Brainscape's Knowledge GenomeTM

Browse over 1 million classes created by top students, professors, publishers, and experts.


See full index

SOC200 > SOC200 - Conceptualization (Chapters 4+5) > Flashcards

SOC200 - Conceptualization (Chapters 4+5) Flashcards

1
Q

UNITS OF ANALYSIS

A
  • what/who being studied
  • Identifying can difficult
  • Periodically diff betw who/what we observe to get info we need + who/what generalizing about based on info
  • what characteristics interested in observing
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

UNITS OF ANALYSIS

A

•info from individuals + pooling info to find patterns
•Individuals unit of observation, but aggregates units of analysis
•Derive characteristic of social groups from those of individual members - Couples, cities, gangs, churches
Social artifacts: Concrete items – books, paintings, buildings/Social interactions – Weddings, friendship

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

UNITS OF ANALYSIS AND FAULTY REASONING: ECOLOGICAL FALLACY

A

assume observations at broader unit of analysis say something about indivs comprising unit/equally distributed to individuals in that group
Eg: Neighbourhoods with lots Protestants higher suicide rate than lots of Catholics
•couldn’t infer from aggregate level data because you don’t have individual data
•individualistic fallacy: bias, racism, prejudice
•can’t generalize characteristic of one person to whole groups

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

CONCEPTUALIZATION

A

process of agreement about what concepts mean
•Indicators & Dimensions: Sign of presence/absence of concept
•Definitions: Real, Nominal + Operational
•Conceptual Order
•If common images changes over time, then concept means something else

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

OPERATIONALIZATION

A

Specifying exact procedures involved in measuring variables represent concepts (the operational definition)
•Operationalization Choices
•Levels of Measurement

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

MEASUREMENT

A

measures use depend on operational definition + way available data collected
•Accuracy vs. Precision
•Reliability vs. Validity
•Indexes vs. Scales

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

CONCEPTUALIZATION: Interchangeability of Indicators

A

doesn’t matter if researchers disagree on specific indicators only matters if all indicators used do not behave same way in testing

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

CONCEPTUALIZATION: Interchangeability of Indicators

A

If some indicators behave differently, then possible they represent diff dimension of the concept/don’t represent that concept at all.
•Example: all indicators measure level of reckless driving, if you dropped, one you can still measure it

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

CONCEPTUALIZATION: Real Definitions

A

statement of essential nature of some entity
IMPOSSIBLE – mistakes construct for a real entity + produces vague definitions
•only exists in theory

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

CONCEPTUALIZATION: Nominal Definitions

A

arbitrary definition

based on conventions of how term commonly used everyday conceptual understanding

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

CONCEPTUALIZATION: Operational Definitions

A

specifies exactly how a concept will be measured

high clarity by limiting definition - how it is measured only means that thing

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

CONCEPTUALIZATION: Conceptual Order

A

need to refine/expand meaning, their increased understanding of the concept necessitates it
may divide up concept into diff dimensions + subdimensions
•Hermeneutic circle: cyclical process of ever deeper understanding

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

OPERATIONALIZATION: Range of Variation

A

what distance betw highest + lowest points in data
•Example from HBSC Survey: frequency distribution, maybe decide $100+
oHow much variation do you need?

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

OPERATIONALIZATION: Degree of Precision

A

degree of precision at the time of data collection will affect what you can and cannot do with the data later
you can always break it down into less precise units
•If you don’t need to know exactly how much they smoke, then put it into categories

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

Degree of Precision is Important

A

cannot collect more general data then break it down to specific later
•More precise data has more informative models
•General data limits types of models you can use
•If possible more detail, can aggreagate later
•More precise – more measurement validity
•Collapsing data is more vague, and less measurement power

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

LEVELS OF MEASUREMENT: Nominal Measure

A

Variables with attributes merely categorical, no rank, no numeric value
different from each other and have no order
Yes No

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
17
Q

LEVELS OF MEASUREMENT: Ordinal Measure

A

Variables with attributes rank ordered
can’t really pin down range/distance between attributes
Never, Occasionally, Regularly, Frequently, All the time, or 0-10, 11-20, etc.
•Ordinal - percentage

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
18
Q

LEVELS OF MEASUREMENT: Interval Measure

A

Variables with attributes can rank + equal distances, no true 0
IQ Score 60,70,80,90,100,110,120,130

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
19
Q

LEVELS OF MEASUREMENT: Ratio Measure

A

Interval measure but with a true 0 point
income, kelvin-0,1,2,3,4,5,6,7,8,9,10,11,12,13,
•Always nice to collect data at ratio level
•Certain types of analysis requires certain level of measurement
•Conclusions have to reflect data you have
•Ratio–mean

20
Q

Reliability

A
  • Consistent = reliable
  • We don’t know whether 1 time measurement affected by other factors
  • Replication important
21
Q

