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EPISTEMOLOGICAL FOUNDATIONS OF METHODOLOGICAL PARADIGMS

Wendy Olsen, Reader in Socio-Economic Research, University of Manchester July 2014 Berlin Summer School

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ABSTRACT:

THE AIM OF THE SESSION IS TO PRESENT A REALIST APPROACH THAT CAN BE USED FOR ALL KINDS OF SOCIAL-SCIENCE RESEARCH. THE REALIST APPROACH IS EASILY EVIDENT IN STATISTICAL ANALYSIS (BOORSBOOM, ET AL., 2003; OLSEN, 2007) BUT THE FOCUS TODAY IS TO STRESS THAT IT IS ALSO USEFUL FOR QUALITATIVE METHODS (OLSEN, 2012). AN INTEGRATED MIXED-METHODS APPROACH WOULD ALLOW A WIDE RANGE OF METHODS TO BE JOINED TOGETHER FOR DATA-COLLECTION STAGES OF RESEARCH AND FOR THE ANALYSIS OF DATA (DANERMARK, ET AL., 2002).

My thanks to all who helped me put together Data Collection (London: Sage, 2012), with

most of this material.

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Sections of the Talk

First principles of paradigms in Social Science Research Methods/-ology

1 Realism 2 Retroduction not

deduction please 3 Modes of analysis 4 Ways to Logically Move

Toward Conclusions 5 . Paradigm 3, Strong

Constructivism – worthy? 6. Applied Retroduction in

Qualitative Research

Findings

The realist foundations can be questioned, but they are not meant to oppose constructivist methods of data-analysis;

Instead they offer a challenge to post-structuralist strong constructivism.

There is common ground.

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Exercises That Come Later

1) An analysis of an

interview extract, raising questions about the paradigms and epistemological issues

2) : a set of 3 mini

debates, for 3 groups. I think groups of 6 would do fine, summing up to 18 folks, which is half of the whole group of 48, approx..

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WHAT RELEVANCE CAN REALISM HAVE TO DOING QUALITATIVE RESEARCH?

This is the real issue.

1. Realism: some definitions.1a) A ‘systems’ approach? Defining “Systematic Mixed Methods

Research” requires definitions of open systems and closed systems – useful for many projects: an OPEN SYSTEM has permeability, organic

capacity to change itself, and/or multiple causes

a CLOSED SYSTEM (e.g. a set of equations) has routinised workings, has parameters

The study of systems requires that we realise that social systems are open systems.

This creates a rationale for trans-disciplinarity. It is also sociological. But water and farming are also open systems! (Lemon – book on water systems)

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1b) “Substantivist” Views

Bhaskar argued in 1975 that it is the WORLD we are talking about. It is not the DATA we are talking about.

This is known as ontology – being expert about that which is being referred to.

A substantivist argues that the nature of cause depends on what we are referring to. E.g. events vs. structures; institutional change vs. institutional

reproduction, and so on. Best books by Bhaskar: The Possibility of

Naturalism 1979, 1989, 1998) and A Realist Theory of Science (1975)

The Realist Approach to Evidence Empirical data, observations, records

are at a superficial level.

Actual events and things that existed in the past are or were real – and very numerous! (Quine)

Real structures are not directly or easily observable

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The Realist Approach to Evidence

Empirical data, observations, records are at a superficial level.

Actual events and things that existed in the past are or were real – and very numerous! (Quine)

Real structures are not directly or easily observable

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The data could be wrong.

The data give traces of the real.

SMMR is the study of open systems using a mixture of methods of social research which recognise patterns but also acknowledging the tendency of patterns to change at different rates. The rates of change and the nature of change

depend on what factors are causing change and what can cause new changes.

See Sayer 1992 on durable structures Method in Social Science: A Realist

Approach See Fay 1987 on embodied habits and

rates of change (Critical Social Science)

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2. Retroduction – how to ask ‘why’ See Downward, Mearman, Dow (article

on “Structured Pluralism”) on mixing methods by doing retroduction = asking why.... Ask why the data look the way they do. Ask why the culture accepts as ‘normal’

what is thought to be normal Ask why something has happened which

seems deviant; to some agent, this is ethical or right

action?

This is a small step in building up a pictureThen you build an argument to defend your

conclusions.

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Read about Retroduction, Causal Analysis, Causality, and Causes

Olsen, 2012, Key Concepts in Data Collection.

A whole section on retroduction is found in Danermark, et al., 2009.

Hunt, S. (1994). “A Realist Theory of Empirical Testing: Resolving the Theory-Ladenness/ Objectivity Debate.” The Philosophy of Social Sciences 24:2.

Danermark, B., et al., eds. (2002). Explaining Society: Critical realism in the social sciences. London, New York: Routledge, pages 60, 79, 107-111.

