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Part I Setting Up Systematic Mixed Methods Research (SMMR) -- 1 Mixed Methods for Research on Open Systems -- 1.1 The Link Between Quantification and Mixed Methods -- 1.2 A Conceptual Introduction to Methodology and Ontology -- 1.3 Triangulation -- 1.4 Three Domains of Reality, As Realists Approach Research -- 1.5 Conclusion -- Appendix -- References -- 2 Mixed Methods with Weakly Structuralist Regression Models -- 2.1 Modelling and Methodology for Mixed Methods -- 2.2 Strategic Structuralism -- 2.3 Logics Used in Strategic Structuralist Research -- 2.4 Conclusion -- Appendix -- References -- Part II SMMR Approaches in Practical Terms -- 3 Causality in Mixed-Methods Projects That Use Regression -- 3.1 Causality in a Regression Model -- 3.2 Stages of Research Design Amendment for Mixed-Methods Research -- 3.3 Deduction Cannot Stand Alone -- 3.4 A Quantitatively Complex Example -- 3.5 Conclusion -- References -- 4 Multiple Logics in Systematic Mixed-Methods Research -- 4.1 Multiple Logics in Statistical Research: Some Exemplars -- 4.2 An Exemplar Using Participatory Research with Panel Data -- 4.3 A Statistical Exemplar with a Randomised Control Trial for a Social Intervention -- 4.4 Warranted Arguments and Two Caveats for Strategic Structuralism -- 4.5 An Exemplar Using Correspondence Analysis Without Regression -- Appendix -- References -- 5 Factor Analysis in a Mixed-Methods Context -- 5.1 Latent Variables and Entities -- 5.2 One Could Use Exploratory or Confirmatory Factor Analysis -- 5.3 Measurement Issues for the Manifest Variables in a Confirmatory Model -- 5.4 Mixed-Methods Research Designs Using Latent Variables -- 5.5 Whether to Use Scoping Analysis or Primary Field Research -- 5.6 Research Scope and Feedback Loops -- 5.7 Closed and Open Retroduction in a Factor Analysis Context -- 5.8 The Ontological Element -- 5.9 Conclusion -- References -- 6 Qualitative Comparative Analysis (QCA): A Classic Mixed Method Using Theory -- 6.1 QCA Is an Umbrella Over Many Procedures -- 6.2 Tables Help to Summarise Qualitative Comparative Evidence -- 6.3 Data Reduction Has Been Well Theorised -- 6.4 Threshold Tests, Quasi-Sufficiency, and Next Steps in QCA -- 6.5 Conclusion -- Appendix -- References -- 7 Calibration of Fuzzy Sets, Calibration of Measurement: A Realist Synthesis -- 7.1 Two Forms of Calibration: Ordered Categories or Fuzzy Sets -- 7.2 Features of Multiple Hypothesis Tests Using Fuzzy Sets -- 7.3 Asymmetry of the Causal Mechanisms? Issues Around Counterfactuals -- 7.4 How to Make and Illustrate Deep Linkages -- Appendix -- References -- 8 From Content Analysis to Discourse Analysis: Using Systematic Analysis of Meanings and Discourses -- 8.1 Methods of Qualitative Analysis and Elaboration of Findings -- 8.2 Qualitative Methods, with a Content Analysis Example -- 8.3 Three Illustrations Demonstrating Deep Arguments Based on Depth Ontology -- 8.4 Conclusion -- Appendix -- References -- Part III Interpretation and the Validity of Research -- 9 Interpretations, Meanings, and Validity in Mixed-Methods Research -- 9.1 Truth Is Not Simple in a Complex Society -- 9.2 Epistemology for Late-Modern Mixed Methods -- 9.3 Falsifying Hypotheses: Possible and Desirable, but Not Necessary -- 9.4 A Retroductive Approach -- 9.5 Conclusion -- References -- 10 Summary of the Logics and Methods for Systematic Mixed-Methods Research -- 10.1 Induction -- 10.2 Deduction -- 10.3 Retroduction -- 10.4 Synthesis -- 10.5 Recognising Relevant Irreducible Phenomena (Holism) -- 10.6 Logical Linkage -- 10.7 Conclusion -- References -- 11 Glossary.

