Lecture ‚Social Research Methods‘ - Kulturgeographie

Prof. Dr. Florian Dünckmann - Lecture ‚Social Research Methods‘

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Lecture ‚Social Research Methods‘


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Content

1. Introductory lesson and comparison between qualitative and quantitative methodology

2. Conducting quantitative surveys 1: Structuring a topic / Developing hypothesis 3. Conducting quantitative surveys 2: Questionaire design / Pretest / Sampling

methods / Interview situation 4. Conducting quantitative surveys 3: Sources of error / Working, interpreting and

presenting the data 5. Methodology: Epistemology / Theory of social sciences / Critical Rationalism 6. Methodology: Hermeneutics / Symbolic Interactionism / Constructivist

Paradigm 7. Conducting qualitative research 1: Narrative Interviews / Interviewing experts 8. Conducting qualitative research 2: Focus groups / Participant Observation /

Participatory Research / Grounded Theory 9. Conducting qualitative research 3: Transcription / Approaches to interpretation 10. Mixed methods / Hybrid methods 11. Choosing the right research design / Research ethics


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What is science?


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How does science work? How do we get to scientific results?


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What are the differences between natural and social sciences?


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Theoretical findings

Empirical findings

Quantitative rationale

Qualitative rationale


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Aim of first lesson

• To comprehend the fundamental difference between the quantitative and qualitative research rationale.


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Political and social change in exurban villages

Comparing quantitative and qualitative research


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Exurban villages


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Quantitative Research

• Making statements about the universe of all exurban villages (population)

– Highest possible number of cases – Random sample


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Hypotheses

Statements about correlations / causalities 1. The closer a village lies to the urban agglomeration,

the higher is the potential for conflicts between agriculture and residential use.

2. The more intensive the agriculture in a village is, the higher is the potential for conflicts between agriculture and residential use.


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Definitions

• Village – Municipality < 5.000 Inhabitants • Urban agglomeration– Hamburg, Bremen und

Hanover • Exurban area – Counties adjacent to urban

agglomerations • Proximity– As the crow flies • Intensity of agriculture – Index of land tax and

livestock units/inhabitant • Potential for conflicts between agriculture and

residents – Survey of mayors


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Standardized survey / Questionaire

To what extent do you agree or disagree with the following statement? (please mark with a cross) „Agriculture is a topic that leads to a lot of conflicts inside our commune.“

-Strongly agree -Mildly agree -Neither agree or disagree -Mildly disagree -Strongly disagree

- I don‘t know


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Data

Name Confl Agr Distance Land Tax LSU


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Measure of correlation

• Statistical Measure: Rank correlation (Spearman‘s Rho)

• Between –1 and 1 • -1: direct negative correlation • 1: direct positive correlation • 0: no correlation


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Rating of the potential for conflicts

• Correlation proximity: -0,05 • Correlation index of agricultural intensity:

0,35

• Could this result be accidental? • Significance test • Only possible with a random sample • The correlation is signifikant on a 95% level of

significance.


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Findings

• There is a verifiable connection between the intensity of agriculture and the potential for conflicts in the village.

• There is no detectable influence of the distance to the urban agglomeration on the potential for conflict.


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Qualitative Research

• Making statements about the actor‘s perception and construction of meaning

• Exploring subjective worlds – Interpretation of comments (i.e. also looking for

inconsistencies and contradictions) – Small number of cases – Conscious sampling of cases/persons


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Qualitative Research

• „Topography“ of the research object is only little known – Openly approaching the research object – No formulation of hypotheses in advance – Interpenetration of theoretical and empirical work

as well as selection of new cases


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Conscious sampling of cases

• Village „Kuhdorf“ • Lies 30 km east of Hamburg • Has got 650 inhabitants • Many older farm buildings were bought up

and renovated by incoming housholds from Hamburg

• 16 farms, 8 full-time farmers, 2 organic farms • Proportion of votes for the Green Party is

outstanding (12,3 %) • Large nature reserve


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Interview with mayor

• Extensive conversation • Literal recording • No ready-made questions, it is possible to

react to the respondent • Interview partner has to express his answers • Interview partner can touch on new subjects • Biography and seemingly remote subjects are

important


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Interpretation

• Context of a statement • What is said? What isn‘t said? • Frequency and vehemence of statements • Different levels of meaning • Reasoning styles • Metaphors and images • Inconsistencies, contradictions


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PD Dr. Florian Dünckmann

Context: Nature reserve

„I try to balance conflicts with agriculture alltough I‘m not always sucessful.“


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following

„And then there is the problem of smell. Especially hog feeding.“


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following

„Are you the only one here in the village who is disturbed by this or are there more people ?“

„Yes, but only behind the back. No one has openly adressed it yet.“


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following

„It is not a topic in the local council? “

„A large portion of them are farmers who have stables“


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Position of the farmers, following

„They say: If you move to the countryside then you have to accept it“


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Context: A successful local organic farm

„Now I‘m surely riven (...) Shurely we are fans of that organic farm (...) Well, in the local counsel there are many farmers who say, you and your ecology. We have to secure profit maximation (...) For me as a mayor it‘s a tightrope walk“


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The perspective of the mayor

• There are latent conflicts between agriculture and residents (odor nuissance)

• Farmers try to defend their local hegemony, i.e. they try to equate their interests with the „village‘s interest“.

• Rejection of agriculture is first of all directed towards conventional farmers. The organic farm is viewed positively.


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Questions to the quantitative analysis

• What does is mean when a mayors says that there are no conflicts between ? – There should be no conficts with agriculture

becaus it is a central part of the village. – Personally I think that surely there are conflicts

with agriculture. But as a mayor I can‘t put it that way.

– There are no conflicts with organic farming, but with conventional agriculture.


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Questions to the qualitative analysis

• How can I contextualise the case of Kuhdorf? – How can I justify the choice of Kuhdorf ? – Is Kuhdorf an interesting exception? – Is Kuhdorf an example for a certain type of

village? – Can I find the patterns that I have identified in

Kuhdorf in all the other villages? – When interpreting the protocol, have I stressed

the remarkable statements at the expense of the normal ones ?


