CRJ
301—Research Methods in Criminal Justice
Points of
Interest from Senese
Pages 2-7
•
The
problematic assumption that some CJ students make.
•
General
definition of “applied research.”
•
The
“scientific method” and CJ.
•
The
Martinson report and implications.
•
The
five “concepts” of research.
•
“Theory”,
and what research does for it.
•
The
basis of most current theories.
•
Drunk
driving theories and implications.
Pages 7-12
•
Objectivity.
•
Multiple-choice
versus essay exams and objectivity.
•
Logical
structure of social science research.
•
Qualitative
vs. Quantitative Data.
•
Cycles
of research.
•
Paint
and light variations w/inmates and implications.
•
Foci
of CJ research.
•
“Process
studies.”
Pages 12-17
•
The
relationship between CJ researchers and practitioners.
•
Areas
of impact of research in CJ.
•
CJ
practitioners’ possible rejection of research.
•
Political
constraints.
•
Resource
constraints.
•
Research
constraints.
•
Relative
amount of CJ research.
•
The
CJ institution most researched.
Pages 16-21
•
Research
on police patrol.
•
Research
on police subculture.
•
Research
on police discretion and decision-making.
•
Research
on courts.
•
Research
on Corrections.
Pages 24-34
•
“dichotomy”
•
“pure”
vs. “applied” research
•
“quantitative”
vs. “qualitative” data
•
whether
“qualitative analysis” is easier than quantitative
•
Which
form of data is superior
•
“descriptive”
vs. “inferential” analysis
•
“discrete”
vs. “continuous” data
•
“units
of analysis”
•
“appropriate
to the research purpose”
•
“levels
of measurement”
•
Nominal
•
Ordinal
•
Interval
•
Ratio
Pages 34-42
•
Variables
•
Dependent
vs. independent variables
•
Concepts
and prior research
•
Basic
ways of defining concepts
•
Operational
definitions
•
Cross-sectional
vs. longitudinal studies
Pages 45-56
•
“research
design”
•
When
the research design is formulated
•
Hypothetical
jail administrator
•
Dangers
the HJA might face without proper research design
•
Theoretical
purpose*
•
Relationship
between prior research and research design
•
Evaluation
design
Pages 56-64
•
The
bases of “idea formation”
•
Conceptualization
•
The
problem of “definition”
•
Operationalization
•
Approaching
the issue of “variation”
•
Data
collection
•
Data
analysis
Pages 65-75
•
Extent
to which qualitative and quantitative analysis are mutually exclusive
•
Descriptive
analysis as part of quantitative analysis*
•
Quantitative
analysis and the relationship between variables*
•
Experimental
designs
•
Pre-
and post-tests.
•
Control
group
•
3
steps in experimental designs
•
Content
analysis
•
Observation
analysis
•
Needs
assessment
•
Process
evaluation
•
Outcome
evaluation
Pages 77-87
•
Composite
measures and their purpose
•
His
example of rating correctional officer effectiveness
•
Purpose
of redundant measures
•
Elements
in establishing causation
•
Face
validity
•
Predictive
validity
•
Content
validity
•
Construct
validity*
Pages 87-101
•
Reliability
(as opposed to validity)
•
Methods
of testing reliability
•
The
inmate infraction example
•
The
role of accepted measures
•
Codebooks.
Pages 104-113
•
The
“basic idea” of sampling
•
Why
we sample and the “logic of sampling”
•
Probability
versus non-probability sampling
•
Simple
random sampling
•
Systematic
random sampling
•
What
can cause bias in systematic random sampling
•
Stratified
random sampling
Pages 114-123
•
Non-probability
sampling
•
Purposive
sampling*
•
Quota
sampling
•
Accidental
(availability) sampling
•
Snowball
sampling
•
Determining
sample size
Pages 126-134
•
What makes experimental
designs “ideal”
•
Single group designs
•
Pretest/posttest designs
•
Problems with
pretest/posttest designs
•
Posttest only
•
When posttest only are
used
•
Basic
features of “classical experiments”
•
Purpose
of the control group
•
How
classical experiments demonstrate causation
•
Matching
vs. randomization
•
Solomon
four-group designs and their purpose
Pages 136-142
•
Biggest
barrier to proper experiments in CJ
•
“contrasted
designs”
•
“time-series
designs”
•
How
common time-series designs are and why
•
External
validity
•
Internal
validity
•
History
•
Maturation
•
Mortality
•
Instrumentation
•
Testing
effects
Pages 174-190
•
Frequency
of observational studies in CJ
•
The
“soft data” problem
•
Comparing
quantitative and observational data in term of “hard” and “soft”
•
Full
participant
•
Participant-researcher
•
Researcher
who participates
•
Complete
researcher
•
Considerations
of research setting (public, etc.)
•
Typical
objects of observational study
•
Advantages
of observational designs
•
Disadvantages
of observational designs
•
Consistency
problem
•
Types
of phenomena noted in observational research (body language, etc.)
Pages 296-310
•
Level
of discussion of qualitative research technique and why
•
Qualitative
vs. quantitative analysis of inmate control
•
Different
types of interview analyses
•
Thick
description
•
Grounded
theory
•
“integration
of data collection and analysis”
•
Analytical
induction
•
Why
S. recommends a thorough review of all qualitative data prior to analysis
•
Categorization
•
Content
analysis—general meaning
•
Potential
for “representativeness” of content analysis
Pages 244-251
•
Why
we conduct inferential inferences
•
The
general relationship between levels of measurement an test statistics.
•
The
basis of hypothesis setting
•
Null
hypotheses and their purpose
•
What
we assume about the null prior to the statistical test.