Reasearch Design Methods Before examining types of research designs it is important to be clear about the role and purpose of research design. We need to understand what research design is and what it is not. We need to know where design fits into the whole research process from framing a question to finally analysing and reporting data.
Description and explanation
Social researchers ask two fundamental types of research questions:
1 What is going on (descriptive research)?
2 Why is it going on (explanatory research)?
Descriptive research
Although some people dismiss descriptive research as `mere description', good description is fundamental to the research enterprise and it has added immeasurably to our knowledge of the shape and nature of our society. Descriptive research encompasses much government sponsored research including the population census, the collection of a wide range of social indicators and economic information such as household expenditure patterns, time use studies, employment and crime statistics and the like.
Descriptions can be concrete or abstract. A relatively concrete description might describe the ethnic mix of a community, the changing age profile of a population or the gender mix of a workplace. Alternatively the description might ask more abstract questions such as `Is the level of social inequality increasing or declining?',`How secular is society?' or `How much poverty is there in this community?'
Accurate descriptions of the level of unemployment or poverty have historically played a key role in social policy reforms(Marsh, 1982). By demonstrating the existence of social problems, competent description can challenge accepted assumptions about the way things are and can provoke action.
Good description provokes the `why' questions of explanatory research. If we detect greater social polarization over the last 20 years (i.e. the rich are getting richer and the poor are getting poorer) we are forced to ask `Why is this happening?' But before asking `why?' we must be sure about the fact and dimensions of the phenomenon of increasing polarization. It is all very well to develop elaborate theories as to why society might be more polarized now than in the recent past, but if the basic premise is wrong (i.e. society is not becoming more polarized) then attempts to explain a non-existent phenomenon are silly.
Of course description can degenerate to mindless fact gathering or what C.W. Mills (1959) called `abstracted empiricism'. There are plenty of examples of unfocused surveys and case studies that report trivial information and fail to provoke any `why' questions or provide any basis for generalization. However, this is a function of inconsequential descriptions rather than an indictment of descriptive research itself.
Explanatory research
Explanatory research focuses on why questions. For example, it is one thing to describe the crime rate in a country, to examine trends over time or to compare the rates in different countries. It is quite a different thing to develop explanations about why the crime rate is as high as it is, why some types of crime are increasing or why the rate is higher in some countries than in others.
The way in which researchers develop research designs is fundamentally affected by whether the research question is descriptive or explanatory. It affects what information is collected. For example, if we want to explain why some people are more likely to be apprehended and convicted of crimes we need to have hunches about why this is so. We may have many possibly incompatible hunches and will need to collect information that enables us to see which hunches work best empirically
Answering the `why' questions involves developing causal explanations. Causal explanations argue that phenomenon Y (e.g.income level) is affected by factor X (e.g. gender). Some causal explanations will be simple while others will be more complex. For example, we might argue that there is a direct effect of gender on income (i.e. simple gender discrimination)(loot at picture below). We might argue for a causal chain, such as that gender affects choice of field of training which in turn affects
occupational options, which are linked to opportunities for promotion, which in turn affect income level (look at picure 1.1b below). Or we could posit a more complex model involving a number of interrelated causal chains (look at picture 1.1c below).
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