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Differences between qualitative and quantitative research

• Question of sample size is not central! • Different direction of inquiry • Different research questions • Different confidence in the researcher‘s

power of judgement • Different conception of measuring and

evaluating • Different meaning of „result“


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Content








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Conducting quantitative surveys

1. The more liberal the law on divorce, the lower is the proportion of married persons in a society.

2. When the proportion of foreign workforce rises, than the income of the domestic people sinks and unemployment rates rise significantly.

3. Persons with a strong environmental consciousness have a higher willingness to save energy than less environmentally conscious persons.

4. Regions with a better supply in day nursery have a higher fertility rate.


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Cause for caution 1: Scientific and practical reason

• We are all experts in our daily lives! • Practical expertise • Judgment s, assumptions, theories about society • Scientific inquiry has to abandon common sense. • Instead: structured and inter-subjective proceeding • Formalizing and theorizing our day-to-day expertise


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Cause for caution 2: Injection of scientific results into society

• The object of social research (society) is also its addressee.

• Scientific results might change the course of social change.

• Scientific concepts and terms are taken up by common language – Globalization – Urbanization – Gentrification


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Cause for caution 3: Ethical problems

• Relevance and choice of research question • Implicit moral judgments • Research funding

– Study sponsored by BMW with the result that a speed-limit on the autobahn significantly reduces the risk of accidents and car emissions (?)

• Personal rights of the test person


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Dimensional analysis / Conceptual analysis

• Either translation of fuzzy concepts of everyday thinking into distinguished dimensions

• Or translation of abstract concepts of theoretical thinking into distinguished dimensions

• Linking idealistic concepts to empirical reality • Decision about the relevance of traits / criteria


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Dimensional analysis

• Brainstorming: What dimensions could be part of a concept? – Individual quality of life – Acceptance of environmental conservation

measures – Environmental consciousness

• Structuring: Identifying high-level and low-level dimensions


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Relevant dimensions? -Sunspots -Situation of the national economy -Infrastructure -Political Situation - Social Recognition


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• „Is there a relationship between the social background of a person and its professional career?“

• Social Background • Professional career

• Nature of relationship?

– Education


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Social Background

• Social status of family • Social network of family • Habitual style of the family • Demographic characteristics • Place of origin • Ethnicity


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• Place of origin:

– National origin – Regional origin – Urban / rural – Neighborhood

• Temporal scope of „origin“ (Parents, birth, childhood, formative

adolescence etc.)


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• Social status of family – Father, parents, wider family? – Wealth – Income – Professional prestige – Education


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• Justified selection: What dimensions are included in the survey and why? – Centrality to the theoretical framework – Relevance – Empirical managerability – Correlation between dimensions


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Conceptual analysis

• Ambiguous conceptual term • Designates different empirical contents in different

contexts • Example: Germany

– comprises an area of 357.121 km2

– won the FIFA world cup in 1974 • Globalization • Capital • Development / Underdevelopment • Brainstorming / structuring / justified selection


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Conceptual analysis

• What is development? (Kenia, Colombia, Norway) • Apart from physical geographical differences

(development is not restricted to the temperate zone)

• Apart from cultural differences (development ≠ westernisation)

• Apart from individual happiness


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Conceptual analysis

• 331 variables of the World Bank – % employed in agriculture – % access to electricity – Mortality Rate – Pupil-teacher-ratio – CO2 emissions per capita – Number of teenage mothers – Cars per 1.000 people – Poverty gap – Researchers in R & D – Military expenditure (% of GDP) – % urban population – GDP / capita


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Indicator

• Indicates (points at) • Concrete dimension that can stand for an abstract concept • Three criteria for quality of indicator:

– objective (measurable independently of person) – reliable (trustworthiness of measurement) – valid (indicator really mirrors abstract concept)

• Development indicators? • Human Development Index:

– Economy: GDP/capita – Health: Life expectancy at birth – Education: literacy rate & years in school


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Summary

• Translation of complex concepts into distinguished dimensions – Fuzzy concepts of the everyday language: dimensional analysis – Abstract concept of academic language: conceptual analysis

• Three steps: – Brainstorming all possible dimensions – Structuring higher- and lower-level dimensions – Justified selection of the analyzed dimensions


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Theories and Hypotheses

• Quantitative research tests theories and hypotheses. • Theory:

– Abstract theories (rational choice, structuralist theories, cultural theories etc.): Provide terms, research objects, perspectives etc.

– Mid-ranged theories: Provide explanatory models for sections of reality

• Coping strategies • Succession of value orientation through generations

(materialist – post-materialist) • Tragedy of the commons


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Theories and Hypothesis

• Hypothesis derived from theory. • Statements about relation between two or more

variables. • „A lot of people are afraid of climate change“ is not a

hypothesis. – „A lot of“ is too vague – No statement about a relation between two or more variables.


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• Deterministic and probabilistic hypotheses – In social sciences normally probabilistic models

• If…then-hypothesis • The (more/less) … the (more/less)-hypothesis • Individual or collective hypothesis

Individual variable 1 (education)

Individual variable 2 (voluntary environmental behaviour)


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Individual variable (voluntary environmental action)

Collective variable (existence of rules that govern collective environmental action)


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Individual variable (individual or household dependence on use of natural resources)

Collective variable (existence of rules to govern collective environmental action)


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• A hypothesis should be mortal. There should be a possibility of not being approved.

• A hypothesis should have informational content. • The informational content of a sentence increases with the

amout of sentences excluded by it. – „Communities in which more than 50% of the households either

rely on hunting, agriculture or fishery as the dominant occupation will exhibit more elaborate environmental institutions than communities with a lower index of direct natural resources dependency“

– „A widespread dependency on the use of natural ressources in a community may lead to an increasingly elaborate system of environmental institutions.“


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Content








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• A hypothesis should be mortal. There should be a possibility of not being approved.

• A hypothesis should have informational content. • The informational content of a sentence increases with the

amount of sentences excluded by it. – „Communities in which more than 50% of the households either

rely on hunting, agriculture or fishery as the dominant occupation will exhibit more elaborate environmental institutions than communities with a lower index of direct natural resources dependency“

– „A widespread dependency on the use of natural ressources in a community may lead to an increasingly elaborate system of environmental institutions.“


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From hypothesis to questionaire

• What/who is the object of inquiry? – Individuals? – Individuals of a certain group? – Households?

