, say, a person\u2019s income. In both cases, ethnocentrism and bureaucracy, these theoretical notions represent ideas whose meaning we have come to agree on. Though we may not be able to observe these abstractions directly, we can observe the confluence of things that they are made up of. Kaplan referred to these more abstract things that behavioral scientists measure as constructs. Constructs are \u201cnot observational either directly or indirectly\u201d (1964, p. 55), [6] but they can be defined based on observables.<\/p>\n
Thus far we have learned that social scientists measure what Abraham Kaplan called observational terms, indirect observables, and constructs. These terms refer to the different sorts of things that social scientists may be interested in measuring. But how do social scientists measure these things? That is the next question we\u2019ll tackle.<\/p>\n
Measurement in social science is a process. It occurs at multiple stages of a research project: in the planning stages, in the data collection stage, and sometimes even in the analysis stage. Recall that previously we defined measurement as the process by which we describe and ascribe meaning to the key facts, concepts, or other phenomena that we are investigating. Once we\u2019ve identified a research question, we begin to think about what some of the key ideas are that we hope to learn from our project. In describing those key ideas, we begin the measurement process.<\/p>\n
Let\u2019s say that our research question is the following: How do new university students cope with the adjustment to university? In order to answer this question, we\u2019ll need to some idea about what coping means. We may come up with an idea about what coping means early in the research process, as we begin to think about what to look for (or observe) in our data-collection phase. Once we\u2019ve collected data on coping, we also have to decide how to report on the topic. Perhaps, for example, there are different types or dimensions of coping, some of which lead to more successful adjustment than others. However we decide to proceed, and whatever we decide to report, the point is that measurement is important at each of these phases.<\/p>\n
As the preceding paragraph demonstrates, measurement is a process in part because it occurs at multiple stages of conducting research. We could also think of measurement as a process because of the fact that measurement in itself involves multiple stages. From identifying one\u2019s key terms to defining them to figuring out how to observe them and how to know if our observations are any good, there are multiple steps involved in the measurement process. An additional step in the measurement process involves deciding what elements one\u2019s measures contain. A measure\u2019s elements might be very straightforward and clear, particularly if they are directly observable. Other measures are more complex and might require the researcher to account for different themes or types. These sorts of complexities require paying careful attention to a concept\u2019s level of measurement and its dimensions. We\u2019ll explore these complexities in greater depth at the end of this chapter, but first let\u2019s look more closely at the early steps involved in the measurement process.<\/p>\n","protected":false},"author":84,"menu_order":1,"template":"","meta":{"pb_show_title":"on","pb_short_title":"","pb_subtitle":"","pb_authors":[],"pb_section_license":""},"chapter-type":[48],"contributor":[],"license":[],"class_list":["post-173","chapter","type-chapter","status-publish","hentry","chapter-type-numberless"],"part":114,"_links":{"self":[{"href":"https:\/\/opentextbooks.concordia.ca\/quantitativeresearch\/wp-json\/pressbooks\/v2\/chapters\/173","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/opentextbooks.concordia.ca\/quantitativeresearch\/wp-json\/pressbooks\/v2\/chapters"}],"about":[{"href":"https:\/\/opentextbooks.concordia.ca\/quantitativeresearch\/wp-json\/wp\/v2\/types\/chapter"}],"author":[{"embeddable":true,"href":"https:\/\/opentextbooks.concordia.ca\/quantitativeresearch\/wp-json\/wp\/v2\/users\/84"}],"version-history":[{"count":3,"href":"https:\/\/opentextbooks.concordia.ca\/quantitativeresearch\/wp-json\/pressbooks\/v2\/chapters\/173\/revisions"}],"predecessor-version":[{"id":179,"href":"https:\/\/opentextbooks.concordia.ca\/quantitativeresearch\/wp-json\/pressbooks\/v2\/chapters\/173\/revisions\/179"}],"part":[{"href":"https:\/\/opentextbooks.concordia.ca\/quantitativeresearch\/wp-json\/pressbooks\/v2\/parts\/114"}],"metadata":[{"href":"https:\/\/opentextbooks.concordia.ca\/quantitativeresearch\/wp-json\/pressbooks\/v2\/chapters\/173\/metadata\/"}],"wp:attachment":[{"href":"https:\/\/opentextbooks.concordia.ca\/quantitativeresearch\/wp-json\/wp\/v2\/media?parent=173"}],"wp:term":[{"taxonomy":"chapter-type","embeddable":true,"href":"https:\/\/opentextbooks.concordia.ca\/quantitativeresearch\/wp-json\/pressbooks\/v2\/chapter-type?post=173"},{"taxonomy":"contributor","embeddable":true,"href":"https:\/\/opentextbooks.concordia.ca\/quantitativeresearch\/wp-json\/wp\/v2\/contributor?post=173"},{"taxonomy":"license","embeddable":true,"href":"https:\/\/opentextbooks.concordia.ca\/quantitativeresearch\/wp-json\/wp\/v2\/license?post=173"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}