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SOC 315 > Midterm > Flashcards

Midterm Flashcards

1
Q

Common components of a theory

A
  • definitions: what are key terms?
  • descriptions: characteristics?
  • relational statements; deterministic (variables are related), probabilistic (the relationship isn’t inevitable)
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2
Q

middle range theories

A
  • limited in scope
  • testable
  • ex. Durkheim’s theory of suicide
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3
Q

Grand theories

A
  • general and abstract
  • provide ways to look at the world
  • ex. structural functionalism
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4
Q

deductive method

A
  • most common approach to social research
  • begins with a theory
  • understand specific phenomenon through background research
  • develop hypothesis
  • test with empirical data
  • revise if necessary
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5
Q

inductive method

A
  • theories and interpretations are the outcomes of the theory
  • gather and examine data first
  • create theory from observations
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6
Q

grounded theory

A
  • deriving theory from observations

- used by qualitative researchers

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7
Q

epistemology

A
  • how do we know the world?

- how does knowledge become acquired?

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8
Q

positivism

A
  • follows the natural sciences
  • uses the principle of empiricism
  • generate hypothesis to test (deduction)
  • can provide foundation for induction too
  • science is value-free (intersubjectivity)
  • scientific statements are of key importance
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9
Q

interpretivism

A
  • critique on positivism
  • goal is to grasp the subjective meaning of people’s lives
  • people interpret the reality of their own lives
  • views the social world from the POV of the social actor
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10
Q

symbolic interactionism

A
  • major perspective in soc that uses interpretism

- ex. George herbert mead, Irving Goffman

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11
Q

critical approaches/theory

A
  • critiques of positivism
  • use both inductive and deductive methods
  • reject “value-free” science
  • anti-oppressive in practice and political in nature (Karl Marx and conflict theory)
  • involves praxis: putting one’s theoretical positions into practice
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12
Q

ontological considerations

A
  • what is considered real

- ontological assumptions about reality effect: research question formulation; the way research is carried out

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13
Q

ontological debate 1: objectivist perspective

A
  • social phenomena have an objective reality, independent of our perceptions
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14
Q

ontological debate 2: constructionist perspective

A
  • constructionist hard: reality is merely a set of mental constructions; Nietzsche: there at no facts, only interpretations
  • constructionist soft: more middle ground; there is an objective social reality that is marred by human interpretation
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15
Q

quantitative research

A
  • uses numbers and stats in the collection and analysis of data
  • surveys, demographics
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16
Q

qualitative research

A
  • uses mainly words and other non-numeric symbols in the collection and analysis of data
  • concerned with things that can’t be quantified
  • motivations, reasonings, beliefs, understandings and how that shapes what they do
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17
Q

values: a researcher’s values can contribute to bias in research

A
  • choice of topic
  • formulation of research question
  • choice of method
  • formulation of research design and data collection methods
  • actual data collection
  • analysis of data
  • interpretation of data
  • conclucions
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18
Q

values: reflexivity

A
  • researchers’ awareness that their values and decisions have an impact on the research
  • personal biases are made explicit
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19
Q

values: 3 different positions on values in social research

A
  1. research should be value-free
  2. research cannot be value-free, but researchers should be open and explicit about their values
  3. researchers should use their values to direct and interpret their investigations; value commitment is a good thing for researchers to have
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20
Q

politics in social researchers

A
  • researchers sometimes “take sides”
  • funding: who gets it? are there strings attached? govt funding as strategic
  • research subjects/participants: gatekeepers; who gets access?
  • research findings: what sorts of findings are “acceptable” to those who fund or publish research?
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21
Q

research questions: key characteristics

A
  • as clear as possible so it is understandable to others
  • be researchable
  • relate in some ways to other research
  • neither too broad nor too narrow
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22
Q

research questions: choice of research orientations, design and method must match question