• Selection and specification of indicators – E.g. Accessebility: distance as the crow flies /

distance in conducted miles / traveling time and expenditure


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Scales

• Nominal scale: a is different from b – Sex (male / female) – Profession

• Ranking / Ordinal scale: a is higher/smaller than b – Ranking: fully agree/ agree/disagree/fully disagree

• Interval scale: a is the value of c higher/smaller than b – Temperature in °Celsius, Age


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Scales

• Amount of information decreases from interval to ordinal to nominal scale

• Statistical procedures demand interval scales • Ordinal scales can be analyzed with non-parametrical

measures (more rough) • Higher scales can be transformed in lower scales (but

not vice versa) • Always aim for the highest scale possible! • Age: age categories / year of birth / age in years


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Categories

• Categories press a multiformed reality into chunky containers.

• Criteria for the quality of categorization: – Limited number of categories – Distinct: No ambiguity in classification – Exhaustive: Every empirical case belongs to one category

• Logic of categorization: – Equally spaced (every 10 units) – With regard to special content (under 18 years, over 65 years)


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Place of residence

• Adress? • Postal code • Town/city/county • Special categories becoming more general with

increasing distance – Kiel, Kiel region, rest of Schleswig-Holstein, Lower

Saxony/Hamburg/Mecklenburg/Bremen, Rest of Germany, Rest of Europe, other


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Questionaire

1. Forms of surveys 2. Types of questions 3. Constructing a questionaire


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Forms of surveys

• Postal • Online • Telefone • Face-to-face

– With a fixed date – Household survey – Spontaneous


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Types of questions

• Demographic information: Age, sex, income etc. • Attitudes: Acceptance, Agree/disagree, Satisfaction • Questions about actions: How often do you go

shopping? / Where are you coming from today? • Questions about motives:

– Never ask: „Why do you do x?“ – But: „What is important to you when you do x?“


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„The identification of reasons for the shapes of a certain variable must be part of the interpretation of the date and is not a task for the interviewee. “ (Nisbett & Wilson 1977)

• Ad-hoc-Answers

„My questions as a researcher are not the questions I

can ask my interviewees“


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Constructing a questionaire

• Open questions (without categories) – Ex post categorization – Explorative

• Closed questions – Dichotomous categories – Categorical scheme with/without ranking – Possibility to give multiple answers?

• Semi-closed questions – With one open category (else:____________)


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What is wrong with these questions?

• „How would you assess the economic impact of sea level rise in Schleswig-Holstein?“

• „How many journeys did you do last year?“ • „Did you receive subsidies from the EU, the national

government or the commune?“ • „In which way are you helping to save the climate?“ • „What is your monthly income?“ • „If you would have one million Euro available, how much would

you spend on environmental issues?“ • „How would you assess the ecological quality of this part of the

beach?“ – Excellent / good / neither good nor bad / bad / terrible


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• Easy, concrete • Without ambigiuty • One-dimensional • Neutral, not suggestive • Sensible • Not hypothetical • „Don‘t know“ as a category


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• Max. 10 minutes for spontaneous interviews • Introductory commentary: Who are you? What is the

survey for? Anonymity. • Warming-up: First question should be fascinating and

relevant. • Rule of thumb: Central questions in the middle third • Sensible questions (e.g. age, income) at the end


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• Filtering questions • Questions have surrounding fields of framing (mostly

unwanted) • Buffering questions (to reduce the biasing effect) • Control questions (asking the same question

differently in order to check central points)


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Rating technique

• Assessing different statements on a standardized scale

• Rate the following statement on a scale from 1 (totally agree) to 5 (totally disagree)

• „I think that economic interests should have priority when balanced with environmental interests.“


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Pretest

• Testing the questionnaire (10-20 times) • Questions a pretest should address:

– Are the questions understandable? – Are questions interpreted in the wrong way? – Do all the interviewees give the same answer? – Do some questions have a biasing effect on the

following questions? – Are the categories appropriate

• Ideally with two interviewers • No questionnaire is perfect without a pretest!


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Sampling

• Random or non-random • Arbitrary (without rules) • Non-random sampling methods:

– Ideal types – Snowball – Extreme cases – Theoretical sampling (Grounded theory)

„Non-random samples don‘t allow for statistically validated inferences on the population/universe. Predications can only relate to the cases of the direct sample. Otherwise they are generalizations!“


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Central requirement for a random sample

„Every case of the population / universe N must have exactly the same possibility to be integrated in the sample“


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Sampling procedures

• Random numbers • Systematical procedure (every fourth person) • Multi-layered procedure (1. random selection of

specific subgroup, 2. random selection of individuals of that subgroup)

• Stratified sample – Division of the universe N in subgroups – Random sample in every subgroup – E.g. age – No proposition can be made concerning this variable – Variable can be used as an independent variable


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Sample size

• Not dependent on the size of the population / universe N

• The more the better! • Samples with less than 30 are too small. • The smaller the sample the bigger the uncertainty of

the findings. • The bigger the variance the bigger the uncertainty of

the findings.


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Content








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Interview situation

• Artificial situation of communication – Interviewee: Object – Interviewer: Instrument

• No forerun, no follow-up • Extremely one-sided • Standardized • Danger of rejection


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Sources of error

• Sampling error: Bias in the selection of the analysed cases (e.g. sympathy)

• Coverage error: Certain parts of the population are not included in the sampling procedure (e.g. because they are difficult to address)

• Non-response error: Bias due to non-random distribution of rejections


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Important terms

• N: Population / universe • n: sample • Variable • Case • Characteristic value


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• Population: All households in a flood risk area in the city X

• Sample: Specific sample of 200 households • Variable: Main source of household income /

Number of household members • Case: Specific household • Characteristic value: informal street trading / four


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Modes of data analysis

• Descriptive, analytic statistics • Primary / secondary frequency distribution • Absolute, relative, percentage frequency • Building classes • Graphical representation (charts) • Parameters of distribution

– Measurements of centrality – Measurements of variation – Standardization


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“Statistical methods are means to analyze numbers as numbers and not as indicators of a property.” (Diehl & Kohr 1994, p. 25)

Statistics can never replace interpretation of content. It

can only order large sets of data and thereby facilitate interpretation.