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3. Think about your own empirical methods. What data/ how do you interpret the data? Three main methodologies exist: –

1) Popperian, 2) realist, and 3) strong constructivist.

If you are mixing the three most common methodologies, or cutting across them, then you will need a methodology that is fairly comprehensive, open to new knowledge, and not simply falsificationist. The Popperian falsification framework was questioned by Quine and Kuhn.

Quine: 3 Dogmas of Empiricism, 1951 Kuhn: The Structure of Scientific Revolutions (anomaly, normal

science) You also need to work out whether values inform your work, and if

so, in what ways they are ‘premises’ versus in what way learning about them or exploring them could generate changes in your value stance.

FIRST METHOD – STATISTICAL ANALYSIS – Do not simply follow Popperian critical rationalism. The hypothesis-testing approach is faulty as methodology. See:

‘A Critical Epistemology of Analytical Statistics: Addressing the Sceptical Realist’, Wendy Olsen and Jamie Morgan Journal for the Theory of Social Behaviour, 35(3) (2005): 255–284.

Ways to Logically Move Toward Conclusions

METHODS are tools and techniques, which can be used by any researcher.

MODES OF ANALYSIS are the small-scale bits of logic that we use to move our ‘claims’ forward, e.g. in statistics, the arguments are often: • deductive: adducing from laws or theory

to the specific prediction for a given case, then testing that hypothesis, the drawing the conclusion.

I recommend instead: • retroduction: asking why the data

show their patterns. This is more exploratory. Triangulate to answer it.

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Housewife is as Fulfilling as Working for Pay

2002, 2006 WVS15

01

02

03

04

0

0 1 2 3 0 1 2 3

Bangladesh India

Percentkdensity housfulf

normal housfulf

Pe

rcen

t

housfulf

Graphs by country

World Values Survey

Statisticians make a single factor out of these.

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Four Variables Used in a Factor Analysis for Bangladesh DHS 2007

…to estimate the social norm that women and men can equally participate in the economy. This variable has four components.

Who Has: The final say on own health care The final say on making large household

purchases The final say on making household

purchases for daily needs The final say on visits to family or

relatives If respondent (wife) then the indicator takes the

value 4. If respondent and husband decide together, it takes

value 3. If respondent and another person (which is rare), it

takes value 2. If any other decision maker, e.g. husband alone, it

takes value 1. 4 ordinal variables with 4 options each =

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Components which are binary at origin and/or when recoded here

India Bangladesh

Jobs scarce: Men should have more right to a job than women (disagree = 1, agree or other=0)

Child needs a home with a father and a mother D018 (disagree=1)

Marriage is an out-dated institution D022 (agree or it depends = 1, vs. disagree=0; binary indicator)

1990 46%1995 40%2001 36%2006 20%

1995 15%2001 5%2006 10%

1995 23%2001 18%2006 17%

1996 23%2002 17%

1996 2%2002 1%

1996 12%2002 5%

DIFFERENT PATTERN17

WVS shows no clear overall trend over time.

Three Broad Schools of ThoughtFirst school: problem of universalistic reductive individualism

Second school: a mixed and confusing terrain, allowing for diversity within the societyThird school: is supported by many gender and qualitative specialists

Norms, roles, attitudes, beliefs, desires

-- the realist view is that they are real, and exist, and are malleable 1) vs. idealised

psychometric approaches, e.g. Schwartz, see the World Values Survey – not realist

2) realist approach and the Bourdieuvian ‘fields’ with habitus and doxa (rules) in each field, creating tensions.

3) eclectic approaches

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Three Broad Schools of ThoughtFirst school: problem of universalistic reductive individualism

Second school: a mixed and confusing terrain, allowing for diversity within the societyThird school: is supported by many gender and qualitative specialists

Norms, roles, attitudes, beliefs, desires

-- the realist view is that they are real, and exist, and are malleable

1) vs. idealised psychometric approaches, e.g. Schwartz, see the World Values Survey – not realist

2) realist approach and the Bourdieuvian ‘fields’ with habitus and doxa (rules) in each field, creating tensions.

3) eclectic approaches

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Conclusions So Far

Realism has changed the reasoning behind some statistical methods, clarifying assumptions.

Realism has influenced and strengthened mixed methods. Realists use retroduction therefore they prefer mixed methods data sets (QUAL+QUANT).

Realists deeply criticise Popperian reasoning.

4. Ways to Logically Move Toward Conclusions

METHODS are tools and techniques, which can be used by any researcher.

MODES OF ANALYSIS are the small-scale bits of logic that we use to move our ‘claims’ forward:• induction: from particular to general.• deduction: adducing from laws or theory

to the specific prediction for a given case.• abduction: exploring the thing from the

inside, e.g. policy areas and gender regimes.

• retroduction: asking why things are the way they are. This is more exploratory.

