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MIXING QUALITATIVE AND QUANTITATIVE METHODS IN PURSUIT OF RICHER ANSWERS TO REAL-WORLD QUESTIONS

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CONCEPUTALIZING QUALITATIVE, QUANTITATIVE AND MIXED METHODS Qualitative and quantitative research methods both involve an array of data types and techniques of analysis. Qualitative methods are associated with case studies, which may be historically and geographically bound events, organizational units or individuals, among others. Data regarding these cases may be drawn from participant or non-participant observations, from semi-structured interviews, focus groups or from narrative analysis of text. Quantitative data collection and analysis comprises observational data, indexing human behavior or non-human factors, survey data reflecting human perceptions, and experiments, with the latter involving a variety of laboratory, survey-based, field-based and natural designs. - 4 - Still, the above assortment of research techniques does not tell us how qualitative and quantitative methods fundamentally differ. An illuminating distinction, suggested by Gerring (2017), rests on the comparability of data observations. Qualitative observations are heterogenous or non-standardized, and therefore non-comparable. In quantitative data, conversely, heterogeneity is reduced, by construction, to facilitate comparability. Thus, while the differences and similarity between qualitative unit of analyses – countries, organizations, individuals, historical events – can be analyzed, the observations themselves are nonstandardized, since they are embedded in context, and their comparison therefore calls for interpretation. Moreover, whereas qualitative data can be converted, through standardization and reduction, into quantitative data, the opposite cannot be done. What this means, for this paper, is that qualitative data, by definition and construction, provides a richer, yet not easily comparable, depiction of cases in context. The above conceptualization, and the aim of this paper, leads me to adopt a conceptualization of mixed methods as a “type of research in which a researcher or a team of researchers combines elements of qualitative and quantitative research approaches” (Johnson et al. 2007). The mixing of methods can take place at the stage of data collection or data analysis (Small, 2011), although what I have in mind, in this article, are projects in which mixing occurs at both stages, resulting in a combination of methods within the same research program or even the same paper. Drawing on the above distinctions, the following section offers that current public administration scholarship has reached an unhealthy balance that needs to be recalibrated towards more qualitative research, and that mixed methods is the means to do so without losing the advantages afforded by quantitative research. - 5 - SIDELINING ARTIFICIAL DIVISIONS IN PUBLIC ADMINISTRATION A widespread understanding of our community is that public administration is an applied field that should be driven by our shared commitment to the pursuit of policy-relevant research questions, important due to their practical consequences over and above their theoretical significance (Riccuci, 2008, 2010). Reflecting this concern with real-world concerns, and their embeddedness in unstable political environments, Riccuci (2010) writes: “[P]ublic administration is an applied field … concerned with applying scientific knowledge to solve practical problems in highly politicized environments. The real world of government and nonprofits is our laboratory; we do not bring subjects and specimens into the lab as the physical sciences do. Most of our research is conducted in the “field”, and it is aimed at improving government or, more specifically, arriving at a better understanding of it so we can seek to improve governing operations in this country and beyond. But because politics drives performance in public agencies, our understanding of government and how it operates in practice are in a constant state of flux …the task of public administration will always revolve around practical applications of solving problems in the real world, which is highly political, fragmented, and transitory” (ibid, 25). A logical implication of the normative commitment to study real-world problems, and of the unruly nature of the phenomena that we study, is that our research needs to account for the variation in political, cultural and institutional factors, within which actual policy tak

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MIXING QUALITATIVE AND QUANTITATIVE METHODS IN PURSUIT OF

RICHER ANSWERS TO REAL-WORLD QUESTIONS

Sharon Gilad






ABSTRACT

Qualitative methods are relatively scarce in public administration research. This imbalance

between qualitative and quantitative methods poses three significant concerns. First, there is a

risk that measurement hurdles, coupled with the distance that quantitative methodology fosters

between academics and administrative practice and practitioners, undermines our inclination and

capacity to study policy-meaningful research questions that matter in the real world. Second, and

related, the causality underlying the real problems that policymakers and public organizations

face is often much too complex to be captured by one type of methodology, whether quantitative

or qualitative. Third, quantitative methodology is most conducive to testing already available

theories and hypotheses, as opposed to theory building. I propose that the answer to these

concerns lays in denouncing commitment to abstract philosophical divisions and advancing

collaboration between qualitative and quantitative researchers and versions of mixed methods

that transcend mere triangulation. These arguments are illustrated in relation to the study of

bureaucratic discrimination of minorities.