A
  • is it a brand new phenomenon?
  • world views?
  • measuring impact
  • hypothesis testing?
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23
Q

research question

A
  • states the purpose of the study in the form of a question
  • qualitative: less specific research question; inductive; no hypothesis
  • quantitative: can test causal models; deductive; narrowed research question to make a testable hypothesis
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24
Q

research design

A
  • a framework for the collection and analysis of data
  • ask: what do I want to learn? what is the nature of research question? what kind of explanation will I want? (typically nomothetic and idiographic)
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25
Q

nomothetic explanations

A
  • involve attributions of cause and effect, expressed in terms of general laws and principles
  • typically quantitative
  • 3 criteria of causation: correlation, time order, non-spuriousness
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26
Q

idiographic explanations

A
  • involve a rich description of a person or group and seek to explain the particular
  • typically quite limited
  • typically qualitative
  • it is not meant to apply to persons or groups who were not part of the study
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27
Q

select method

A
  • questionnaire
  • structured interview and semi-structured
  • participant observation
  • ethnography
  • experiments
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28
Q

experimental design

A
  • true experiments are common in psych and organizational studies but rare in soc and pols
  • many variables of interest are not subject to experimental manipulation
  • ethical concerns preclude performing experiments
  • many phenomena of interest have long-term, complex causes that cannot be simulated in experiments
  • even where applicable, experimental models do not get at the perceptions and feelings of research subjects
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29
Q

field experiments

A
  • conducted in real-life surroundings

- difficult to set up due to ethical concerns

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30
Q

lab experiments

A
  • take place in artificial environments
  • controls research experiment
  • easier to randomly assign research subjects; enhanced internal validity
  • easier to replicate
  • weak external validity
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31
Q

key concepts to relevant experiments

A
  • experimental or treatment group
  • control group
  • random assignment
  • pre-test
  • post-test
  • causality underpins different types of research design
  • expressed by variables
  • IV are manipulated to see if they have impact on DV
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32
Q

classic experimental design

A
  1. IV and DV are identified
  2. the DV is observed/measured in each of the control and treatment groups and recorded at T1
  3. treatment group receives while control group is left alone
  4. DV measured in post-test and recoded as occurring at T2
  5. any changes in each group are noted (ideally will only occur in treatment group)
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33
Q

internal validity

A
  • validity in social research assesses the extent to which a research study addresses the issue that the research is intended to explore
  • concerned with extent to which any given research design is a good test of the hypothesis under consideration
  • third variable problem
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34
Q

Cook and Campbell (1979) threats to internal validity when lacking random assignment or control group

A
  1. history: some event occurring after the treatment was given may have influenced the DV
  2. testing: the pre-test may have influenced the DV
  3. instrumentation: changes in the way a test is administered may account for pre/post-test differences
  4. mortality: participants leave the experiment before it is over
  5. maturation: participants change over time
  6. selection: post-test differences between the control and experimental groups may have been caused by pre-existing differences
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35
Q

measurement validity (construct validity)

A
  • “are you measuring what you want to measure?”
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36
Q

external validity: 2 primary causes

A
  1. are the findings applicable to situations outside the research environment
  2. can the findings be generalized beyond the people or cases studied?
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37
Q

Cook and Campbell (1979) threats to external validity in experimental research

A
  1. the representativeness of the study participants
  2. effects of the setting
  3. effect of pre-testing
  4. reactive effects of experimental arrangements
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38
Q

replicability

A
  • the results remain the same when others repeat all or part of a study
  • the procedures used to conduct the research are sound and spelled out
  • very important
  • currently in applicability crisis in research
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39
Q

the laboratory experiment

A
  • greater control over environment is an asset
  • easier to assign participants randomly to conditions
  • limitations: low external validity; life in a test tube?
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40
Q

quasi-experiments

A
  • differ from true experiments in that internal validity is harder to establish
  • less control over variables
  • ex. natural experiments –> covid pandemic
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41
Q