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Think about your own empirical methods. What data/ how do you interpret the data? Three main methodologies exist: –

Popperian, realist, and strong constructivist.

-work out your theoretical and assumptive starting points (premises)

-work out what will be exploratory in your project (open-mindedness, learning)

-work out what hypotheses or claims can be “tested” in your project. - Try using mini-tests rather than having

testing as the ‘paradigm’.

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Three Main Methodologies in Social Science 1 Polar Extreme of Hypothesis Testing

2 A Middle-Way Position- Structures exist and exert powerful influences, but are not

deterministic.- See also Byrne, Blaikie, Layder, and Danermark advanced

texts which support this approach- An interpretivism that is not strongly social-constructivist

can fit in here- Some forms of multilevel modelling can also fit in here

3 Polar Extreme of Multiple Standpoint Post-Structuralism-

- ‘phenomenology’ as it is sometimes called - perhaps post-modernist, but that is something else

5. Paradigm 3, Strong Constructivism:Theories Underlie The Interpretation of Texts

Analyse narratives…. Analyse social constructions…. Deconstruct

[ Deconstruction is a method not a methodology]

Analyse agents’ habituation to socially-normal meanings: HABITUS / DOXA (Bourdieu) and BIOPOWER (Foucault);

Be careful of FUNCTIONALISM (Parsons) – obviously weaknesses;

BEWARE of accidentally falling into the functionalist trap. Avoid saying ‘the discourse of X [muslim Pakistani culture]

causes her to do all the household work’ - this misattributes agency.

‘Phenomenology’ has specific strengths, such as insight: ETHNOMETHODOLOGY

can this be done in a CULTURALLY COMPARATIVE CONTEXT? Difficult.

Institutional Ethnography is often said to be phenomenological. This is best laid upon a weak constructivist methodological foundation not on a strong constructivist ontology. (Chapter in Carroll, C., ed., volume)

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6. Applied Retroduction When Used in Qualitative Methods of Research

Policy analysis

-text analysis – can use NVIVO – textual analysis techniques include:

content analysis

document analysis

discourse analysis

Analysis of the context in which a main outcome has appeared or not appeared

the study of historyProcess tracing

the retroduction of why data are so commonly interpreted as they are

-dominant discourses

-resistant, marginal(ised) and unheard discourses

-dialectical discursive moves

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Interviews – What Scientific Role? Unstructured Interviews? Semi-structured interviews Harmonisation Location, location, location:

sampling and selection of cases Enabling retroduction to occur

. . . Use mixed methods! Investigate! Triangulate!

TENETS OF SCIENCE: transparency, sophistication of analysis, reproducible results given these data (=reliability), internal validity (coherence)

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From Olsen, 2012: Data Collection, page 53, adapted from Danermark, et al., 2001: 160.

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From Olsen, 2012: Data Collection, page 53, adapted from Danermark, et al., 2001: 160.

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Conclusions

I showed unique, new approaches to data in the first 3 sections-• retroduction• mini-hypothesis tests• arguments rooted in premises and reasoning,

which uphold warranted conclusions

I showed epistemological tenets that fit with realism:

Transparency, sophistication of analysis, reproducible results given these data (=reliability), internal validity (coherence)

I suggest also external validity. With triangulation, the assertion of external validity is intrinsically present. Showing your data allows readers to agree with you whether the conclusions are warranted.

Multi-Stakeholder Dialogue Also Useful.

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6. Appendix: Complexity Theory Adds to Knowledge Like This:

If some evidence shows that X Y sometimes appears to be true, then (X Y) can be true for some configurations or situations

(the potential truth of fallibilist knowledge in a realist context pointing to evidence about reality)

If some evidence shows that X Y is not always true, then (X Y) can be true for some configurations or situations but not true for others

Both assert a deeper truth that there is causal complexity of the world but that causality is real.

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Doubting the Conclusion About X Being a Cause Doubt number 1. There is more

complexity in a multi-dimensional world than in a simple X/Y world. Perhaps some other factor Z is missing, and it was Z that made X appear to be sufficient for Y to occur. Therefore it is not X that is necessary for Y, but rather Z that is necessary for Y.

Conclusion: When X appears to be necessary for an outcome Y, watch out for hidden or masked real causes.

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Doubt Number Two: Contingency is Required

2. Even if in all observed or recorded cases, X and Y appear together or are absent together, this does not imply that X necessarily causes Y. Other data would be necessary to establish this as a well-justified argument. Evidence could be of several kinds. See Sayer (1992).

Bhaskar argues that X may simply be a part of Y. This is called ‘natural necessity’ or ontic embeddedness of X in Y. In such cases, X and Y are not contingently related. These are identifiable by the total absence of X~Y and of ~YX. See Bhaskar 1975.~=‘not’