Basics of Research Methods for Criminal Justice and by Michael G. Maxfield

By Michael G. Maxfield

This short advent to investigate tools combines accessibility and a conversational writing type with Michael G. Maxfield's services in criminology and felony justice. In fewer than four hundred pages, the textual content introduces you to the fundamentals of legal justice examine using actual facts and that includes insurance of such key matters as ethics, causation, validity, box learn, and study layout.

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By focusing specifically on what we will include in our measurement of the concept, as we did here, we also exclude the other possible meanings. Inevitably, then, quantitative measures will be 24 Part One An Introduction to Criminal Justice Inquiry more superficial than qualitative descriptions. This is the trade-off. What a dilemma! Which approach should we choose? Which is better? Which is more appropriate to criminal justice research? The good news is that we don’t have to choose. In fact, by choosing to undertake a qualitative or quantitative study, researchers run the risk of artificially limiting the scope of their inquiry.

Our excitement at the prospect of a new research project may blind us to obstacles that ethical considerations present. Any of us can immediately see that a study that requires juvenile gang members to demonstrate how they steal cars is unethical. You’d speak out immediately if we suggested interviewing people about drug use and then publishing what they said in the local newspaper. But, as ethical as we think we are, we are likely to miss the ethical issues in other situations—not because we’re bad, but because we’re human.

When we say that that person has appeared three times in a local comedy club, we are attempting to quantify our assessment. Most observations are qualitative at the outset, whether it is our experience of someone’s sense of humor, the location of a pointer on a measuring scale, or a check mark entered in a questionnaire. None of these things is inherently numerical. But it is often useful to convert observations to a numerical form. Quantification often makes our observations more explicit, makes it easier to aggregate and summarize data, and opens up the possibility of statistical analyses, ranging from simple descriptions to more complex testing of relationships between variables.

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