AbstractDevelopment evaluation refers to evaluating projects and programmes in development contexts. Some evaluations are too narrow. Narrow within-discipline impact evaluations are weaker than multidisciplinary, mixed-methods evaluations. A two-step process leads toward profoundly better arguments in assessing the impact of a development intervention. The first step is setting out the arena for discussion, including what the various entities are in the social, political, cultural and natural environment surrounding the chosen problem. The second step is that, once this arena has been declared, the project and triangulation of data can be brought to bear upon logical arguments with clear, transparent reasoning leading to a set of conclusions. In this second step, we do need scientific methods such as peer review, data and so on, but, crucially, the impact evaluation process must not rest upon a single data type, such as survey data. It is dangerous and undesirable to have the entire validity of the conclusions resting upon randomised control trials, or even a mixture of data types. Different contributions to knowledge exist within the evaluation process, including the interaction of people during action research, ethnography, case-study methods, process tracing and qualitative methods. The cement holding my argument together is that multiple logics are used (retroductive, deductive, and inductive, in particular). Deductive mathematics should not dominate the evaluation of an intervention, as randomised controlled trials on their own lend themselves to worrying fallacies about causality. I show this using Boolean fuzzy set logic. An indicator of high-quality development evaluation is the use of multiple logics in a transparent way.

This paper explores a pluralist approach to moral economy in two ways. First, as a review, four major schools of thought on the rental of land in India are described. I focus on their normative and ontic assumptions. Second, noting that none of these schools is value-neutral, a plurality of six complex moral reasoning strategies emerge from this review. The advantage of the social researcher doing an overview of these normative positions is that we can compare and contrast the meta-criteria that are used. The six moral reasoning strategies are a neoliberal growth strategy, a human capabilities approach, a redistribution approach, a transformative approach, a social equality approach, and a Pareto-optimality approach. The study of these six strategies leads toward the conclusion that more research on complex moral reasoning strategies is called for, because combining them rapidly leads to difficulties. Scientific research can provide evidence to underpin and shape the moral reasoning that takes place in real-world dialogues and debates. © The Author 2009. Published by Oxford University Press on behalf of the Cambridge Political Economy Society. All rights reserved.

AbstractA theoretical orientation toward 'strategies' is proposed in this paper. This theoretical approach suggests that we study both the context for immediate decision-making and the broader context in which reflection and deliberation occur. Whilst these are very broad concerns, the paper itself is based on fieldwork about land rental relationships in rural South India. The paper introduces strategies as a solution to the theorists' dilemma of choice vs. constraints. We treat tenants (as both households and as individual agents) in their structural contexts whilst respecting the complexity and co-mutuality of their agency. The strategies that people use involve an orientation to current and future events, including possible events which are imagined or which could happen. Both structural relationships and concrete past incidents act as reference points for decisions made today in a given relationship. The strategies of tenants include being pliable vis-à-vis landlords but some tenants make this conditional upon landlords' proper behaviour. Agents negotiate and enforce proper behaviour and, thus, both create and change the system of norms that exists. In Macintyre's terms (1985), the virtues intrinsic to the socio-economic practices are continually being re-worked. The theory of strategies reframes 'virtue' in dynamic structure-and-agency terms. Agents are not simply individuals. The debate about rational choice vs. holism can be augmented by looking at agency supra-individualistically. The strategy of a household is an emergent property of the household as an agent. It includes detailed first-order strategies along with more reflective second-order strategies which reconcile goals in the education, migration, household work, and marriage domains. The paper is, thus, interdisciplinary and contributes to sociology, while pluralistically drawing upon other disciplines.

Realism is an approach to humanity which recognizes the real existence of social objects as well as physical objects. Thus realism does involve being realistic. But more importantly, it asserts that the things we are studying in social research have some prior existence and would continue to exist even if our knowledge of them was limited. Indeed, sometimes our knowledge is quite wrong, and realists assert that the real world will tend to constrain science so that wrong claims get challenged