Research Methods in criminal justice
Research Methods in criminal justice CCJ 4700
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This 13 page Study Guide was uploaded by miami305 on Tuesday January 12, 2016. The Study Guide belongs to CCJ 4700 at Florida International University taught by Dr. Meldrum in Winter 2015. Since its upload, it has received 79 views. For similar materials see Research Methods in Criminal Justice in Criminal Justice at Florida International University.
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Date Created: 01/12/16
CCJ 4700 • “more children using marijuana” CNN title • 1. how were “children” defined? • 2. More? • 3. Time frame? One year. • 4. Data collection? Ages of 12 to 17. Marijuana increased of 9% from 2008 to 2009. In 2008, 6.7% of 12-‐17 children used marijuana. In 2009 7.4% did. It was an increase in marijuana use, but it wasn’t a dramatic change • 5. Recruitment? • NSDUH: national survey of drug use health. It’s a survey • ACASI: survey you do online. CHAPTER 1&2, SCIENTIFIC INQUIRY AND THEORY IN SOCIAL SCIENCE RESEARCH • Experiential reality: the things we know from direct experience. • Agreement reality: the things we consider to be real because we have been told so, and everyone seems to believe they are. • Empirical research: research based on experience or observations. • Scientists have to meet criteria before agreeing on something they haven’t experienced. An assertion must have logical and empirical support, it must make sense and agree with observations. • Epistemology: the science of knowing • Methodology: the science of finding out. • Personal inquiry (day to day) : • Tradition: things that everyone knows, but that sometimes can be inaccurate (e.g, the earth is flat) (e.g. crimes are committed only by people in lower classes) • Authority: we tend to believe to things told by us by individuals who are in position for power , even if they’re not expert in the subject. • The believing in both of them can lead to mistakes and assumptions. ERRORS WE MAKE IN EVERYDAY REASONING 1. Inaccurate observations: we’re sloppy observers of everyday life. We don’t pay attention to some details. We tend to generalize. 2. Overgeneralization: form opinion based on anecdotal evidence, evidence accumulated basing on our personal data, rather that on specific data. • Scientific lifeguard: have lot of observations to base our conclusion on. Replication: repeating a study with different people and se tting to see if we get the same results. 3. Selective observations: we focus on specific events in the past and we ignore other event. E.g. Racial/ethnic prejudices. Limited interaction with people. E.g. parents and their view of their kids compared to how they see their kids. • Scientific lifeguard: making non-‐selective observations and not ignoring some of them 4. Illogical reasoning: the belief that an observation is an exception to the rule. The gambler’s fallacy: I’ve lost 9 times in a row, I’ll win next time. False, every time is the exact same odds. E.g. Resetting effect: thieves believe if they’ve just be caught in something, they wont be caught next time. False, the odds of being caught are always the same. • Scientific lifeguard: use of theories to guide researches. 5. Ideology and politics: this can bias our understanding of things. We might have certain believes in religion/politics etc. that can make it difficult to be objective in everyday life. • Scientific lifeguard: peer review helps to minimize biases . 2 FOUNDATIONS OF RESEARCH AND INQUIRY • Scientific inquiry is logic-‐empirical: -‐ 3 foundations: the systematic use of logic (theory); observation (data collection); and data analysis. • Scientific inquiry wants to find probabilistic patterns of regularity, not deterministic patterns. • Not every observation fit the pattern for the pattern to be valid. The key thing is saying: more likely to, NOT WILL. If 99 people fit, the pattern can be taken seriously. Not everyone has to fit • There is a focus on aggregates (groups of people) rather than on individuals. DIFFERENT PUPOSES OF RESEARCH • Exploration: the need to study of evaluate new policies, laws of phenomena. -‐ Do gay couples have lower divorce rates? • Description: simple counting and documenting. • Explanation: theory testing, every time you want to explain an outcome you have causes (generating the outcome). -‐ Why do some people commit more crime than others? • Evaluation: evaluating the effective of polices, programs etc. • Is the DARE program effective? • Prediction: using what we know about the past to predict something about the future. DIFFERING AVENUES FOR INQUIRY • ideographic vs nomothetic approaches. • Ideographic: developing a complete understanding of the reasons why a particular event happened. Understanding for a unique case