Lecture outline Differences between qualitative and quantitative methods: a review Breaking down the quantitative/qualitative divide Mixed methods: rationales and practices Mixed methods: research examples (Peter Ratcliffe) Concluding thoughts
Differences between qualitative and quantitative research strategies QuantitativeQualitative Principal orientation to the role of theory in relation to research Deductive; testing of theory Inductive; generation of theory Epistemological orientation Natural science model; in particular positivism Interpretivism Ontological orientation ObjectivismConstructionism Bryman, 2008, Social Research Methods, p. 22
Differences between qualitative and quantitative research methods Quantitative methods are generally seen as ideally suited to: Questions to which responses are potentially measurable, i.e. quantifiable e.g. How often do you make use of service x? Questions where only absolute guarantees of anonymity would persuade respondents to answer honestly e.g. questions about income, illegal/deviant activities, voting intentions, etc. When you want to be able to say something about the whole population (generalisability, statistical inference, etc.) Qualitative methods are seen as preferable when: You are interpreting views, opinions, ideas Context is important Research is with vulnerable or hard to reach groups Research is into complex or dynamic social processes
Breaking down the quantitative/qualitative divide It is important not to exaggerate differences between quantitative and qualitative research. Qualitative research sometimes exhibits features that are normally associated with positivism: e.g. Adler and Adler 1987: qualitative study that explored whether participation in athletics in higher education in the USA is associated with higher or lower levels of academic achievement (i.e. tested hypothesis; objectivist overtones) Quantitative research sometimes engages with an interpretivist stance: e.g. Westergaard et al 1989: quantitative study that explored how people who were made redundant responded to their experience in terms of their job-search methods, their inclination to find jobs, and their political attitudes (i.e. interpretivist overtones)
Mixing our methods and epistemology Mixed methods (or multi-method): generally refers to research strategies that mix qualitative and quantitative methods (although some may use the term more loosely to refer to other mixtures of methods). Epistemological and methodological debates are routinely set up around the discussion of supposedly mutually exclusive (quantitative and qualitative) approaches. The argument against mixed methods tends to be based on one or both of two kinds of argument: the idea that research methods carry epistemological commitments, and the idea that quantitative and qualitative research are separate paradigms (i.e. incommensurable, or incompatible, in epistemological terms).
Arguments for mixed methods The connections between epistemology and ontology and research methods are not deterministic. Research methods as techniques of data collection or analysis can be viewed from a pragmatic epistemological point of view, concerned with what is useful for research purposes rather than the nature of reality. Strong objections to quantitative research amongst feminist researchers (e.g. the silencing of womens voices, controlling variables as a masculine approach) have softened in recent years (e.g. recognizing that quantitative methods can be useful for highlighting statistics of gender discrimination ). BUT: mixed-method research is not intrinsically superior to mono-method research: like any other method it must be appropriate to the research questions, context and design.
Mixed methods: approaches Different methods can be used to good effect either in parallel or sequentially and either discretely or in an integrated fashion. Triangulation (also known as convergent findings) use quantitative and qualitative methods to address the same research question, to ensure greater certainty of results Additional coverage Assigns different methods to different components of a project on the basis of their particular strengths/relevance Example: parallel use of methods for discrete purposes Complementary assistance Link methods together so that one method helps the other Example: sequential use of methods for pilot studies
Triangulation of data Triangulation is a process of checking the inferences drawn from one set of data sources by collecting data from others. Within an ethnographic approach you might want to check your own observations of a situation/event against how it is described to you in an interview. Alternatively you might use a diary entry or a set of family photos to confirm or contest something said in conversation. This process of triangulation in ethnographic work is a way of improving validity [countering the view that the researcher gets a very partial understanding of the social world]. But this comes about because it allows you to first capture differences and contradictions and work through them to try and understand the whole.
Additional coverage with parallel use of methods Triangulation is an example of the parallel use of methods as a check on inference from those data. However, methods can be used discretely in parallel in order to provide a different kind of data, answering a different question, but helpful to the overall research It is common for qualitative researchers to employ a small- scale survey, for example, in order to generate descriptive [though not inferential] statistics. The dangers in this kind of parallel work is that the data from different sources may simply present different types of information that cannot be easily integrated and thus produce no discernable analytic gain.
Complementary assistance with mixed methods applied sequentially An alternative approach is to use different methods sequentially. The most common example of this is the recognition by survey researchers that the formulation of questions for questionnaires is benefited by using qualitative research methods either interview or focus groups to understand how respondents are likely to interpret, and respond to, questions. The aim of such mixing of methods is to reduce misreporting and cross-cultural confusion and thus the qualitative element is designed to improve the main technique which is quantitative. Although less common, qualitative specialists may also use quantitative work to identify interesting cases for study, or else to test statistically hypotheses generated by ethnographic work. Finally, remember the potential gains from pursuing the secondary analysis of existing survey, and official statistical, data
Research Examples Selected to illustrate: Theoretical/methodological issues whats the problem? Epistemological issues. Relationship between different components horses for courses Role of sociologist (ethical/political concerns, potential of public sociology)
CASE 1: Race and Housing in Bradford (1996) Background (severe housing need, esp. in certain areas/communities, fiscal constraint, investment required making case to govt.) Principal method major survey (Why? Why not ethnographic?) Ethical considerations (Pathologisation v. potential gain, role of sociologist) Sampling issues (use of NAMPECHAN)
Key concept housing need Major issue: housing need is multi-dimensional (N.B. process: theory/concepts/indicators) current needs (quality, space, social/physical environment....) special needs (cultural, health/disability....) future needs (spatial and social mobility, fertility/fecundity, household transformation processes, net in-migration.......) Different dimensions require different methods
Mixed methods Current/special needs survey and observational data complemented by official statistics (Census, LA databases, morbidity/mortality data, unemployment levels, deprivation indices..) Future needs more complexwhy? BHF as focus group social change processes Key informant interviews semi-structured Demographic data in-migration, spatial mobility
CASE 2: Black Barrister Study (1993) Very different research model highlights the role of sociologist. Background (Judicial Review High Court, backed by Society of Black Lawyers) Substantive issues institutional discrimination on basis of ethnicity, gender (+ class?) Sociologist as expert advisor/advocate Used all available data to make the strongest case (various documents records/reports/ quantitative data, qualitative interviews)
Mixed methods: complementarity Qualitative interviews with complainants subjective assessment of discriminatory processes Statistical analysis of marks (ethnicity/gender) Investigation of assessment procedures discourse analysis of documents - subjective judgements (reports), single marking, minutes of Exam Boards Report interrogated by Lincolns Inn QCs.. (multidisciplinary - socio-legal - research) Outcomes (role of public sociologist ramifications for CLE + led to a public inquiry chaired by the black QC, Dame Jocelyn Barrow)
CASE 3: Community Cohesion research (2006) Background urban unrest in nor