Computer-programs might give you the average of male

and female coded as 1 and 2, since they don’t know what 1 and 2 stand for.


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Statistics

• Descriptive statistics: – Displays data – Simplifies complex sets of data – Delivers no analysis – Delivers no inference from sample to the universe / population

• Analytical/deductive statistics – Analyses data – Identifies relations between variables – Infers from sample to the universe using theory of probability


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First steps in describing the data

• Raw data Case Variable X Variable Y

1 5 3

2 6 2

3 9 4

4 1 2

5 7 3

6 6 4

7 3 1


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• Ranking the cases Case X Y

4 1 2

7 3 1

1 5 3

2 6 2

6 6 4

5 7 3

3 9 4



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Erste Schritte der Datenbeschreibung

• Ranking the cases

Case X 4 1 7 3 1 5 2 6 6 6 5 7 3 9


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• Ranking the cases

Case X Position 4 1 1 7 3 2 1 5 3 2 6 4,5 6 6 4,5 5 7 6 3 9 7


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Erste Schritte der Datenbeschreibung

• Frequency distribution

Case X 4 1 7 3 1 5 2 6 6 6 5 7 3 9


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X Absolute frequency 1 1 3 1 5 1 6 2 7 1 9 1


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X Absolute frequency Relative frequency

1 1 1/7 = 0,14 3 1 1/7 = 0,14 5 1 1/7 = 0,14 6 2 2/7 = 0,28 7 1 1/7 = 0,14 9 1 1/7 = 0,14


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X Absolute f. Relative f. Percentage f. 1 1 1/6 = 0,14 14 3 1 1/7 = 0,14 14 5 1 1/7 = 0,14 14 6 2 2/7 = 0,28 28 7 1 1/7 = 0,14 14 9 1 1/7 = 0,14 14


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X Absolute H. Percentage f. Cumulative f. 1 1 14 14 3 1 14 28 5 1 14 42 6 2 28 70 7 1 14 84 9 1 14 98


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Classification

• Breaking down the raw data into classes • Loss of information, gains in clarity • Requirements for classification:

– No overlapping – Covering the whole range of values – Equal class intervals can be useful – Class boundaries on integral numbers (if possible)


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Sturge‘s Rule

• Number of classes : 1 + 3,32 * lg n • 140 cases result in ca. 8 classes • Just a crude rule!


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Diagrams

• Circular chart • Bar chart • Polygon


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Circular chart

135679


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Bar chart

0

0,5

1

1,5

2

2,5

1 3 5 6 7 9


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Säulendiagramm

0

0,5

1

1,5

2

2,5

1 2 3 4 5 6 7 8 9


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Polygon

0

0,5

1

1,5

2

2,5

1 2 3 4 5 6 7 8 9


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Means of transport

1

2

3

4

5


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Figures of distribution

• Centrality – Arithmetric mean – Median – Mode

• Variation – Range – Standard deviation


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Arithmetric mean

• Sum of all values / Number of values • Sensible to extreme values • Integrates all values in calculation • Only possible for metric scales! • Example: Per-capita income?


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Median

• 50% of cases have higher / lower value • Departing from ranked order • Impair number of cases: value of k +1 case • (n = 2 x k + 1) • Pair number of cases: mean over kth and

k+1st value • (n = 2 x k)


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Median

• Not sensible to extreme values • Also possible for ordinal scales (not for nominal

scales) • Has less information content than aritmetric mean


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Mode

• Most frequent value • Also for nominal scales • Contains few information


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Range

• Maximal value minus minimal value • Only possible for metric data • Strongly influenced by extreme values • Few information about distribution of values


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Standard deviation

• Integrates the whole distribution into calculation • Extreme values are weightet higher because all

values are squared • Same measuring unit as variable • The better the aritmetric mean characterizes the

distribution the more meaningful is the standard deviation

• Great significance in statistical procedures


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Z-Transformation

• Deviation of a value from the aritmetric mean measured in standard deviations

• Standardization of the distribution • Mean= 0, standard deviation = 1 • Independent from the measuring unit of the

variable • Enables the comparison of the position of a case in

different distributions of different variables


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Content








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Epistemology

• “There is an apple” implicates a lot of preconditions • Perceptual apparatus • Subject • Concept of space and time • Concept of an apple

• Are Robinson and Freitag both “seeing” a ship at the

horizon?


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Epistemology

• Can I say anything about the apple insofar as it is not perceived be me?

• Anything an apple means to me is based on my perception of the apple!

• The apple “in itself” is a mystery to me! • My perception has a priory settings: Space, time, causality • And categories: quantity, quality, relation, modality • “Thoughts without content are empty, intuitions without

concepts are blind” • Distinction between a priory (necessary) knowledge and a

posteriory (contingent) knowledge


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Deductive and inductive reasoning

• Deductive reasoning: Linking of premises with conclusions

• Going from general statements to specific statements • Inductive reasoning: Linking specific observations to

broader generalizations • Basis: Identification of patterns and regularities • Theory: Approach in explaining the underlying

mechanism that lead to this regularity


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Problems of inductive reasoning

• Probabilistic: Inductive reasoning never provides absolute certainty

• “All swans are white” can never be absolutely verified!

• “All material substances are affected by gravity”. • “Mankind cannot alter the global ecosystem

fundamentally.” • How can inductive statements be scientifically

reliable?


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Critical rationalism

• Karl Popper (1902-1994) • General statements can never be verified. • They can only be falsified (by one black swan). • Scientific must not try to prove theories • But should try to refute them. • As long as a theory is not falsified it can be considered as valid. • Science is NOT about discovering or constructing new theories • Science is about exposing these theories to a substantial and

controlled inspection. • Truth is always provisional and contestable. • Critical rationalism was the dominant paradigm of sciences in

the post-war period.


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Sequence of inquiry

Research question

Theory

Hypothesis

Operationalization

Empirical Survey

Statistical Analysis

Falsification Confirmation


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Problems of critical rationalism in social sciences

• Only applicable to repeatable events. Not to single historical events.

• Problem of falsification by mistake. • Social theories are not falsificable by one single case:

Probabilistic theories • Relation between status as single partent and

poverty is not falsified by one affluent single mom • Work with levels of significance • Critical rationalism is only analyze (and thereby

justify) the status quo.