or event. -‐ E.g. seeking to understand why a specific person committed suicide. • Nomothetic: explaining a class of events rather than a single event. • E.g. explaining 50 mass shooting. • Inductive vs deductive reasoning 3 • Inductive: theory building, moving from a set of observations to reach a conclusion about patterns in the observation. • Deductive: theory testing, moving from an expect pattern to making observations to confirm or not the expected pattern. • Quantitative vs qualitative data • Quantitative: observations are numerical, easy to statistically analyze. Empirical data that is numerical. • Qualitative: descriptive narration of something. Non -‐numerical. THE PLACE OF THEORY IN RESEARCH • A paradigm is a fundamental model that organizes our view of some social phenomena. • Spiritualism vs naturalism. • Spiritualistic explanation, of why people committed the crime, it was the devil. For ages they believed the spiritualistic explanations. • Naturalism, there are naturalistic explanations for why people commit crimes • People are inherently good vs people are inherently bad. • A theory is a logical interrelated set of propositions (hypothesis) about empirical reality. • Theoretical constructs: the factors that the theory emphasizes. The concepts that a theory directs our attention to. • For a theory to be useful it has to be falsifiable: we have to be able to put the theory to the test and collect data. We have to test it and see if the claims are valid or not. • A hypothesis is a statement that anticipates the relationship between theoretical constructs. We test hypothesis to determine the validity of a theory. Hypothesis are sets of “if” and “then” statements. • When we collect data to test a hypothesis, we do a hypothesis testing: • The research hypothesis is an affirmative statement of an expected relationship between variables. (H1) • The null hypothesis is a statement referring to a result that would run counter to the anticipated relationship between variables (H0). 4 MEASURING THEORETICAL CONSTRUCTS • Variable: the eye color. Anything we can measure that takes on distinct characteristics or properties. Hair color, age, height, money someone makes. • Criminological examples of variables: criminal (how much someone is a criminal), self control, depression, neighborhood. • Attribute, the different characteristics. • When the purpose of research is description, we are largely just talking about the distribution of attributes on one or more variables. • The US census • When the purpose of research is explanation, we see if there is a relationship between the attributes for two different variables. • Frequency of attending class and grades DIFFERENT TYPES OF VARIABLES • Independent variable (IV): something we believes explains the occurrence of something else. • the attributes for an IV are believed to cause the attributes for another variable. • Dependent variable (DV): the thing that we are trying to explain. Attendance and grades: grades are the DV, and attendance the IV. • Explain wining football games? If they trained in the rain more often, that would be a dependent variable. Body weight? Calories, height, genetics • There are different ways of thinking about the relation between independent variable and dependent variable: • IV à DV • Cause à effect • X à Y • Y= f(X)the DV is a result of the functioning on the IV. 5 • Examples of DV/IV relationships • Class attendance à+à good grades (if you attend class more often, you attend higher grades. More brings to something more) • Self control à -‐ à delinquency (less delinquency) • Effective parenting à -‐ à alcohol abuse (more parenting brings to less alcohol use) • Smoking à + à lung cancer. • Mediating variable: why an IV has a influence on a DV. • Mediating: comes between. • Self control à + à class attendance à + à grades. Class attendance: variable. Why does self control have better grades? Because they’re more likely to attend class, and as a consequence to have better grades. Mediated by the class attendance. • HIV status à + à AIDS status à + à early death. HIV itself doesn’t cause death, but the fact that if we have HIV we get AIDS does. AIDS mediates. • Moderating variable: a variable that alters or modify how an IV influences a DV. It doesn’t come in between, it changes it. When taking drugs, if we drink alcohol we are more likely to be drowsy. Alcohol changes the way drugs act on us. • Experiencing discrimination, committing delinquency is moderated by social support form parents. Two people, one of them has a lot of parents support and the other lives with his family but he doesn’t have a good relationship with his parents. The first person is least likely to commit delinquency because he has an open relationship with his parents, they can moderate and change the way he think s. ILLUSTRATING THEORETICAL RELATIONSHIP Fig.1. 