cross-sectional design

A
  • no before or after comparisons
  • do not include manipulation of the IV
  • ex. questionnaires, structured interviews/observations
  • 2 or more variables are measured in order to detect patterns of associations
  • issues with internal validity and establishing direction of causation
  • issues with external validity: random method should be used
  • can examine the effect of variables that cannot be manipulated in experiments
  • tend to be quantitative
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42
Q

longitudinal design

A
  • cases are examined at a particular time (T1) and again at a later time(s) T2, T3, etc
  • provide info about the time order of changes in certain variables
  • helps to establish the direction of causation
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43
Q

longitudinal design: 2 basic types

A
  1. panel study: the same people, households, orgs. etc are studied at different times
  2. cohort study: people sharing the same experience are studied at different times, but different people may be studied at each time
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44
Q

longitudinal design: drawbacks

A
  • attrition over time
  • may be difficult to determine when subsequent waves should be conducted
  • panel conditioning: people’s attitudes/behaviours may change as a result of participation in a panel
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45
Q

case study design

A
  • basic one involves in-depth study of a single case
  • a single case can be a person, family, org, event, country etc
  • qualitative and/or quantitative methods
  • tends to be inductive and start with qualitative approach
  • achieving external validity is not main reason for case study
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46
Q

case study design: 3 types

A
  1. critical case: illustrates the conditions under which a certain hypothesis holds or does not hold
  2. extreme (or unique) case: illustrates unusual cases which help in understanding the more common ones
  3. revelatory case: examines a case or context never before studied
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47
Q

research ethics

A
  • need to be addressed in the initial stages of a study and kept in mind in every phase
  • first priority of a researcher: ensure participants are not being harmed
  • participant safety > knowledge
  • researchers must constantly balance between potential gain and risk of harm
  • SSHRC, CIHR, NSERC
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48
Q

research ethics board (REB)

A
  • policy to due to inadvertent harm caused to participants
  • all Canadian research requires REB approval FIRST; may require modifications, appeal process
  • conflict of interests roles
  • can be found in many institutions comprised of people from various interest groups
49
Q

ethics approval in quantitative research

A
  • considered by some to be easier to obtain
  • stated hypothesis and specific plan for testing
  • some REB favour quantitative work because it’s considered to be more scientific
50
Q

ethics approval in qualitative research

A
  • flexibility for emerging themes means indeterminate methods
  • may capture data on people that would not want their activities observed
  • a cautious REB can: restrict project, prevent funding, prevent project
51
Q

general ethics principles

A
  • TCPS2 provides for variation in research methods
  • 3 core overlapping principles: respect for persons, concern for welfare, justice
  • consent form
  • front end deception
  • debriefing
  • covert research is very intrusive
  • duty to report
52
Q

ethics information sheet outline

A
  • research project
  • methods
  • potential risks/benefits
  • names of those in charge
  • assurances of confidentiality
  • funding
  • compensation
  • how data will be stored
  • institution and contact
  • publishing info
53
Q

quantitative research

A
  • epistemological and ontological assumption
  • the collection of numerical data
  • a deductive relationship between theory and research
  • a preference for the natural science approach to research (positivism)
  • an objectivist conception of social reality
  • major concern: measurement validity
54
Q

quantitative research: the main steps

A
  1. theory
  2. hypothesis
  3. research design
  4. devise measures of concepts
  5. select research site(s)
  6. select research participants
  7. administer research instruments/collect data
  8. process data
  9. analyze data
  10. finding/conclusion
  11. write up findings/conclusions
55
Q

operationalization

A
  • the process of converting concepts into indicators or into specific questions in a questionnaire or an interview
  • you need questions that allow you to measure the phenomenon you are trying to study
56
Q

concepts

A
  • the ideas or mental representations of things
  • may be independent (manipulated) or dependent (outcome) variables
  • measurement allows a delineation of fine difference between people/issues we are interested in
  • what is the correlation?
57
Q

concepts: 2 types of definition

A
  1. nominal: describes the concept in words, much like a dictionary definition
  2. operational: describes how the concept is to be measured
58
Q

indicators

A
  • tell us that there may be a link and indicate how strong that link may be
  • usually one indicator for each concept is adequate
  • advantageous to use more than one indicator of a concept
  • can be direct or indirect
59
Q

benefits of using multiple indicators to measure a concept

A
  • reduces likelihood of misclassifying some people because the language of question is misunderstood
  • endures definition of underlying concept is understood correctly
  • gets access to a wider range of issues related to concept
  • allows for factor and cluster analysis
  • helps to weed out response sets
60
Q

