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CJ 300 Chapter 4

by: Rachel Sutherland

CJ 300 Chapter 4 300

Marketplace > Grand Valley State University > CJ > 300 > CJ 300 Chapter 4
Rachel Sutherland

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Concepts, operationalization and measurement These notes are from lectures Sept. 19 and 21, and are from pages 80-94 and pages 103-106.
Dr. Cwick
Class Notes
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This 4 page Class Notes was uploaded by Rachel Sutherland on Monday September 26, 2016. The Class Notes belongs to 300 at Grand Valley State University taught by Dr. Cwick in Fall 2016. Since its upload, it has received 8 views. For similar materials see Methods in CJ at Grand Valley State University.


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Date Created: 09/26/16
Chapter 4 Concepts, Operationalization and Measurement I. Conceptions and Concepts 1. Step one: clarifying mental images, or conceptions a. Conceptions are subjective thoughts-they are individual in nature b. We have a wide array of subjective thoughts in our minds c. Ex: think of a murder i. Did you all think of the same thing? ii. No, because our concepts vary 2. Step two: apply a concept or an accepted word that allows us to vaguely describe what we are thinking about 3. Concepts are the words or symbols in language that we use to represent these mental images 4. Conceptualization a. The process by which we specify precisely what we mean when we use particular terms b. Day to day communication is made possible through general but often vague and unspoken agreements about the use of terms 5. Indicators and Dimensions a. The end product of the conceptualization process is the specification of a set of indicators of what we have in mind, indicating the presence or absence of the concept we are studying b. A good indicator of crime seriousness is harm to the crime victim i. Physical injury is an example of harm, as well as economic harm or psychological harm c. Dimension i. Some specifiable aspect of a concept ii. It is possible to subdivide the concept of crime seriousness into several dimensions iii. Specifying dimensions and identifying the various indicators for each of those dimensions are both parts of conceptualization 6. Conceptual order a. A conceptual definition is a working definition specifically assigned to a term b. A real or essential nature definition is inherently subjective c. Operational definition i. A definition that spells out precisely how the concept will be measured d. Conceptualization › conceptual definition › operational definition › measurements in the real world II. Operationalization Choices 1. Developing an operational definition also moves us closer to measurement a. Requires that we think about selecting a data collection method 2. Measurement as Scoring a. Many people consider measurement to be the most important and difficult phase of criminal justice research 3. Executive and exclusive measurement a. Variables are logical sets of attributes b. Every variable should have two important qualities i. Attributes composing it should be exhaustive ii. At the same time, attributes composing a variable must be mutually exclusive  Researchers must be able to classify every observation in terms of one and only one attributes  Observations should fit into only one category 4. Levels of measurement a. Attributes composing any variable must be mutually exclusive and exhaustive b. Variable may represent different levels of measurement: nominal, ordinal, interval and ratio c. Nominal i. Variables with those attributes have only the characteristics of exhaustiveness and mutual exclusiveness ii. Ex: gender, city of residence, major iii. They are distinct from one another and just mainly offer names or labels for characteristics d. Ordinal i. Variables whose attributes may be logically rank ordered ii. The different attributes represent relatively more or less of the variable iii. Examples of variables that can be ordered in some way are opinion of police, occupational status, crime seriousness e. Interval i. When the actual distance that separates the attributes composing some variables has meaning ii. The logical distance between attributes can be expressed through meaningful standard intervals iii. Ex: boiling point of liquid, temperature change f. Ratio i. The attributes that compose a variable in ratio measures are based on a true zero point ii. Cannot have a negative number iii. Ex: exam grades (0-100) III. Criteria for Measurement Quality 1. Measurements have varied precision a. Precision refers to fineness of distinction between attributes b. Precision does not equal accuracy i. Ex: I am from the UP – accurate ii. I am from Baraga in the UP – precise and accurate 2. Two way to evaluate the quality of measurement: a. Reliability i. Applied repeatedly, yielding the same result (consistency)  Ex: Miscalculated speedometer is not accurate  It’s reliable, but not accurate ii. Reliability can be a major issue considering data that comes from observation iii. Why is this?  Multiple observers will have different results  Misinterpreting iv. Dealing with reliability issues  Test-retest o Sometimes it’s appropriate to take the same measurement more than once o Faulty memory may produce inconsistent responses if there is a lengthy gap between the initial interview and the retest o If the test-retest interval is short, answers given in second interview may be affected by earlier responses if the subjects are trying to be consistent b. Validity i. Measurement validity involves whether you are really measuring what you are you are measuring ii. There are three types of validity:  Face validity: is it logical and agreed upon? o If something has no face validity, it simply does not make sense o Good ex of face validity: the Census Bureau has created operational definitions of such concepts as family, household, and employment status that have a workable validity in most studies using those concepts  Criterion-related validity: does it predict scores on something that is already accepted as validity (face validity) o Ex: do college entrance exams actually predict success in college?  Construct validity: logical relationships o Is this measure correlated or related to other measures in a way that we would expect? o Ex: fear of crime  Are people who are more fearful of crime less likely to go out at night? c. Use multiple measures to verify validity i. Ex: self-report and official measures IV. Composite Measures 1. Sometimes a single variable or indicator is not a very good measurement a. Can’t capture complex concepts in a single measure b. Limited variation using just one measure c. Combining individual measures can benefit reliability and validity and aid in efficiency 2. Typologies a. Intersection of two or more variable to create a set of categories or types i. Typology is the simplest composite measure, which is sometimes called taxonomy b. Typologies can be more complex, combining scores on three or more measures or by combining scores on two measures that take many different values i. An example of a complex typology is research on patterns of delinquency over time, done by Rolf Loeber c. Loeber’s delinquent categories: i. Stable – crime at time 1, and crime at time 2 ii. Escalators – minor crime at time 1, and more serious crime by time 2 iii. Desistors – crime at time 1, no crime at time 2 3. Index a. Combining scores using statistical techniques (ie. factor analysis, combined z-scores) i. More valid that a single question ii. More efficient than 9 separate variables


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