6 INTERACTION OF THEORY, RESEARCH, AND CJ POLICIES AND PRGRAMS • Many CJ policies and programs have theoretical foundations: CHAPTER 5 • A concept is a mental image that summarizes a set of similar observations, feelings or ideas. We can think of an ide a, but until we decide to make choices of how we want to explain this concept, is a mental image. The concept of love: we can’t see it, but we can think of it. The concept of machiavelism and of self-‐ control. • Conceptualization: the process of specifying what is meant by a term by transforming mental images into something definable. Defining what love is. Specify what is meant by the term love. • Conceptual definition: the working definition of a concept. This is part of the process of conceptualization. • Concepts can be unidimensional (only one aspect) or multidimensional (having multiple aspects). • An operation is the procedure for measuring the concepts; the identification of a value of a variable. • Operationalization: the process of specifying the operations (measures) that will indicate the value of a variable. The can measure love with a survey about how warm they are with their loved ones. Ex, love, machiavelism (manipulate others for personal game), self-‐control. • Operational definition: the specific wording or procedure used to measure a concept. This is part of the process of operationalization. • Indicator: the question or other operation used to indicate the value of cases on a variable. 7 • Measurement choices: • Use of available data: URC data, local police records, census data etc. • Constructing survey questions: encompass public opinion polls. Placing people in the scenario and they see how they would react. • Making direct observations: in laboratory environments of other settings physically observing someone’s behavior. • Collect unobtrusive measures: physical trace evidence; archives; simple observations; contrived observation. • Exhaustiveness: the measurement of a variable must include all possible attributes. We must be able to classify every observation. Ex, survey on someone’s occupation: we could leave a blan k space and let them write it down. Then someone would have to read them all and classify them. Or they could provide 25 categories. The only problem is if the survey maker doesn’t provide enough categories and people get confused, and they would check a wrong one or decide not to respond. • Exclusiveness: each attribute for a variable should be mutually exclusive from every other attribute. Ex: what’s your college GPA? The options provided have to mutually exclusive. Ex: 0 – 1.00. 1.01-‐ 2.00. 2.01—3.00. 2.50-‐3.50. this is wrong because we have two categories that overlap each other. It is not accurate. • 4 different levels of measurement: • 1, nominal. Attributes for a variable have no inherent hierarchy or order. Ex, gender, race, panther ID, crime type. The a ttributes can’t be ranked as more or less than something. There’s no more or less. • 2, ordinal: attributes can be logically ranks – there can be ‘more’ or ‘less’ of something. Ex, education, support for the death penalty. • 3, interval: attributes can be ranked AND the distance/difference betwee attributes is assumed to be equal. Ex, IQ score, 8 temperature. Comparing someone who has an IQ of 90 and one of 100, is the same thing as comparing someone who has an IQ of 100 and one with 110. • 4, ratio: attributes can be ranked AND the distance between attributes is equal AND there is a true zero value starting point. Ex, income, age. They can all start with 0. • Reliability: when a measure yields consistent scores or observations on different occasions or in differ ent ways • Reliability can be assessed when something is measured: repeatedly • ways to assess reliability: • 1, test-‐retest reliability: measuring something at multiple points in time to see if you get the same result. Ex, asking college students to report their GPA. You always get the same answers over and over again. • 2, interrater reliability: having multiple people record the same measurements. Ex, to the extent that multiple raters provide the same score, this suggests reliability. • 3, internal consistency: using multiple indicators to measure a single concept. is there a consistent pattern in responses? Ex. Strong internal consistency: when the answers are all ‘strongly agree’ or ‘agree’. Weak internal consistency: when the answers are all different ‘strongly disagree’ ‘disagree’ ‘agree’ ‘strongly agree’. • 4, split-‐half reliability: splitting items intended to measure a single concept into two samples to see if the average scores across the two samples ae similar. Used in exploratory research. ex, we have 16 items. we can split them into 8 (1-‐8) and 8 (9-‐16). • 5, false