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Midterm

CRIM220 Midterm.docx

10 pages95 viewsFall 2013

Department
Criminology
Course Code
CRIM 220
Professor
William Glackman
Study Guide
Midterm

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CHAPTER 1 - QUANTITATIVE VS QUALITATIVE
Quantitative
Natural Science model: do not treat human as a special
entity, instead see them as another biological organism,
subject to same scientific principles
Realism: there is only one reality that exists independent
of the researcher awaits our discovery
Emphasis on causes and effects: world made
up of predictors and outcomes (all visible)
organisms = black boxes”, any invisible
processes that goes on inside (eg thinking) are
deemed irrelevant
Positivism: Information derived from logical and
mathematical treatments , valid knowledge (truth) only in
scientific knowledge (Avoid introspective/intuitive
knowledge)
Prefer Quantitative measures for their precision
and amenability to mathematical analysis
Emphasis on observable variables that are
external to the individual (eg social facts) - Ignore
any metaphysical notions such as
consciousness
Depersonalize: Objectivity is achieved through social
distance and a detached, analytical stance
Behaviour can be extracted from its context to be
studied
Maintain neutrality, do not hate or love group, do
not “go native” or “overidentify”
Researcher-centred: Researcher/theory decide what is
important to study and how results be interpreted
(participants minimal role beyond responding to stimuli,
thoughts/motive not of interest)
Deductive approach: start with theory, make predictions
and assess their success in an ongoing process of theory
refinement
Understanding = ability to predict - if truly understand a
phenomenon (hurricanes, depression) you should be able
to predict its occurrence
Larger samples - looking for general overall pattern
across many cases (paying more attention to “the forest”)
Standardized procedures, data all gathered in exactly same
way from every subject, data all compared and correlated
mathematically
Preference for aggregation to reduce „noise‟ in the data
compile responses from many persons so that general trends
or patterns across people are visible across all responses,
any variability will cancel one another out in any group as a
whole, making the „averagethe purest statement of what is
„normal‟
Qualitative
Human-centred approach: Human behaviour are
fundamentally different from natural sciences, we can talk to
humans, must view them as thinking, motivated actors
Constructionism: knowledge and truth are created, not
discovered it is all a “socially constructed concept”
Emphasis on processes: reality is not stable and
awaiting discovery, they are actively constructed,
deconstructed and reconstructed on an ongoing basis
constructions of the world are open to change.
Phenomenologism: to understand human behaviour, must
take into account humans actively perceive and make sense of
the world, abstract from experience, ascribe meaning to
behaviour, and are affected by those meanings
Prefer Direct, qualitative verbal reports; quantifying
responses (eg scale of one to ten) interferes with
understanding of people‟s words and perceptions
No variables ruled out; internal, perceptual variables
expressly considered
Greater Validity comes with closeness: extended contact
with participants in their natural environment
Behaviour cannot be extracted from its context
Rapport (development of a bond of mutual trust
between researcher and participant
Participant-centered: should consider the meanings that
people themselves give to what they do instead of us inventing
these meanings
Inductive approach: start with observation and allowing
grounded theory to emerge
Understanding = verstehen - understanding behaviour in
context in terms meaningful to the actor
Case study analysis: prefer research in “the field”, where
behaviour is examined in context ; (paying more attention to
“the trees”)
Mixed or Multi Method Approaches
Both are committed to empirical understanding (understanding
should not be from philosophizing and speculation, should be
from data from interacting and observing the world)
Both value theory and data, differ in which comes first
Both seek to eliminate rival plausible explanations
Both are now seen as necessary compliments to each other in
order to increase understanding
o Quantitative give general description while qualitative
only give partial understanding, together they provide a
broader, more comprehensive understanding
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CHAPTER 2 GETTING STARTED W/ RESEARCH
Wallace’s Wheel
Both approaches are not opposing each other, but us a cycle/circular
Both is the same process, but with different start point
Empirical generalization theories (D) hypotheses observations (I)
Deductive Approach
Start with theory, express hypothese/predictions and assess their success in an ongoing process of theory refinement
Sources of Research ideas?
1) Theory as a research idea
o Theories help provide research focus and imply hypothesis that can be tested empirically
o Downside of theories: blind you from other variables/perspectives that are outside the theory
2) Applying theory to situations
o If theory say some set of events should go together, can test specific situations in which theory should be able to
predict outcomes
3) Extending or limiting a theory’s coverage
o Try to extend the coverage eg apply business theory to family dynamics
o Point out limitations to the applicability of existing theories (eg theories of aggression towards minority also the