Likert scale

A
  • very common way of collecting data on peoples opinions
  • asked to give their level of agreement with statements
  • items must be statements
  • must all relate to the same subject
  • options should be interrelated
61
Q

coding unstructured data

A
  • derive codes: labels or titles given to the themes or categories
  • assign numbers to codes
  • basic principles to observe: categories must be exhaustive and not overlap; must be clear rules for how codes are applied
  • very unreliable and little validity was of coding data
62
Q

reliability: stability over time

A
  • whether the results of a measure fluctuate as time progresses, assuming that what’s being measured isn’t changing
  • can be measured using the test-retest method
  • difficult to quantify because of factors in passage of time
63
Q

reliability: internal reliability

A
  • whether multiple measure that are administered in one sitting are consistent
  • can be measured using Cronbach’s alpha coefficient or the split-half method
64
Q

reliability: inter-observer consistency

A
  • all observers should classify behaviour or attitudes in the same way
65
Q

face validity

A
  • established if at first glance the measure appears to be valid
66
Q

concurrent validity:

A
  • established if the measure correlates with some criterion thought to be relevant to the concept
  • a lack of correlation brings some doubt to the validity of the original measure
67
Q

construct validity

A
  • established if the concepts relate to each other in a way that is consistent with the researcher’s theory
  • confirmed by seeing that the results match what would be predicted given the theory
68
Q

convergent validity

A
  • established if a measure of a concept correlates with a second measure of the concept that uses a different measurement technique
  • a measure that is not reliable will not be valid
  • a measure may be invalid but still reliable
69
Q

main goals of quantitative research

A
  • measurement
  • establish causality (internal validity)
  • generalization of findings to those not studied
  • replication
70
Q

critiques of quantitative research

A
  • researchers fail to distinguish people and social institutions from “the world of nature”
  • the measurement process produces an artificial and false sense of precision and accuracy
  • the reliance on instruments and procedure produces a disjuncture between research and everyday life
  • the analysis of relationships between variables ignores peoples everyday experiences and how they are defined and interpreted
  • explanations for findings may not address the perceptions of the people to whom the findings purportedly pertain
  • quantitative researchers tend to assume an objectivist ontology - social order is fixed
71
Q

open questions: advantages

A
  • allow for replies that researcher may not have contemplated
  • make it possible to tap the participants’ unprompted knowledge
  • salience of particular issues for respondents can be examined
  • can generate fixed choice format answers
72
Q

open questions: disadvantages

A
  • more time consuming
  • answers must be coded
  • less convenient to compose an answer
  • may require transcribing
  • face inter-interviewer variability
73
Q

closed questions: advantages

A
  • minimize intra and inter-interviewer variability
  • may make it easier to understand question because answers are provided
  • can be answered quickly and easily, reduces response rate issues
74
Q

closed questions: disadvantages

A
  • loss of spontaneity and authenticity because relevant answers may be excluded from choices provided
  • respondents may differ in the interpretation of the wording of fixed responses
  • respondents may not find a fixed response that they feel applies to them
75
Q

prominent sources of error in survey research

A
  • poorly worded questions
  • interviewer error in asking a question
  • misunderstanding on part of the interviewee
  • interviewee lapses in memory
  • interviewer error in recording info
  • mistakes in entering data into computer
  • baises related to characteristics of interviewers and/or interviewee
76
Q

types of questions

A
  • personal factual questions - demographic
  • factual questions about others
  • factual questions about entity or event
  • questions about attitudes, beliefs, knowledge
77
Q