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Specific challenges of empirical social sciences

• We are all experts of our everyday social lives • Folk and everyday theories about social relations

• Clarified, structured and transparent theories

• Expectations • Pseudo-regularities • Selective perception


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Social Sciences


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Causes and motives

• Human actions have a meaning. • Reversed causality: Motives and agendas (in the

future) are cause • Actions relate to a social and cultural context

(stuctures of meaning) • Only individuals can act, but no act is purely

individual • Routines / Repetitions reduce complexity


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Collective structures or individual agency?


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Different approaches to reasoning in social sciences

Rational choice • Actions as rational results of aims, values, perceived costs and

benefits • Theories of social action Structuralist approaches • Collectives and societies have their own logic of development • Cannot be reduced to sum of individual actions • Marxism or Systems Theory Culturalist Approaches • Neither structures nor actions are independent of each other • Culture shapes actions which in turn produce and reproduce

culture • Culture is contingent


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Content








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Positivism

• Positivism: Depart from and concentrate on the ‘positive’ (manifest) facts.

• Sciences should restrict its statements to what can be objectively said.

• Natural and social sciences follow the same logic. • The researcher should have the minimal influence

possible. • Intersubjective, representative measurement


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Critical points in positivist social sciences

• Social phenomena don’t exist outside of individuals but are based on the individual interpretation of a certain group. Meaning is central!

• Social phenomena cannot be identified objectively, since they always depend on the context.

• Positivism hold the manifest for the real. Latent or virtual patterns are excluded. Thereby they tend to just legitimate the status quo.

• Departing from hypothesis formulated by the researcher only perpetuates his/her perspective. There is no possibility of being confronted with a different view.

• Measurability and not relevance determines what can count as a research topic.


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Development of qualitative research

• Early 20th century: Sociological Schools and Studies – Chicago School of Sociology – Cultural Anthropology (Malinowski) – “Die Arbeitslosen von Marienthal” The unemployed of

Marienthal (Lazarsfeld et al.)

• Mid 20th century: Suppressed by ‘hard’ science

• Since 1970ies: New discussion about methods


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Interpretative Paradigm

• Basic assumption of qualitative research • Every social interaction is an interpretative process • Actors act in reference to one another • On the basis of their interpretation of what the

others do. • Social reality: action, communication, interpretation • Scientific task: Comprehend the interpretations that

guide action


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Qualitative research is: Interpretation of interpretations

or Re-constructions of constructions


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Interpretative Paradigm

• Relevance of ‚reality‘? • Socially relevant is the social construction

of reality! • Qualitative social research

– identifies – interprets – compares

constructions and their becoming conventional.


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Symbolic Interactionalism

• Stresses the significance of the symbolic system • e.g. traffic signs (bus stop) • e.g. language • e.g. place of residence (symbol of social status)


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Three basic assumptions of symbolic interactionalism (H. Blumer)

• "Humans act toward things on the basis of the meanings they ascribe to those things."

• "The meaning of such things is derived from, or arises out of, the social interaction that one has with others and the society."

• "These meanings are handled in, and modified through, an interpretative process used by the person in dealing with the things he/she encounters."


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Symbolic Interactionism

• Symbols and meanings are bound to culture. • Scientific approach:

– Understanding thesubjective theories through which people make sense of their world

– Autobiographical stories by which people make sense of biographical facts (e.g. meaning of migration)

• Scientific re-construction is – construction – Bound to theory – Not ‚objective‘


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Hermeneutics

• Art (science) of understanding / interpreting • Comprehend the motives behind and meaning of

actions and statements • Identify the context of meaning • „Fusing of horizonts“ • Openness toward object of inquiry • No fixed hypothesis • Not subject-object but co-subjects • Danger of misunderstanding and misinterpretation • Hermeneutic circle


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Qualitative research as science?

• Total fusing of horizonts is never possible. • ‚Scientific‘ interpretation is subjective • Criteria: consistency and plausibility of

interpretation • Analysis must be grounded in a theoretical

approach • Theory as a guideline for interpretation


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Characteristics of qualitative research

• Methodological spectrum • Methods relate to the research question • Everyday practice and knowledge • Difference of perspectives • Reflexivity of the researcher • Understanding • Openness • Contextuality


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Content








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Marienthal

• Small industrial town in Austria • Classical social study about the impacts of high unemployment

rates (about 50%) on social life • Marie Jehoda, Paul Lazarsfeld, Hans Zeisel • 6 weeks of field research in 1932 • Special characteristics:

– Attempt to characterize unemployment (individual and collective) as precisely and detailed as possible

– Precise, poetic and naturalistic writing style – Researcher are not mere observers but immerge into the

community – Wide range of different methods


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Methods of the Marienthal-Study

• Non-reactive methods – Statistics – Documents

• Complaints • Account books • Diaries


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Methods of the Marienthal-Study

• Reactive methods – Participant observations

• Family visits • Consultation hours of physicians • Drawing lessons • Gymnastics for girls • Political work • Educational counseling

– Expert interviews (Teacher, mayor, physicians etc.) – School essays – Written surveys

• Inventaries (of meals) • Time sheets

– Biographical interviews


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Aim of qualitative research

• Quantitative research: Testing known, pre-formulated hypothesis and theories

• Qualitative research: – Thick description – Exploring new phenomena – Discovering new insights – Constructing mid-range theories out of empirical

data


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Role of theory and the researcher

• Theory stands at the end. • But:

– Starting point can never be tabula rasa. – Researcher always departs from theoretical

assumptions. – Identification of a topic already means employing

a theory. – Clarify your theoretical assumptions – Clarify your perspectivity


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Interviews

• General openness of conducting the interview. • Encourage the interviewee to interpret and evaluate

the events. • Situate the interview in a intimate setting. • Follow the rules of social interaction (trust,

politeness, sensitivity, mutuality) • Situation of strangeness is not necessarily a

disadvantage (“passing stranger”) • Anonymity? Confidentiality?


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Directives for qualitative interviews

• Plan with enough time! • Don’t dominate the conversation! • Don’t depart from your own standpoint! • Listen patiently! • Lead a conversation and don’t work through your

questions! • Clarify the purpose of your study! • Use your ignorance as a resource!


