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ESRC Research Methods Festival:

Why Integrate Methods?

Tony Macmillan CoxonHonorary Professorial Research Fellow

SSPS, University of Edinburgh

When, why & how (and if!) to integrate qualitative and quantitative research methods

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The qualitative vs quantitative distinction …

is … in my opinion

• internally incoherent • covers several levels of

discourse• is used differently within and

across levels.

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The Q&Q distinction can refer to different …

• Methodological approaches – Variable-centred versus Meaning-centred

• Epistemological approaches – Empiricism vs Interpretativism

• Data conceptualisation – Representational measurements vs speech as

data

• Data collection– systematic questionnaire-format vs discursive

data-elicitation

• Data analysis– GLM vs semantic and content analytic.

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But the Q&Q distinction can also refer to:• Affiliative Identification / Ecumenism

• “Integrated” Q&Q is viewed as traitorous by the ‘true believers’ (CAIDAS rather than CAQDAS?)

• Software hegemony• Packages pre-empt integration by assumptions about

appropriate data and and range of analysis offered– “Law of the Instrument”

• New paradigm needed? • to supplant the qualitative and quantitative distinction

• Artificial Intelligence? which successfully integrates Q&Q – (as do other "cognitive" disciplines)

• in search for adequate representation of more subtle and complex data-structures which today's developments demand

– Belief-systems, semantic networks, fuzzy-logic categorization ...

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Practicalities of integration …

• Practical issues: not separating – software and data storage

• i.e. integrated Q&Q data base AND data structure

– nor data collection from analysis• Software that assumes integrated data

• TWO EXAMPLES in paper… one here– POOC: Project on Occupational Cognition

• Data inherently Q&Q, but primarily quantitative– SIGMA: Sexual diaries

• Data inherently Q&Q, but primarily textual, but structured

• How represent and analyze?

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POOC …Hierarchical Method (Similarity task)

• Standard instructions given to {R} by {I} on how to construct a bottom-up hierarchy– And encouraged to verbalise– Tape-recorder switched on– “Data collection” proceeds

• Account is transcribed and calibrated by tape-position

– In the Interviewer’s Report

– In machine readable file (initially as comment) at appropriate “action” position (Basic File)

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POOC …Hierarchical Method (Similarity task)

• Data file checked – and extracts UMI matrix for “quantitative” (scaling)

analysis

• Textual analysis of Basic file using GI3, – by level of hierarchy (cf class terminology)– By referent subset of covered occupations (for

descriptors / categories

• RETRIEVAL IN CONTEXT!– For analysis there needs to be

» A file whose data structure contains BOTH types of information

– Software which allows “retrieval in context”: both» Text with pointers to quantitative “task”» Quantitative data with pointers to text

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… [Final Join at Level 15 of the two main branches. What follows is the transcribed tape-recording relevant to this point]______________________________________{Respondent}... I think that I would put the Psychiatric Nurse[MPN] and the Ambulance Driver [AD]in this category as well, um, I realise there's a contradiction here - I've got people with professional qualifications and perhaps academic skills, um, and an ambulance driver, but the reason I mentioned {i} Policeman [P] vis a vis the Commercial Traveller [CT] and Barman [BM]; it seems to me these people have responsibilities in relation to the community which they're working in, that perhaps the Commercial Traveller and Barman doesn't have. {Interviewer}

OK, we're there. 

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POOC …Hierarchical Method (Similarity task)

• INTEGRATED RETRIEVAL: “qualitative retrieval in

quantitative context” : Research problem : • Themes established as most prevalent in the

occupational narratives generated in doing the Hierarchies task

– Money, Training, Caring and Responsibility

• (1) Are they generalising or particularising themes ?– need to know not only how often a Theme occurs in

these data AND

– where in the hierarchical structures they occur, and

– relate their occurrence to the overall consensus hierarchy (see paper)

• (2) Class terminology: where does it occur in structure, & at what levels of generalising?

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Some final thoughts on Q&Q divide …

• hegemony of software producers – will ensure a “safe” Q&Q divide continues to

exist

• Data archives– often perpetuate the Q&Q divide by narrowing

“acceptable data”

• Students (& surely not staff!)– prefer to keep Q&Q divide because of:

• Threat of the other side & its competencies• No ready-made paradigm/ research practice is

established.

• Do we/they really want integration?