ARM - workgroups Flashcards

1
Q

Gap-spotting

A

finding a gap in the literature and based on that, formulating specific research questions.

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2
Q

Problematization

A

endeavor to know how and to what extent it might be possible to think differently, instead of what is already known.  assumption-challenging approaches (aims to question the assumptions underlying existing theory in some significant ways)  formulate more informed and novel research questions based on that.

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3
Q

3 types of problematization:

A
  1. incomplete
  2. inadequacy
  3. incommensurate
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4
Q
  1. Incomplete
A

claiming that existing literature was incomplete in some way or another, and that the researcher’s own study would be able to advance it.

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5
Q
  1. Inadequacy
A

claiming that prior literature has overlooked an important perspective which would have had the potential to further our understanding of the subject matter

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6
Q
  1. Incommensurate
A

argueing that existing literature misguided the way knowledge was produced about the subject matter in question

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7
Q

three forms of gap-spotting

A
  1. confusion spotting
  2. neglect spotting
  3. application spotting
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8
Q

confusion spotting

A

finding confusion in existing literature –> competing explanations

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9
Q

neglect spotting

A

spotting something neglected in existing literature –> not enough research done, overlooked (pregnancy research on fetus ipv mother), unsubstantiated = lack of empirical evidence

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10
Q

application spotting

A

spotting a new application in existing literature; The research task is to provide an alternative perspective to further our understanding of the particular subject matter in question –> extend/supplement in a specific area of research

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11
Q

What are the various techniques that Mays and Pope (2000) describe to improve the validity of a qualitative study?

A
  1. Triangulation
  2. Respondent validation/member check
  3. Clear exposition of methods of data collection and analysis
  4. Reflexivity
  5. Attention to negative cases
  6. Fair dealing
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12
Q

Triangulation

A

comparing results from either two or more different methods of data collection. Ensuring comprehensiveness and encouraging a more reflexive analysis of the data (see below) than as a pure test of validity

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13
Q

Respondent validation/member check

A

the investigator’s account is compared with those of the research subjects to establish the level of correspondence between the two sets. Study participants’ reactions to the analyses are then incorporated into the study findings

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14
Q

Clear exposition of methods of data collection and analysis

A

provide a clear account of how early, simpler systems of classification evolved into more sophisticated coding structures and thence into clearly defined concepts and explanations for the data collected. Necessary because methods unavoidably influence the objects.

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15
Q

Reflexivity

A

sensitivity to the ways in which the researcher and the research process have shaped the collected data, including the role of prior assumptions and experience, which can influence even the most avowedly inductive inquiries. Personal and intellectual biases need to be made plain at the outset of any research reports to enhance the credibility of the findings. The effects of personal characteristics, such as age, sex also need to be discussed.

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16
Q

Attention to negative cases

A

to search for, and discuss, elements in the data that contradict, or seem to contradict, the emerging explanation of the phenomena under study. Such “deviant case analysis” helps refine the analysis until it can explain all or the vast majority of the cases under scrutiny.

17
Q

Fair dealing

A

to ensure that the research design explicitly incorporates a wide range of different perspectives so that the viewpoint of one group is never presented as if it represents the sole truth about any situation.

18
Q

What are the various ways in which the relevance of a qualitative study could be improved according to Mays and Pope (2000)?

A

Relevant = when it either adds to knowledge or increases the confidence with which existing knowledge is regarded. Another important dimension of relevance is the extent to which findings can be generalised beyond the setting in which they were generated.

  • to ensure that the research report is sufficiently detailed for the reader to be able to judge whether or not the findings apply in similar settings
  • to use probability sampling (to ensure that the range of settings chosen is representative of a wider population, for example by using a stratified sample)
  • theoretical sampling ensures that an initial sample is drawn to include as many as possible of the factors that might affect variability of behaviour, and then this is extended, as required, in the light of early findings and emergent theory. The full sample, therefore, attempts to include the full range of settings relevant to the conceptualisation of the subject