Suchergebnisse

In our earlier work on generalizing from qualitative research (GQR) we identified our two-decade struggle to have qualitative research outcomes formally "listened to" by policy personnel and bureaucratic systems in general, with mixed success. The policy sector often seems reluctant to acknowledge that qualitative research findings can be generalized, so impacts tend to be informal or simply ignored. The "official" methodological literature on generalizing from qualitative research is epitomized by Lincoln and Guba's (1985) still oft quoted, "The only generalization is: there is no generalization" (p. 110). We now understand there are many alternative possibilities for generalizing. In this paper we hope to provide a platform for discussion on GQR. We suggest Normative Truth Statements (NTS) as a foundation. NTSs, used in our proposed generalizability cycle, are a potential key to ensuring designated qualitative research methodology provides a capacity for generalization—and therefore be considered as a valid form of evidence in policy decisions. In other words, we need a platform to articulate how to design qualitative research to maximize the type and scope of generalizability outcomes, referred to here as Designed Generalization from Qualitative Research (DGQR). Five steps of DGQR, using progressive NTSs in the generalizability cycle, are proposed as a way forward in understanding how generalizing from qualitative research may be made more transparent, accountable, and useful. The five steps are illustrated by reference to two example studies.

In this paper, the authors debunk a long-held myth that generalisation is primarily the domain of quantitative research. Based on a review of modern and historical approaches to generalisation, they argue that generalisation from qualitative research (GQR) can be achieved, not through a process of self-justification, but through defensible and rigorous research design and methods. The authors go on to consider examples from their own qualitative research work spanning the last 20 years. From these examples they offer mechanisms that qualitative researchers can employ to generalise from their findings. They suggest that generalisation is achieved through a process of generalisation cycles (GCs) which produce normative truth statements (NTSs), which in turn can be contested or confirmed with theory and empirical evidence.

What is social capital? In answering this question, the paper reports on new research which differentiates between social interaction processes and social capital as the product of those processes. Following a review of literature, structured as a social theory against which social capital might be understood, the paper then describes a study of a rural community, and reports on two analyses of data which contribute to answering the question, 'What is the nature of the interactive productivity between the local networks in a community?' The paper concludes that social capital, for which a new definition is forwarded, can only 'exist' if it is somehow able to be produced. This is the chief assumption of the paper. Social capital is defined as an accumulation of the knowledge and identity resources drawn on by communities‐of‐common‐purpose. If social capital originates in micro interactions which are in turn embedded in a meso and macro social order, then these processes and connections should be observable. This paper makes an initial contribution to the establishment of such micro, mesa and macro links.

Evaluations are often focused on assessing merit, value, outcome or some other feature of a programme, project, policy or some other object. Evaluation research is then more concerned with the particular rather than the general – even more so, when qualitative methods are used. But does this mean that evaluations should not be used to generalise? If it is possible to generalise from evaluations, under what circumstances can this be legitimately achieved? The authors of this article have previously argued for generalising from qualitative research (GQR), and in this article, they extrapolate the discussion to the field of evaluation. First, the article begins with a discussion of the definitions of generalisability in research, recapping briefly on our arguments for GQR. Second, the differentiation between research and evaluation is explored with consideration of what literature there is to justify generalisation from qualitative evaluation (GQE). Third, a typology derived from the literature is developed, to sort 54 evaluation projects. Fourth, material from a suite of evaluation projects is drawn from to demonstrate how the typology of generalisation applies in the context of evaluations conducted in several fields of study. Finally, we suggest a model for GQE.

During the last decade significant progress has been made in the field of ship stability.Yet in spite of the progress made, numerous scientific and practical challenges still exist with regard to the accurate prediction of extreme motion and capsize dynamics for intact and damaged vessels, the probabilistic nature of extreme events, criteria that properly reflect the physics and operational safety of an intact or damaged vessel, and ways to provide relevant information on safe ship handling to ship operators. This book provides a comprehensive review of the above issues through the selection of representative papers presented at the unique series of international workshops and conferences on ship stability held between 2000 and 2009. The editorial committee has selected papers for this book from the following events: STAB 2000 Conference (Launceston, Tasmania), 5th Stability Workshop (Trieste, 2001), 6th Stability Workshop (Long Island, 2002), STAB 2003 Conference (Madrid), 7th Stability Workshop (Shanghai, 2004), 8th Stability Workshop (Istanbul, 2005), STAB 2006 Conference (Rio de Janeiro), 9th Stability Workshop (Hamburg, 2007), 10th Stability Workshop (Daejeon, 2008), and STAB 2009 Conference (St. Petersburg). The papers have been clustered around the following themes: Stability Criteria, Stability of the Intact Ship, Parametric Rolling, Broaching, Nonlinear Dynamics, Roll Damping, Probabilistic Assessment of Ship Capsize, Environmental Modelling, Damaged Ship Stability, CFD Applications, Design for Safety, Naval Vessels, and Accident Investigations.

This article argues that not only is theory building from qualitative evaluation possible, but ought to be considered as a desirable product and utilisation of evaluators' work. Based on three case studies, the authors show how theory building can work, and why it can be important and useful. Theory building is seldom considered an impact-producing product from evaluation. Theory in evaluation is typically limited to 'evaluation theory' as a way of explaining why and how different approaches to evaluation work. Theory is also used to inform programme design and 'theory of change'. The literature seldom suggests that evaluations can be used to build theory in social sciences. The argument presented in this article builds on literature of 'theories of evaluation use' to suggest that theorising is a form of knowledge utilisation arising from well-constructed, open-ended evaluation questions, and conceptual use of findings and recommendations.