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Qualitative Interviews

• Different techniques • Differ in openness and participants • Three examples:

– Guided interview – Narrative interview – Expert interview


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Guided interview

• Focuses on a certain topic • Half-structured

– Questions are pre-selected – Order is flexible – No categories – Interview guide based on a theoretical concept


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Elements

• Beginning of the conservation (“Could you tell me how…”)

• General inquiry (“What happened in detail then?”) • Specific inquiry (Summaries, contradictions,

feedbacks) • Ad-hoc questions • Post-script with thhe most important impressions

and information about the context (directly after the interview)


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Other possible elements

• Short questionnaire • Drawings (i.e. mental maps) • Photos, texts, sounds as impulses • Biographical stories • Diaries

• Number? • Bottleneck is the analysis of the protocols


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Narrative interview

• Open and unstructured • Story of own experiences and events • Telling a story means:

– Selecting – Ordering – Making sense of – Contextualizing – Interpreting

• Examples: – Life stories – Migrant stories – Experiences with big events (Fukushima) – “The fight against Möbel Kraft”


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• Structure of a story: – How it began (“once upon a time” or “in the beginning”) – How it went on (selecting and developing relevant elements) – How it ended (meaning of the story)

• Function of the interviewer: Sustaining the structure and recapturing the flow of storytelling by asking questions

• Plausibility and completion of the story is part by the interviewee


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Narrative interview

• Schedule of a narrative interview 1. Expanation phase (What is this conversation about?) 2. Introductory phase (“ Could you tell me about how the

protest against Möbel Kraft started at that time?”). Open ambiguous introductory question.

3. Inquiry phase (“Just just mentioned that … Could you tell me more about it?)

4. Wraping-up (Making sense of the story)


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Narrative interview

• Researcher gains access to stories (creative, meaningful reproductions of events)

• NOT to events itself • Problem: Analysis of a massive body of unstructured

(but often exciting) texts.

• Decision depends of the research question


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Expert interviews

• Very common • Hardly ever thought through critically • Nearly absent in methodological literature • Often combined with other methods • What is an expert?

– Special knowledge – Decision making – Professional distance

• Gap between private person and representative of an organization


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Expert interviews

• Expert interviews address persons as experts • “Mental problems of young adults”: Teacher is addressed as an

expert • “Mental problems of teachers”: Teacher is addressed as a

person involved • Expert interviews aim at reconstructing the expert’s

knowledge: – Explicit knowledge – Tacit, practical, embodied, local knowledge

– Inside knowledge – Context knowledge


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Expert interview

• Ignorance is NOT a resource! • The better the interviewer is qualified the freer and

more informal the conversation • Bounded openness of the conversation • Flexibility in adjusting to the specific language game

(code).


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Expert interview

• Problematic courses of a conversation: – Expert is not qualified for the topic or backs out on a formal terrain. – Expert blows the whistle about internal, personal or confidential

information – Expert constantly changes position between professional and personal

perspective

• Successful interviews are based on a two-sided curiosity with regards to the topic

• Clarify your research in an interesting way • Show qualification inconspiciously • Researcher is seen as a co-expert (can be problematic)


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Focus group interview

• How can a group interview represent individual structures of meaning?

• Classical study about antisemitic ideology in the 50ies – No traces of antisemitism in individual interviews – Escalation of antisemitism in group discussions

• Collective structures of meaning are only detectable in “natural” conversations.

• Opinions are situational and are negotiated by participants. • Groups who know each other well tend to complete each

others statements.


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Focus group interviews

• Natural or artificial groups • Homogeneous or heterogeneous groups • Ideal seize: 5-12 persons • Course of a focus group interview:

1. Explication 2. Introduction of the participants 3. Impulse for the discussion (film, text etc.) 4. Moderation of the discussion 5. Metadiscussion


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Moderation

• Basic impulse should be emotional, polarizing • Formal Moderation (list of speakers, speaking time) • Substantial Moderation • Moderator can keep the discussion going by

– Asking in more detail – Paraphrasing – Questioning – Provoking – Introducing new perspectives


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Monitoring and interpreting

• Tape the discussion! • Ideal: Quite listener to monitor the group situation • Problem: Transcription of several people speaking

simultaneously • Problem: The dynamic of group interviews is always

uncompareable. How can you derive general results from it?

• Two levels of interpretation: – Basic content of what has been said. – Situatedness of statements in the dynamic of discussion


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Focus groups

• Sense and nonsense of focus groups – High input in work and time – No strategy of saving input in comparison to individual interviews – Only appropriate when collective opinions and social dynamics are

object

• Selection strategies of participants: – Complete inventory – Snowball – Gatekeeper – Theoretical sampling – Extreme or ideal types – Pseudo-representative selection


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Observation

• Does reality only consist of language and verbal data? • Embodied meaning • Concrete situations • E. Goffmann: Sociologist (1922-1982) • E. Laurier: Geographer • Exploring the richness and complexity of ordinary

situations • Difficult to represent verbally • Structured observation and interpretation


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Types of observation

• Secret vs. open observation • Participant vs. non-participant observation • Systematic vs. unsystematic observation • Natural vs. artificial situations • Self-observation?


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Observation

• Object: Events and actions • Researcher reduces the complexity of situations with

three filters – Selectivity of intention – Selectivity of perception – Selectivity of protocol

• Observation is not a merely receptive capturing of facts but an active re-construction by the researcher.

• The aim is not just the description of situations but the re-construction of meaning.


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Objects of observation

• Actors: shadowing persons through different settings • Events and Actions: whole social context with

different roles and practices (restaurant, meeting). Difference between routine and unexpected events.

• Artefacts: Analysing actions that are related to a certain material objects (blood preservation, class room).


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Problems of observation

• Defining and delimiting a whole cycle of action • Access to all relevant situations • Familiarity of “normal” situations • Significance of marginal details • Complexity of situations


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Participant observation

• Attempting to get the “inside” perspective • “Doing pidgeon” • Reenacting embodied, situated meanings • Difficulty of distinguishing between scientific outsider

perspective and participative insider perspective • Constant balance act between two modes of

perception • “Going native” • Constant self-reflection of the researcher! • Always keep a research diary!


