The document outlines the complex processes of measurement and operationalization in research, emphasizing the need for clear definitions and reliable indicators of abstract concepts like crime and poverty. It discusses the importance of developing both conceptual and operational definitions to enhance measurement quality, focusing on the criteria of reliability and validity. Additionally, it highlights the use of composite measures to effectively analyze multifaceted concepts in a more efficient manner.

1. 1
Concepts, Operationalization,
and Measurement

2. OUTLINE
 Introduction
 Conceptions and Concepts
 Operationalization Choices
 Criteria for Measurement Quality
 Composite Measures

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•Because measurement is difficult and
imprecise, researchers try to describe the
measurement process explicitly
•We want to move from vague ideas of what
we want to study to actually being able to
recognize and measure it in the real world
•Otherwise, we will be unable to communicate
the relevance of our idea and findings to an
audience

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•Clarifying abstract mental images is an
essential first step in measurement
•“Crime”
•Conception – Mental image we have about
something
•Concepts – Words, phrases, or symbols in
language that are used to represent these
mental images in communication
•e.g., gender, punishment, chivalry,
delinquency, poverty, intelligence, racism,
sexism, assault, deviance, income

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•Direct observables – Those things or qualities
we can observe directly (color, shape)
•Indirect observables – Require relatively
more subtle, complex, or indirect observations
for things that cannot be observed directly
(reports, court transcripts, criminal history
records)
•Constructs – Theoretical creations; cannot be
observed directly or indirectly; similar to
Concept

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•Specifying precisely what we mean when we
use particular terms
•Results in a set of indicators of what we have
in mind
•Indicates a presence or absence of the
concept we are studying
•Violent crime = offender uses force (or
threatens to use force) against a victim

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•Dimension – Specifiable aspect of a concept
•“Crime Seriousness” – Can be subdivided into
dimensions
•e.g., Dimension – Victim harm
•Indicators – Physical injury, economic loss,
psychological consequences
•Specification leads to deeper understanding

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•Concepts are abstract and only mental
creations
•The terms we use to describe them do not
have real and concrete meanings
•What is poverty? delinquency? strain?
•Reification – Process of regarding as real
things that are not

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•Conceptual definition (what is SES?)
•Working definition specifically assigned to a
term, provides focus to our observations
•Gives us a specific working definition so that
readers will understand the concept
•Operational definition (how will we measure
SES?)
•Spells out precisely how the concept will be
measured

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Conceptualization
Conceptual Definition
Operational Definition
Measurements in the Real World

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•Operationalization – The process of
developing operational definitions
•Moves us closer to measurement
•Requires us to determine what might work as
a data-collection method

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•Measurement – Assigning numbers or labels
to units of analysis in order to represent the
conceptual properties
•Make observations, and assign scores to
them
•Difficult in CJ research because basic
concepts are not perfectly definable

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•Every variable should have two important
qualities:
•Exhaustive – You should be able to classify
every observation in terms of one of the
attributes composing the variable
•Mutually exclusive – You must be able to
classify every observation in terms of one and
only one attribute
•Example: Employment status

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•Nominal – Offer names or labels for
characteristics (race, gender, state of
residence)
•Ordinal – Attributes can be logically rank-
ordered
(education, opinions, occupational status)
•Interval – Meaningful distance between
attributes (temperature, IQ)
•Ratio – Has a true zero point
(age, # of priors, sentence length, income)

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•Certain analytic techniques have Levels of
Measurement requirements
•Ratio level can also be treated as Nominal,
Ordinal, or Interval
•You cannot convert a lower Level of
Measurement to a higher one
•Therefore, seek the highest Level of
Measurement possible

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•The key standards for measurement quality
are reliability and validity
•Measurements can be made with varying
degrees of precision
•Common sense dictates that the more
precise, the better
•However, you do not necessarily need
complete precision

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•Whether a particular measurement technique,
repeatedly applied to the same object, would
yield the same result each time
•Problem – Even if the same result is
retrieved, it may be incorrect every time
•Reliability does not insure accuracy
•Observer’s subjectivity might come into play

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•Test-retest method – Make the same
measurement more than once – should expect
same response both times
•Interrater reliability – Compare
measurements from different raters; verify
initial measurements
•Split-half method – Make more than one
measure of any concept; see if each measures
the concept differently

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•The extent to which an empirical measure
adequately reflects the meaning of the concept
under consideration
•Are you really measuring what you say you
are measuring?
•Demonstrating validity is more difficult than
demonstrating reliability

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•Face validity – On its face, does it seem valid?
Does it jibe with our common agreements and
mental images?
•Criterion-related validity – Compares a measure
to some external criterion
•Construct validity – Whether your variables
related to each other in the logically expected
direction
•Content validity – Does the measure cover the
range of meanings included in the concept?
•Multiple Measures – Alternative measures

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•Allows us to combine individual measures to
produce more valid and reliable indicators
•Reasons for using Composite Measures:
•The researcher is often unable to develop
single indicators of complex concepts
•We may wish to use a rather refined ordinal
measure of a variable, arranging cases in
several ordinal categories from very low to very
high on a variable such as degree of parental
supervision
•Indexes and scales are efficient devices for data
analysis

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•“Taxonomy”
•Produced by the intersection of two or more
variables to create a set of categories or types
•e.g., Typology of Delinquent/Criminal Acts
(Time 1 and 2)
•None, Minor (theft of items worth less than $5,
vandalism, fare evasion), Moderate (theft over
$5, gang fighting, carrying weapons), Serious
(car theft, breaking and entering, forced sex,
selling drugs
•Nondelinquent, Starter, Desistor, Stable,
Deescalator, Escalator

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•What is disorder? (Skogan, 1990)
•Distinguish between physical presence &
social perception
• Physical disorder: Abandoned buildings,
garbage and litter, graffiti, junk in vacant lots
•Social disorder: Groups of loiterers, drug use
and sales, vandalism, gang activity, public
drinking, street harassment
•Index created by averaging scores for each
measure

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•A composite index is a more valid measure
than a single question
•Computing and averaging across all items in a
category create more variation than we could
obtain in any single item
•Two indexes are more parsimonious than nine
individual variables
•Data analysis and interpretation can be more
efficient