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,INTRODUCTION

Social-science methodology textbooks, and research-methods courses, commonly mirror the

taken-for-granted division between qualitative and quantitative research. This division is said to

embody not only different technical tools for data collection and analysis, but incommensurable,

that is logically incompatible, philosophical traditions, pertaining to divergent beliefs about

ontology and epistemology. Crudely stated, these textbook distinctions associate quantitative

research with a positivist paradigm that conceives of reality as consisting of generalizable

patterns of cause and effect, which can be objectively known through deductive hypotheses

generation and their empirical verification. A related philosophical approach, post-positivism,

which is amenable to both qualitative and quantitative methods, is associated with a commitment

to objectivity, alongside recognition of the difficulties to fully access and explain the objective

reality, and thereby with a preference for hypotheses falsification over verification. Still,

qualitative research is most often associated with a constructivist paradigm, which stresses the

multiplicity in social constructions of reality, and the limitations and subjectivity of coming to

know them. Constructivists aim to inductively unpack participants’ actions based on their

situated, shared, interpretations of their social environment, which the researcher investigates and

construes, employing her distinct, non-replicable, vantage point.1

Reiterating and espousing the rationale of the above institutionalized distinctions, a recent

systematic review of the state of qualitative methodology in public administration (PA),

published in Public Administration Review, cautions qualitative researchers to pay closer and

careful attention to where they stand on the postpositivist-interpretivist divide (Ospina et al.,



1
See Riccuci (2008, 2010) for a nuanced depiction of alternative paradigms and their implications for the study
public administration.

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,2018: 2). The authors go on to criticize qualitative researchers, in public administration, for their

failure to explicitly self-define their orientation and commitment to the interpretivist versus post-

positivist traditions (ibid, 6). Their analysis of 129 qualitative papers, published between 2010

and 2014, in six key public administration journals, indicated that most authors did not signal

their fundamental ontological and epistemological convictions, and that only 24% adopted what

the authors coded as an interpretivist approach. The authors acknowledge both issues with

lament, offering that this omission may be a function of ignorance or carelessness among the

community of qualitative public administration researchers.

The above paper, by Ospina et al’s (2018) provides us with important systematic

mapping of the state of qualitative methodology in our field, as elaborated below. However,

some of their guidance regarding future research requires further consideration. Contrary to the

above criticism and lament, I offer that in today’s public administration research, which is

dominated by quantitative studies, it would be artificial and unwarranted for qualitative

researchers to avow decisive allegiance to abstract notions of ontology and epistemology and to

distinct methodological camps. Instead, drawing on Morgan (2007), I propose that the choice of

research methods, in PA, should be led by the epistemological challenges that are posed by

concrete policy-relevant research questions, as opposed to general philosophical assumptions

about the nature of reality and how to know it. This approach, which questions the very

usefulness of the linkage between methodological choices and overarching philosophical

paradigms, differs from that of Yang et al. (2008) who offer that research methods, in public

administration, may draw upon alternative paradigms, so long as researchers appreciate the

distinct ontological and epistemological underpinnings of different methods.




-2-

, I further contend that the problem to be addressed, in current PA, is not qualitative

researchers’ failure to signals their ontological and epistemological convictions, but the near

exclusivity of quantitative research in our leading journals. This scarcity of qualitative research

likely undermines our collective endeavor to address real-world problems that governments face

(Milward et al, 2016; Moynihan, 2017; 2018; Roberts, 2018), and may lead to our provision of

overly reductionist explanations for what are often complex, wicked, problems. Moreover, it

hinders theoretical innovation in our field, leading us to focus on more of the same, relying on

existing indices and datasets. Drawing on the developments in adjacent fields and promising

changes in ours (Hendren et al. 2018; Honig, 2018; Mele and Belardinelli, 2018) this paper

offers versions of mixed-methods that transcend mere triangulation as having the greatest

potential to ameliorate these concerns. I start, however, with some building blocks,

conceptualizing what I mean by qualitative, quantitative and mixed methods.




CONCEPUTALIZING QUALITATIVE, QUANTITATIVE AND MIXED METHODS

Qualitative and quantitative research methods both involve an array of data types and techniques

of analysis. Qualitative methods are associated with case studies, which may be historically and

geographically bound events, organizational units or individuals, among others. Data regarding

these cases may be drawn from participant or non-participant observations, from semi-structured

interviews, focus groups or from narrative analysis of text. Quantitative data collection and

analysis comprises observational data, indexing human behavior or non-human factors, survey

data reflecting human perceptions, and experiments, with the latter involving a variety of

laboratory, survey-based, field-based and natural designs.




-3-

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