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Phases of participant observation

• Descriptive analysis: – Crucial phase when everything is still new and noteworthy to the

researcher. – Unfulfilled expectations bear great potential for new insights – Focus on the social and the physical setting

• Focused analysis: – Reconstruction of structures of meaning – Variation of perspective – Construct “normality” – Identify dimensions of meaning (social, factual, temporal, spatial)

• Detailed analysis: – Concentrate on particular topics – Detailing, modificating


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Participatory Research

• Blurring the strict separation between science and practice • Science as a democratic, communicative process • Researcher as engaged part of the process • Participatory Action Research (PAR):

– Aims at change of practices or structures – Working with competent and reflexive participants – Adresses real-life issues – Involvement of participants in knowledge generating

• Paulo Freire: Pedagogic of the opressed • Research as a possibility for conscientização • Make poor marginalized people aware of the forces

affecting their lifes


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Public Sociology

Construction of topic

Scientific Community Non-academic

Problem solving Traditional social research Applied social research

Challenging Critical social research Public Social Research

Audience


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Methods in participatory research

• Art and media • Diagramming and drawing • Group work and discussions • Political action and advocacy • Mapping (paper and using GIS) • Ranking and scoring • Role plays and theater • Secondary data analysis • Shared analysis, writing, and presentations • Storytelling • Transect walks


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Grounded Theory

• Developed by Glaser & Strauss 1967 • Strategy of developing mid-range theory • Grounded in empirical data • Deduction – induction – abduction • Abdutive reasoning: Infering a hypothesis from given data. • Data: “The lawn is wet.” • Sufficient and most economic explanation: “It rained last night.” • Iterative process of gathering data – interpreting data –

selecting cases


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Theoretical sampling

1. Starting with one case study 2. Analysing and interpreting the data 3. Developing a theoretical explanation 4. Selecting the next case based on your theoretical

assumption 5. Expand, modify or re-think original theory 6. Selecting each new case on the basis of each

modified theoretical structure 7. Go on until theory is saturated


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Rules of grounded theory

• Memoring: Writing down memos about theory • Memos accumulate in the process of doing research • Sorting of memos • During sorting process new ideas are memored too

• Theoretical split of Glaser & Strauss:

– Glaser: “Let the data speak” – Strauss: “Everything is construction”


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Transcription

• Most common qualitative data: tapes and audio files • Transcripts of audio files are re-constructions

(selection of “relevant” levels of meaning) • Transcribing is very laborious and time consuming. • 1 hour interview takes about one working day to

transcribe and makes about 30 pages! • Facilitating software in speech recognition.


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Accuracy of transcription

• As original as possible? – Dialect? – Injections? – Pauses – Accentuations – Laughs – With parts that don’t relate to the topic?

• Two dangers: – Loss of important information by sloppy transcription – Fetishism of accuracy

• Level of accuracy should be determined by the research question.


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Strategies of analysis

• Coding • Standardisation • Interpretation


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Coding

• Aim: – Breaking up texts – Developing and assigning categories – Ordering

• Reducing and generalizing • Coding strategies

– Open coding – Theoretical coding


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Open coding

• Move on by line, sentence or paragraph • Summarize into generalizations

– What is being said? – Who acts? – How are the facts adressed? – Context – What motives move the statement? – What strategies are employed?

• Step by step generalizations of generalizations • Does a pattern emerge? • Advantage: flexible responding to the text


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Theoretical coding

• Close commitment to a given topic • Three steps

1. Single case analysis with a characteristic statements and summary

2. Detailed content analysis 3. Comparison over given cases


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Software

• To structure and organize the text • No interpretation or analysis of the text! • Coding of text passages • Retrieval-Function: Listing of passages with

the same code • Retracting the context of each passage • Searching for certain words


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PD Dr. Florian Dünckmann Prof. Dr. Florian Dünckmann

http://www.uni-kiel.de/�


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Constructing idealtypes

• Idealtypes are the most important non-quantitative instrument in social sciences

• Max Weber: Idealtype (doesn‘t have to exist in reality)

• Aim of qualitative inquiry: Identification of empirically grounded idealypes

• Internal homogeneity, externeal hetergeneity


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Constructing types

• Single case: coding of single case • Types: Total number of cases are

aggregated into distinct types • Typology: Differences and similiances of the

types are identified


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Interpretation

• Interpretation is ALWAYS taking place • Conscious act! • Putting oneself into the other position,

understanding • Text, speaker, spoken • What is said / What is meant / What is understood • Ways of understanding: Information about facts,

Relation, Confessing, Appeal


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Objective Hermeneutics

• Hermeneutic circle • Interpretation – better understanding of

the text – new Interpretation • Aim: Revealing the latent (objektive)

structure of meaning of the text • Step by step analysis of small text snibblets

– 1 page of protokoll – 5 Interpreters – Each 30 hours of interpretation work – Ca. 50 pages interpretation text


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Approaches to interpretation

• From the content of the text • From the biography of the autor • From the objective circumstances of its production • From the reader • From motives and decisions


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Topic based content analysis

• Coding different topics • Identifying the similarities that mark all text passages

concerning the topic. • Identifying the different contexts (social,

chronological etc.) in which this topic is addressed. • Identifying the different ways how the topic is

treated in one or more interviews • Integration of the results into research question


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Mixing Methods

• Bridges over the qualitative – quantitative divide? • Calls for easy integration are naïve. • Triangulation: Applying qualitative and quantitative methods on

the “same” question • Possible?

– Different epistemology, – different model of doing science, – different ways of constructing a topic/research question – different angle of enquiry


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Integration of qualitative and quantitative methods

• During the course of research • Different functions in the research design

1. Qualitative exploration (interviews) and quantitative analysis (questionaire)

2. Quantitative exploration / construction of idealtypes (statistical analysis) and qualitative analysis


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Exurban villages

• What political and social processes shape the development of exurban villages near urban agglomerations?

• Tree step inquiry: 1. Identifying types of villages using factor

analysis and cluster analysis of statistical data

2. Quantitative questionaire with mayors 3. Qualitative interviews in selected villages of

each type


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Hybrid methods

• Post-positivist quantitative methods • Quantification of qualitative elements (discourse

analysis with lexicometric methods) • Q-Method


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Q-method

• Method to make subjectivity tangible • Tension between the individual and the collective • Based on complex statistical methods • Interpretative approach • Invented in the 50ies by physicist and psychologist W.

