Sociology: Science or Interpretation

Most sociologists probably find themselves some where between these two positions:

• Sociology as science: Sociological research is a systematic method of direct observation of the world, similar to the natural sciences, which produces objective knowledge of social phenomena and, in some cases, general social laws. Associated with variable research.
• Interpretive sociology: Sociological research examines the meanings that actors attach to social phenomena. Meanings are subjective and not governed by universal laws; hence, sociology differs from natural science. Associated with qualitative research.

3 An area of inquiry is a scientific discipline if its investigators use the scientific method, which is a systematic approach to researching questions and problems through objective and accurate observation, collection and analysis of data, direct experimentation, and replication (repeating) of these procedures. Scientists affirm the importance of gathering information carefully, remaining unbiased when evaluating information, observing phenomena, conducting experiments, and accurately recording procedures and results. They are also skeptical about their results, so they repeat their work and have their findings confirmed by other scientists.

Is sociological research scientific? Yes! By definition, sociological research is the scientific means of acquiring information about various aspects of society and social behavior. Sociologists use the scientific method. Like other scientists, they stress the accurate and unbiased collection and analysis of social data, use systematic observation, conduct experiments, and exhibit skepticism.

5. The four components of research described above are integrated into the following steps of the research process.

1. Define the topic/problem: Identify your topic of interest and develop a research question in the form of a cause-and-effect relationship.
2. Conduct a review of the literature: Access studies that have already been performed by other researchers and published in peer-reviewed journals. You'll find out what is already known about the topic and where more research is needed.
3. Formulate a hypothesis: Refine your research question in a way that will add new information to the existing research literature, expressing it in the form of a testable research hypothesis. This includes identifying two or more variables and articulating how one variable is thought to influence the other.
4. Design the research: Decide on a way to approach data collection that will provide a meaningful test of the research hypothesis. Some designs include data collection at only one point in time, but more complex questions require data gathering over time and with different groups of people.
5. Select a research method: Once a design has been established, one or more actual data gathering strategies will need to be identified. Each method comes with its own strengths and weaknesses, so sociologists are increasingly incorporating mixed-methods approaches in their research designs to enrich their knowledge of the topic. Some of the more popular research methods used by sociologists are: Surveys or Interviews, Experiments, Unobtrusive measures, and Participant Observation or Field Research
6. Operationalize variables: Operationalizing means deciding exactly how each variable of interest will be measured. In survey research, this means deciding on the exact wording of the question or questions used to measure each variable, a listing of all possible responses to closed-ended questions, and a decision as to how to compute variables using multiple indicators.
7. Identify the population and draw a sample: A population is the group a researcher is interested in learning about. Is it all students at one particular University? All residents of the United States? All nonprofit organizations in a particular city? Because it is frequently too expensive to try to collect data from all units in a population, a sample of those units is often selected. Samples that use principles of random selection, where every unit in the population has an equal chance of being included in the sample, have the best chance of reflecting the views and behaviors of the entire population of focus.
8. Collect the data: Data collection must be systematic and rigorous so that procedural mistakes do not create artificial results.
9. Analyze the results: Powerful statistical packages today make data analysis easier than it has ever been. Still, great care needs to be taken to accurately code the data (i.e. transpose responses into numbers), enter it into the computer, and to choose the appropriate statistics to be calculated for analysis.
10. Reporting the Results: Research results are shared with the larger community through presentations, reports, and publications in peer-reviewed journals. This allows others to consider the findings, the methods used, and any limitations of the study.

Every piece of research requires a sample, and there are many ways of finding a suitable sample. Before choosing a method the researcher must find a ‘sampling frame’, this is the collection of people the researcher will then choose their sample from. An example of this could be school or college.

Random sampling –In random sampling everyone in the population has the same chance of getting chosen. This is easy because it is quick and can even be performed by a computer. However, because it is down to chance you could end up with a unrepresentative sample, perhaps with one demographic being missed out.

Systematic sampling –an example of a systematic sample would be picking every 10^th person on a list or register. This carries the same risk of being unrepresentative as random sampling as, for example, every 10^th person could be a girl.

Stratified sampling –this method attempts to make the sample as representative as possible, avoiding the problems that could be caused by using a completely random sample. To do this the sample frame will be divided into a number of smaller groups, such as social class, age, gender, ethnicity etc. Individuals are then drawn at random from these groups.

Quota sampling –In this method researchers will be told to ensure the sample fits with certain quotas, for example they might be told to find 90 participants, with 30 of them being unemployed. The researcher might then find these 30 by going to a job centre. The problem of representativeness is again a problem with the quota sampling method.

Cluster sampling –This is taking a random sample at various stages of the sampling process. For example you might take a random county, take random schools from this county and take random pupils from this school to find your sample.

Snowball sampling –With this method, researchers might find a few participants, and then ask them to find participants themselves and so on. This is useful when a sample is difficult to obtain. For example Laurie Taylor used this method when investigating criminals. It would be difficult for him to find a sample as he didn’t know many criminals; however these criminals know a lot of people who would be willing to participate, so it is more efficient to use the snowball method.

Date: 2016-03-03; view: 2649