measures reliability: inserting items into questionnaires concerning behavior that is non-‐existent, suggesting the reliability of other items on a survey could be in jeopardy. If people say 9 they’ve done something it doesn’t exist, then we realize that their other responses may not be reliable. • Assessing measurement validity: • Measurement validity: when a measure measures what it is presumed to measure. Ex, in the BMI (body mass index) a valid way to measure someone’s overall health risk? • 1, face validity: does the measure seem to be a reasonable w ay, on its face, to measure a concept? • 2, criterion-‐related validity: comparing a measure to some external source (criteria). Ex, the SAT and GPA. • 3, construct validity: when a particular variable is related to other theoretical variable as expected. Is like testing a theory. • 4, content validity: the extent to which a variable encompasses the concept you are trying to measure. • 5, multiple measure validity: comparing an individual measure to alternative sources of the same concept. Ex, compare observational rater scores of child aggression to maternal reports of child aggression. • Composite measures in research: • Composite measure: using multiple indicators to measure a single concept. • 1, typology: combine together the data from two or more variables to create a set of types for comparison. • 2, index: averaging together scores on different items to create an overall single score. • 3, variety index: specific to measuring delinquency/crime, is the sum total of the number of different acts someone reports. CHAPTER 6 10 THE MEASUREMENT OF CRIMINAL BEHAVIOR DELIQUENCY VS CRIME VS STATUS OFFENSES • Delinquency: acts defined as violations of law by individuals under the age of 18 years old. • Crime: acts defined as violations of law by individuals who are at least 18 years old • Status offense: underage drinking. Acts defined as violations of law because of the status of individuals committing the act. When you’re not 18 and you run away from home. • Criminal offense: individual act that can result in a charge for a crime having been committed • Criminal incident: one or more offenses committed within the same place and/or time. PURPOSES OF MEASURING CRIME • Monitoring: tracking trends across time and space. • Agency accountability: stand and/or federal funding is often tied to reporting requirements. You have to demonstrate its effectiveness when you want to start using a new program. • Research: establishing cause and effect relationships: what predicts delinquency/crime? MEASURING CRIMINAL BEHAVIOUR • 1, official police records. • A. crime known to the police: • we consider the data can be reliable if a crime is reported or discovered by the police. Homicide data is reliable. • Poor data resource is a crime often goes undetected by the police • Officers sometimes have discretion in deciding to arrest someone or not. • Dark figure of crime: when crimes are not reported to the police. DUI. 30% of the population is not being arrested for drinking and driving. 11 • B, FBI Uniform Crime Report (UCR) • Started in 1930 and includes a limited number of crime types. • Provides a summary-‐based measure of criminal behavior: no information is presented on individual offenders. (on groups on people) • Produced on a semi-‐annual basis. • States vary on definition of UCR, which is many crimes are not reported to them. • Part 1 offenses ( index crimes): reported to the police, arrest doesn’t have to be included in calculation of crime rates. Violent rate: murder, sexual battery (rape), robbery, aggravated assault. Property: burglary, larceny (theft), • Part 2 offenses: less serious offenses like vandalism, DUI. If there is no arrest, then the offense is not included in the published UCR statistics. DATA QUALITY ISSUES WITH THE UCR • THE HIERARCHY RULE: • Only the most serious offense in a given incident is recorded. • Not all police agencies report data to the FBI. 95% of agencies report to them. • Procedures for data collection and reporting vary across jurisdictions (lack of consistency) • Changes in crime rates may reflect changes in reporting pr actices, not actual change sin crime. Changes in reporting the crime doesn’t have to be a change in behavior. There was a change in the definition of sexual assault, not because of a change of behavior. • Clerical errors, staff turnover, database limitation s. 12 WAYS TO MEASURE CRIME: 1. OFFICIAL POLICE RECORDS • C. FBI Supplement homicide Report (SHR) • Started in 1961, detailed information for individual and specific crime of homicide. • Victim info, offender info, weapon used, relationship between victim and offender, time and location. Stranger homicide/homicide between people who knew each other. 13
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