rules for designing questions

A
  • keep the research question in mind
  • focus on exactly what you want to know
  • put yourself in the position of the respondent
  • consistent wording and balanced questions
  • don’t overstretch respondents memories
  • question order
  • run a pilot study
  • using existing questions can be beneficial
78
Q

what to avoid when designing questions

A
  • avoid: ambiguous terms, long questions, double-barreled questions, very general questions, leading questions, 2 in one questions, negative/double-negatives
  • minimize technical terms
  • carefully consider “don’t know” answers
  • avoid provoking response set
79
Q

vignette question

A
  • presenting people with one or more scenarios and asking them how they would respond
  • anchor the choices in realistic situations
  • weakness: how people say they would act in a situation can be different from how they will actually act
  • can provide useful info or at least a starting point for further research
80
Q

telephone interviews: strengths

A
  • good for national or govt research
  • cheaper and quicker to administer
  • easier to supervise and therefore reduce interviewer errors upfront
  • reduced bias arising from “interviewer effect”
81
Q

telephone interviews: disadvantages

A
  • may exclude people without phones, unlisted numbers, cell phones and hearing impaired
  • hard to sustain for long period of time
  • cannot collect additional information
  • difficult to be sure targetted respondent is actually one answering
  • visual aids cannot be used to assist
82
Q

online interviews: advantages

A
  • quality of face-to-face interviewing with efficiency and economy of the internet
  • opportunity for more considered, fuller responses
  • ease of contact for follow up
  • no need to transcribe
83
Q

online interviews: disadvantages

A
  • fairly high drop out rate, but may be overcome by developing mutual trust
  • answers may be short on detail
84
Q

conducting interviews

A
  • know the schedule
  • prepare the introduction
  • establish the rapport
  • introductory statement
85
Q

questionnaires

A
  • essentially structured interviews without an interviewer
  • involve filling out a form
  • has to be very clear and easy to follow
  • have fewer open questions, have short simple designs
  • online surveys popularity is growing
  • email surveys
  • web surveys
86
Q

questionnaires: advantages

A
  • cheaper, quicker and more efficient to administer
  • no interviewer effects
  • social desirability bias seems to be reduced
87
Q

questionnaires: disadvantages

A
  • researcher cannot explain the question
  • greater risk of missing data because of a lack of probing or supervision
  • difficult to ask a lot of questions and open questions
  • cannot track whether the questions were answered in original order = order effects may occur
  • not appropriate for certain respondents
  • designated respondent may not have completed it
88
Q

researcher driven diaries

A
  • form of questionnaire
  • participants record their feelings, perceptions, actions etc on a form shortly after they occur
  • participants should be given explicit instructions on how to complete, the time periods for recording responses, types of experiences to be recorded
  • used for qualitative and quantitative
89
Q

secondary analysis of survey data

A
  • large amounts of quantitative data already exist
  • raw stat data available on many topics
  • survey data is needed as a check and counterpoint to official stats
90
Q

secondary analysis of survey data: advantages

A
  • cost and time
  • high-quality data
  • opportunity for longitudinal analysis
  • more time for data analysis
  • fulfill wider obligations of social research
  • opportunities for cross-cultural studies
  • subgroup analysis
  • re-analysis
91
Q

secondary analysis of survey data: disadvantages

A
  • lack of familiarity with someone else’s data
  • data sets can be complex
  • ecological fallacy: data gathered by region or neighbourhood are used to make statements about individuals
  • no control over data quality
  • absence of key variables
92
Q

element or unit

A
  • a single case in a population; in social science, its usually a person; can sample other things (nations, regions, schools etc)
93
Q

population

A
  • all the cases about which you are seeking knowledge or all the cases to which your conclusions might apply
94
Q

sampling frame

A
  • the list of elements from which the sample will be selected
95
Q

sample

A
  • the elements selected for investigation; a subset of the population - may involve probability or non-probability
96
Q

representative sample

A
  • a sample that is a microcosm of the population; one that represents its characteristics
97
Q

