Principles for Social Science Research

Social Science Principles

Social science principles are a set of guidelines for gathering and interpreting research data. These guidelines allow reports to be intelligible and reasonable for discussion and debate by researchers, critics, and other people.

They also ensure that similar datasets can be compared and that findings are valid. This is an essential part of any scientific endeavour.

Principle 1: Cause and Effect

A cause and effect relationship occurs when one thing makes another happen. For example, if you spend a week lounging around munching on junk food all day, the effect will be that you’ll probably gain a couple pounds.

Social science research can be complex, with a number of potential causes and effects. It is therefore important to establish causal relationships using a variety of methods, including questionaires, field-based data collection, archival database information and laboratory-based data analysis.

Moreover, social scientists should be encouraged to share their research as widely as possible, to foster the widest academic scrutiny and to encourage diverse scholarly voices. This is a fundamental aspect of the open science movement, which needs to be extended to all social sciences disciplines. In particular, the pooling and sifting of datasets across teams of researchers should be promoted, as should greater triangulation of research methods.

Principle 2: Causal Inference

Social scientists make causal claims all the time – such as that education improves income, that intelligence is influenced by genes, that race and income inequality are caused by racism, that traumatic events worsen mental health. However, determining causal effects with observational data is challenging. Various methods have been developed to address this challenge.

However, these techniques are not without risk. In particular, they can be susceptible to unobserved pretreatment factors that affect the outcome additively. They can also be subject to a lack of consistency between counterfactuals and the underlying model.

Moreover, they can lead to false positives when estimating the effect of a treatment. These risks must be taken into account when designing a study. However, despite these limitations, it is possible to generate valid causal inferences using a variety of designs.

Principle 3: Replication

Replication is the process of trying to duplicate a previous experiment to determine whether or not the original results are valid. Recently, there has been a lot of attention given to replication in psychology due to the fact that a large number of research findings fail to replicate.

There are many reasons for this problem, such as low statistical power and “researcher degrees of freedom” (where researchers purposefully try to get results with p 0.05). Also, small sample sizes can lead to false positives. For example, if you interview five people about their belief in alien abduction, it is quite likely that three of the participants will agree with each other.

All social scientists should be familiar with this issue and learn to take a skeptical view of any flashy findings until they have been replicated. This will help to strengthen the discipline.

Principle 4: Data Analysis

In social science, interpreting research results can be challenging. How a researcher decides to investigate a question and what assumptions are made can influence the results and conclusions of the study.

This is a problem because it can lead to bias in the data analysis. It is important that researchers check their assumptions carefully.

Open science principles can help to promote this type of scrutiny. The principles encourage new research to take into account existing literature and methods. This can improve the quality of scholarly work and enable greater diversity in disciplinary perspectives.

Principle 5: Critical Thinking

In social science, critical thinking involves reasoning through a problem in order to make a judgement. It is also about evaluating the evidence and assumptions involved in making the judgment. Critical thinking skills are important in work situations because they allow you to analyze a situation objectively and come up with realistic conclusions. Many educational jurisdictions include critical thinking in their curriculum guidelines.

Generally, teachers consider the five design principles to be practical for teaching value-loaded critical thinking in a transfer-oriented and dialogic way. However, they were less positive about the third design principle regarding moral values or making the dialogue value-loaded. This was mainly because it required a change in their approach to teaching and was a new concept for them. Nevertheless, the teachers did appreciate that it was a necessary change in education.

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