Validity

A

-Exists when measures accurately reflect the concept it is intended to measure
•Measure that accurately reflects concept it is intended to measure

22
Q

Reliable, not valid

A

consistent, but don’t hit target

oConcepts require rethinking

23
Q

Valid, not reliable

A

measures scattered, one point, not consistent in measurement

24
Q

Neither valid, nor reliable

A

no point in target, not very well clustered

25
Q

Both valid + reliable

A

points clustered around target, Consistent and close to concept

26
Q

Methods for Creating Reliable Measures: 1.Test-Retest Method

A

Make the same measurement more than once

27
Q

Methods for Creating Reliable Measures: Split-Half Method

A

Good for measuring complex concepts comprised of several indicators (good health, religiosity, prejudice).
Statistical method to see how correlated indicators are: Randomly assign half the indicators one set + other indicators as another set
If highly positively correlated, measuring same thing + are reliable measures of your concept.

28
Q

Methods for Creating Reliable Measures: Using Established Measures

A

•Using established measures: previously used + known reliable scales
Rely instead on measures that have been proven in previous research

29
Q

Methods for Creating Reliable Measures: Reliability of Research Workers

A

Ensuring research workers (interviewers, coders, transcribers, translators, analysts) performing as consistently as possible
trained workers as coding the same way

30
Q

Methods for Creating Reliable Measures: Reliability of Research Workers

A

calling subsample of respondents to verify certain info
have same piece of info independently coded by more than one worker or plenty of training
•Clarity, specificity, training, and practice

31
Q

GUIDES FOR VALID MEASUREMENT: Face Validity

A

Indicator seems sensible measure of the concept

checking if they attend class

32
Q

GUIDES FOR VALID MEASUREMENT: Criterion-related (predictive)Validity

A

Based on an external criterion

employee hiring, sats

33
Q

GUIDES FOR VALID MEASUREMENT: Content Validity

A

How much does measure cover range of meanings in concept?

includes passive receiving on sexual activity

34
Q

GUIDES FOR VALID MEASUREMENT: Construct Validity

A

How does the variable relate theoretically to other variables?
created a measure using marks + associate with hours of study
•measure should relate in some logical fashion to other measures

35
Q

COMPOSITE MEASURES: INDEXES

A

measures based on more than 1 data item

summarizing + rank scores assigned to individual indicators Usually represents a more general dimension

36
Q

INDEXES: Must have face validity

A

item should measure what you intend it to measure

13 HBSC items all appear to offer some indication of the person’s health

37
Q

INDEXES: Unidimensionality

A

Each item only represent 1 dimension of concept

items measuring physical health should not be included with items measuring mental health

38
Q

INDEXES: Decide on Specificity of the Variable

A

only want to measure certain aspect of health, then only use items representing that aspect
If measuring overall health, then include more balanced set of items

39
Q

INDEXES: Look at Amount of Variance each Item Provides

A

If your item has 100% of people answering the same way, the item will have no variance and will not be a useful indicator for your measure

40
Q

COMPOSITE MEASURES: SCALES

A

assigns scores to patterns of responses, some items suggest weak degree of the variable + others reflect stronger degrees of the variable
Takes advantage of diff in intensity among indicators
•more variation

41
Q

Scales and Indexes – Similarities

A

▫Both ordinal measures of variables
▫Both composite measures of variables
•Both rank order units of analysis using specific variables

42
Q

Scales and Indexes – Differences

A

▫Index-accumulating the scores assigned to individual items
•index more cumulative
oSimply accumulating scores assigned to individual indicators

43
Q

Scales and Indexes – Differences

A

▫Scale assigns scores to patterns of responses suggesting diff in intensity among indicators of the variable

44
Q

Conceptualizing/Operationalizing “Good Health”

A
  • Indicators: eats well, smiling, fit
  • Working definition: no physical/mental conditions that proclude enjoyment of life
  • Agreed ideas on what concepts mean come from everyday observation
  • Observations make up conceptions
  • Agreed upon conceptions make up definition
  • Going from mental images (conceptions) to indicators and dimensions
45
Q

Ambiguity of Meaning in a Concept

A
  • drawing on everyday meaning of sexual relationship
  • got off on lewinsky case
  • paula jones – lawyers pins down with declarative (written) definion
  • Clinton’s answers were legally correct
  • Ambuiguity researchers can face with definitions
  • Can sabotage judicial procedures
  • Left a loophole for Clinton
46
Q

Construct

A

theoretical creations based on observations but cannot be observed directly or indirectly
•Concepts are constructs derived by mutual agreement from mental images
•Concept have no real, true, or objective meanings
help us organize, communicate about, and understand things that are real

SOC200 (11 decks)

Brainscape helps you reach your goals faster, through stronger study habits.
© 2024 Bold Learning Solutions. Terms and Conditions