calculating a representative sample

A
  • sample size doesn’t change much for pops > 2000
  • margin of error between 1-5%
  • confidence level 99-95%
98
Q

probability sample

A
  • selected using a random process, such that each unit in the sampling frame has a known chance of being selected; goal is to minimize sampling error
99
Q

non-probability sample

A
  • a sample selected using a non-random method
100
Q

sampling error

A
  • error of estimation that occurs if there is a difference between the characteristics of the sample and those of the pop from which it was selected
  • virtually impossible to eliminate
101
Q

non-response

A
  • a situation that occurs whenever some unit selected for the sample refuses or doesn’t participate
102
Q

census

A
  • data collected from all elements of the population rather than from a sample
103
Q

3 sources of bias in sampling

A
  1. not using a random method to pick sample
  2. the sampling frame
  3. non-response
104
Q

process of simple random sample

A
  1. devise a sampling frame
  2. number all of the elements consecutively starting at 1
  3. pick a sample size (n) from the total pop (N)
  4. use a random number table or program to generate a list of random numbers
  5. the sample will be comprised of the cases whose element numbers match the randomly generated ones
    - sampling ratio = n/N
105
Q

systematic sample

A
  • selected directly from the sampling frame, without using random numbers
  • i= size of sampling interval
  • to begin choose a number at random from 1 to i
  • potential issue is periodicity: when/if the cases in the frame are arranged in some systematic order
106
Q

stratified random sampling

A
  • ensures that subgroups in the population are proportionally represented in the sample
107
Q

multi-stage cluster sampling

A
  • used for large populations
  • involves 2 or more stages
  • issues: technical complications; cluster samples are usually stratified as well
108
Q

sample size

A
  • the absolute size of the sample matters
  • as sample size increases, sample error tends to decrease
  • common sample sizes: 100, 400, 900, 1600, 2500
  • each size increase cuts the sampling error by 1/2, 1/3, 1/4, 1/5 respectively
  • the biggest change occurs between 100 and 400
  • often dictated by financial concerns
109
Q

issues with sample size: heterogeneity of the population

A
  • generally the greater the heterogeneity of the pop on the characteristics of interest, the larger the sample size should be
110
Q

issues with sample size: kind of analysis

A
  • the size needed may vary depending on what sort of analysis will be done
  • if small groups in the pop are to be compared to larger groups, it may be necessary to oversample the smaller group in order to make meaningful comparisons
  • certain stat procedures, such as some multivariate analyses, require large sample sizes to work
111
Q

convenience sampling

A
  • cases are included because they are readily available
  • problem: one cannot generalize the results to some larger population with any confidence
  • useful for: pilot studies, testing reliability of measures for larger studies, developing ideas, learning how to do research etc.
112
Q

snowball sampling

A
  • form of convenience sampling

- the researcher makes contact with some individuals, who in turn provide contacts for other participants

113
Q

quota sampling

A
  • collecting a specified number of cases in particular categories to match the proportion of cases in that category in the pop
  • random methods are NOT used to fill the quotas
  • weaknesses: not likely to be representative, judgements about eligibility may be incorrect, not appropriate for calculating standard error term
114
Q

structured observation and sampling

A
  • often no sample frame
  • may involve time and place sampling
  • may include behaviour sampling
115
Q

limits to generalization

A
  • even when a sample is selected using probability sampling, any findings can be generalized only to the population from which the sample was taken
  • do the findings from an earlier date still apply today?
116
Q

error sources

A
  • sampling error
  • sampling-related error
  • data collection error
  • data processing error
117
Q

virtual sampling issues

A
  • not everyone is online and has the technical ability to handle these kinds of questionnaires
  • internet users are a biased sample of the pop
  • few sampling frames exist from the general online pop
118
Q

covert research

A
  • very intrusive
  • no consent
  • benefits must outweigh any harm to participants
  • little to no concern over reactivity
  • permission if over sought after the fact
  • researchers must ensure anonymity of non-consenting participants

SOC 315 (2 decks)

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