Stephenson • Q-method as opposed to R-method (Correlation)


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Q-method

• Basis: Ranking of stimuli (controversial statements, fotos etc.) by persons

• Statistical analysis resembles normal factor analysis • Not correlating tests over individuals • But correlating individuals over tests • Factors are re-constructions of commonly shared

views • Individuals load (correlate) to a different degree • Aim: identifying and understanding internal,

subjective structure of complex frames of reference


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Q-method

• Not counting isolated opinions but taking the entire setting of a persons standpoint into account

• Persons are not homogeneous entities but are shaped by different discourses and identities

• Variety and inconsistency in a subjective view that lie beyond simple dichotomies and group attributes

• Subjectivity is not indefinitely diverse but that there exist certain common patterns that are socially shared

• Less interested in the people doing the constructing than in their actual constructions


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Topography of a topic Example „Rural development“

X X X X X X X X X X

X X X X X X X X X X

X X X X X X X X X X

X X X X X X X X X X

X X X X X X X X X X

X X X X X X X X X X

X X X X X X X X X X

X X X X X X X X X X

X X X X X X X X X X

X X X X X X X X X X

“People in the village have not enough understanding for agriculture.”

“We should create as much jobs as possible in our village”

“How I live is not any villagers business”


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Ranking


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Pattern of evaluation

+ + + + + + + + + +

+ + + + + + + + + + + + + + + + + + + +

+ + + + + + + + + +

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 - - - - - - - - - -

- - - - - - - - - -

- - - - - - - - - -

- - - - - - - - - -


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Patern I and II

+ + + + + + + + + +

+ + + + + + + + + +

+ + + + + + + + + +

+ + + + + + + + + +

0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0

- - - - - - - - - -

- - - - - - - - - -

- - - - - - - - - -

- - - - - - - - - -

+ + + + + + 0 0 - -

+ + + + + + 0 0 - -

+ + + + + + 0 0 - -

+ + + + + + 0 0 - - + + + + + + 0 0 - - + + + + + + 0 0 - - 0 0 0 0 0 0 0 0 - - 0 0 0 0 0 0 0 0 - - - - - - - - - - - -

- - - - - - - - - -

Re-constructions of constructions


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4) Result: Three perspectives on rurality in Panten


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A) The reform perspective

B) The idyllic perspective

C) The anti-museal perspective

4) Result: Three perspectives on rurality in Panten


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A) The reform perspective Differentiating statements

A B C Farmers promote the establishment of new building sites because they hope to make a lot of money by selling their land. 3 -2 -4

Farmers still have too much influence in our village. 1 -1 -4 We must conserve and cultivate the traditions of our village. -1 3 2

We tend to overestimate the advantages of ecological farming. -4 -2 3


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A) The reform view

Citations from interviews

Hegemony of the farmers: „The communal counsel is clearly dominated by farmers. They sit there already in second generation. “ Sceptical when it comes to traditions: „You can conserve traditions. But sometimes times are changing. It would be terrible if we would conserve everything there ever was.“ Progress: „We definitely have an anti-progress alliance in our village“


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A) The reform perspecitve

Pattern

Breaking up old structures

Ecological modernisation

Hegemony of the traditional farmers

Sceptical against growth

Sceptical with traditions


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B) The idyllic perspective Pattern

Children Healthy life

Roots

Tradition Community Continuity


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Colonization

Production Economy Practical

constraints

False idyll

Artificial museum

C) The anti-museal perspective Pattern


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Political model of village life: Gesellschaft

A-political model of village life: Gemeinschaft

Multifunctionalist model of agriculture

Reform perspective Idyllic perspective

Productivist model of agriculture

Anti-museal perspective


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Loading of persons on different factors

Profession Years in the village

Reform Idyll Anti -museal

Driving instructor 20 years 0,02 0,80 - 0,17

Housewife Local -0,15 0,74 0,13

Retired engineer 20 years 0,14 0,73 -0,15

Government employee 12 years -0,39 0,71 -0,03

Retired midwife 30 years 0,27 0,66 0,09

Housewife 10 years -0,22 0,6 0,12

Architect 12 years 0,63 0,55 -0,16

Physicist 20 years 0,64 0,37 0,25

Farmer (Eco) Local 0,68 0,3 -0,32

Farmer Local 0,05 0,19 0,91


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Last words

• Because Q-methodology aims at the plurality of perspectives on a certain topic, it is an appropriate method to explore the different concepts of environment that co-exist.

• One important advantage of the Q-methodology is its approach to take the constructions of reality themselves as the central objects of analysis and not the individuals who hold them. Thus it is possible to bypass the risk of readily falling back on the distinctions between pre-existent groups (e.g. newcomers vs. natives or farmers vs. residents) or socio-demographic factors and ascribing certain positions to them.

• Even though they appear to be ‘objective’ results of an automated statistical operation, the final factors identified by Q methodology should nonetheless always be seen as scientific constructions.


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Choosing a method


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Choice of a method

• What data sources and methods are potentially available or appropriate?

• What can these methods and sources tell me? • Which components of “social reality” can these data

sources and methods help me to address?

• Co-construction of research topic and methodology


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Informal dynamics of urban developments in the Pearl River Delta/China: Perception of stress factors and coping stratgies under the influence of global change in the megacity of Guangzhou

• - qualitative interviews with inhabitants - autophotography - No standardized survey with questionaires


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- Urban governance in european metropolitan areas: Actors constellations in integrated development programs and the role of trust for the realization of projects

- qualitative interviews with actors


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- Social spaces and migration: Transnational migration. Ecuadorians between home, Germany and Spain (Transnational ties and networks)

- qualitative interviews with selected migrants and with migrant organizations - Biographical method - Participant observation in Ecuador


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- Sociodemographic change and new housing markets: An

analysis of the inhabitant structure and the motives of locational decisions in innercity housing areas in Hanover

- Standardized survey of all housholds - Qualitative Interview with inhabitants - Expert interviews


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- Traditional use strategies of marine resources in Central America: Culutral Change and use conflicts

- Qualitative interviews - Focus groups - Participant observation


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• Militarized landscapes – landscapes of memory: Practices of rememberance of the cold war

• Structured interviews • Focus groups • Participant observation • Public methodology