same towards child/wife?)
4) Offer alternative explanations
o Researcher build on one another’s work by offering competing explanatory mechanisms for similar phenomena,
can help shift research focus
o Good theory should suggest research possibilities should be capable of being disapproved
Inductive Approach
Start with observation and allowing grounded theory to emerge
Sources of Research Ideas?
1) Insider
o Having particular life experiences may bring special insights to research
o Downfall of being insider may come with certain beliefs about how things work/ what the problems are need to
ensure to keep open-minded
2) Observations as research ideas
o Observations creates natural curiosity, asking why and how, being with phenomenon that interests you
o then test out factors that might influence it
3) intensive case studies/experience surveys
o list to oral history or experience sureveys may suggest research ideas
o eg talk to Jews who lived in Germany during WW2 to research about prejudice and discrimination
Research is a Heuristic Process
Heuristic = Enabling a person to discover or learn something for themselves.
Other Research as a source of research ideas
1) Replication (society changes over time)
2) Technologies open new doors (some things may be previously inaccessible)
3) Challenging prior research (may prove it wrong, may be different among subgroups)
Other sources of research ideas
1) Resolving conflicting results (why some research contradict each other, why different results)
2) Analogy (eg apply immunization of biology and apply to attitude change of sociology)
3) Anomaly anomalies are situations that should not exist according to theory, “a fact that doesn’t fit” and hence requires
explanation for the deviation Must first be ‘recognized’, and not be ignored or rationalized away
4) Serendipity unexpected findings that are virtually stumbled upon while looking for something else (eg finds gold and
strikes oil) Again, cannot be ignored as a mistake, “recognition precedes discovery”
5) The supplied problem (other give you a problem eg is our program effective? How can we better meet our objectives?)
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6) Cultural folklore/”Common Sense” (many beliefs not verified empirically, research can help refute or confirm our beliefs,
what “everyone knows” may not be true)
Doing Research
Identifying a Researchable Question
Central points:
o Express in researchable terms
o Specific, limited in scope, related to empirical reality
o Should have specific evaluation criteria
o Remain reflexive (consciously and critically aware of multiple influences)
Role of Hypotheses
Two variables and how they relate
Should be a testable statement
Strengths:
o Link between theory and data (abstract and concrete situations)
o Imply a test = can gather evidence to establish truth/falsity, help reveal the reality
Allow us to falsify and “provide support for” but not “prove” truth
To prove truth must be correct in ALL situations, however one false event may falsify theory getting to
Hall of Fame takes a long time
Also, theory make prediction, but may not be the ONLY theory that can predict certain results
o Ensure self-disciplined honesty stating hypotheses ahead of time
Developing indicators for concepts
Nominal definitions
o Similar to dictionary definition, but linked to one’s theoretical stance (eg different definition of violence between
feminist or hard reduction researcher)
o Socially constructed, not right or wrong, but more or less useful
Operational definitions = Creating meaning by delineating the specific indicators operations that are to be taken as
representatives of a concept
o Indicators = eg asking a lot of questions may be big interest, or just want to diver attention away from self may be
erroneous, depends on interpretation
o Operations
Measured operational definitions ( what we observe and our constructions of it eg kiss = love)
Experimental operational definitions (manipulate situation, create variables of interest, eg frustration is
when child is denied access to attractive toy)
Mono-operation/method bias
repeatedly deal with only one single operationalization of a particular variable of interest (Mono-operation bias)
don’t want to run the risk of producing method dependent results (mono method bias)
researcher should use multiple operationalization and multiple methods
Definitional Operationism = imposing definition by fiat and ignoring theoretical issues inherent in that choice eg hard to
create measurement for intelligence so use IQ test “scores on IQ test is intelligence, what is intelligence? It is what the IQ
test measures” – circular argument
Reliability = consistency of theory over time, across different observers
test-retest reliability = same result on two successive occasions
inter-rater reliability = other researcher should read your explanation/or be trained in your procedure, then proceed to
make same judgements you would shows that you have explained clearly
Validity = technique of measurement is appropriate
convergent validity = the operationalization is indeed related to criterion
divergent validity = not related to other constructs you do not want to measure
concurrent validity = operationalization and independent criterion were obtained at the same time
predictive validity = operational measure and observing the criterion occur at different times (eg decide what measure
dangerousness, then see who exhibited dangerous behaviour later)
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