This document discusses different types of nonreactive research methods, including unobtrusive measures, content analysis, archival research, and secondary analysis. It provides examples of each method, such as Erving Goffman's content analysis of gender in advertising from the 1970s, which examined portrayals of masculinity and femininity. The document outlines the process of content analysis, including category formation, sampling strategies, coding, and quantitative/qualitative data analysis techniques.

1. Nonreactive Research
Neuman and Robson Ch. 10

2. Reactive vs. nonreactive research
 Reactive: people being studied are aware of
being studied
 Experiments
 Surveys
 Nonreactive: Subjects are unaware they are
being studied
 Unobtrusive measures
 Often use naturalistic settings

3. Varieties of nonreactive observation
 Erosion measures
 – selective wear
 Accretion measures
 – deposits of something left behind.

4. Strengths and Weaknesses
 Strengths and advantages
 No subject “confounds”
 Can assess actual behavior rather than self-report
 Safety
 Reliability
 Inexpensive
 Good for longitudinal data
 Weaknesses and disadvantages
 No control
 Often don’t know anything about the subjects
 Sample may not be representative
 Secondary information may have bias
 Need triangulation – looking at material from several
different perspectives gives a more accurate view of it.

5. Types of nonreactive research
 Some field experiments could be termed
nonreactive
 Naturalistic observation
 Content analysis – quantitative or qualitative
 Archival research
 Written and audio/visual records
 Secondary analysis

6. Content analysis
 A technique used to study written material by
breaking it into meaningful units, using
carefully applied rules.
 Use objective and systematic coding to
produce a quantitative description of the
observed material.
 Can analyze common myths
 Can also be used in a qualitative way
 Employ semiotic techniques

7. Example: Erving Goffman’s Gender
Advertisements (1979, 1988)
Goffman combined content and
semiotic analysis to look at how
gender was (and still is!)
portrayed in advertising. In his
analysis, Goffman examined a
selection of advertising images
and found that that women are
consistently shown in
subordinated positions compared
to men in a variety of social
situations. He also concluded that
advertising both reflects and
helps shape our concept of what
it means to be masculine or
feminine in our culture.

8. Erving Goffman’s Gender
Advertisements
 Goffman asked the question: How is gender
represented in advertising?
 His underlying premise is that ads are taken-
for-granted pictures or displays of codified
(culturally accepted) gender behaviour – the
ads display ritualized behaviours.

9. Goffman (cont.)
 If we explore these codes, we can learn what it is to
be “male” or “female” in our culture.
 Goffman believed that these codes originated in
how families are structured in our society; based on
the dominant – subordinate relationship between
parent and child.
 Essentially, men treat women as they would treat
subordinate males – in turn both are treated as
“children”, which repeats the dominant parent –
subordinate child relationship within the family.

10. Goffman (cont.)
 Note re: Goffman’s research….
 Goffman showed that a fairly simple, but very
cost-effective methodology like content
analysis can illuminate an important theory
about gender and the social world.
 Most theorists (ie. Leiss Kline Jhally, Waters
and Ellis) believe that Goffman’s findings and
the categories that he uses for his study are
equally relevant today.

11. Example 1:
The Family

12. Example 2:
Relative Size

13. 3. Function
Ranking

14. 4. Ritualization
of Subordination

15. Content Analysis
 What can be studied
 Any written material
 Audio/visual information
 Useful for 3 types of research
 Problems involving a large volume of text
 Research from afar or in the past
 Revealing themes difficult to see with casual
observation.

16. Steps in content analysis
 1. Define problem / identify the issue to be
studied
 2. Select the media that will be used
 3. Derive coding categories
 4. Sampling strategy – which sources will you
use?
 5. Train the coders if using
 6. Code material by hand or with software
 7. Analyze the data

17. Human vs. computer coders
 Can often utilize computers
 Internet searches
 Automated text search
 Great for extremely large sets of data
 Personal judgment not part of the process
 Cheaper and faster than humans
 Humans
 Useful for coding complex concepts
 More flexibility
 Costs more time and money

18. Coding in a content analysis
 What gets counted?
 What is important for understanding themes?
 Structured observation – systematic observation
based on careful rules
 Coding systems
 Before you decide specifically on coding categories, you
must specify what you are going to measure
 A set of rules on how to systematically observe and record
content from text or images.
 What is the unit of analysis?
 One word
 One paragraph
 One theme
 One image

19. Characteristics of text content
 1. Frequency
 2. Direction
 3. Intensity
 4. Space
 Other things that could be counted:
 Characters
 Specific individuals
 Can also consider semantics – the meaning of the text
 Requires interpretation
 Must make judgment calls
 Or concepts
 Crime, mental illness
 Themes

20. Manifest and Latent Content
 Manifest
 Overt or visible material – can count
 Latent
 Symbolic content uncovered by semantic analysis – needs
to be coded first (inductive process) and then counted
 Can use both deductive and inductive approaches
to find categories (codes) for content analysis
 Divide sample in sections
 Use grounded theory on a smaller portion to develop
categories
 Use those categories on the rest of the sample.

21. Deductive and Inductive Category
Formation
 Deductive
 Reasoning from the general to the specific
 Forming categories to score based on theoretical
ideas.
 Inductive category formation
 Reason from the specific to the general
 Come up with categories from data
 Can obtain categories by using grounded theory

22. Grounded theory
 Theories are empirically grounded into the data.
 Data collection and analysis are combined.
 Cycle – observe data, modify theory, observe data based on
theory
 3 stages of analysis in grounded theory
 1. Open coding: Find conceptual categories in the data
 2. Axial coding: Look at relationship between the categories
 3. Selective coding: To account for relationships, find core
categories.
 In grounded theory, meaning derived from the data
 For content analysis, grounded theory can help find
the appropriate codes to use.
 Quantitative analysis after that.

23. Sampling Strategy In Content
Analysis
 Which sources will be used?
 Depends on purpose of study, theory, etc.
 Which dates will be used?
 What will be analyzed?
 All of article, every 2 pages, etc.
 Representative sample is important
 Can use various sampling procedures to obtain
 Random sampling
 Stratified sampling
 Purposive sampling – picking a sample for a particular
reason.

24. Data Analysis in Content
Analysis
 Quantitative:
 Largely depends on procedure
 Correlation analysis
 Percentages
 Inferential analysis
 Qualitative
 Use semiotic analysis (developed in humanities)

25. Analysis of Existing Statistics and
Secondary Analysis of Survey Data
 Also nonreactive
 Many sources of statistical data available
 Government statistics (i.e. Stats Canada, Canadian
Census Data)
 International agencies (i.e. World Health
Organization, the UN)
 Also many private sources
 Secondary analysis can be done when obtain “raw
data” and do statistical analysis for your own
research question
 Raw census data available to academic institutions

26. 2006 and 2011 Canadian Census
 2006 Census
 http://www12.statcan.ca/english/census06/release/index.cfm
 Population and dwelling counts
 Age and sex
 Marital status, families and households, housing
 Language, mobility and migration, immigration and citizenship
 Aboriginal peoples
 Labour, place of work and commuting to work, education and
language
 Ethnic origin and visible minorities
 Income and earnings and shelter costs
 2011 Census
 http://www12.statcan.gc.ca/census-recensement/index-eng.cfm