Ethical Justice Chapter Four: Criminology Research - Theory Testing and Publishing

Criminology Research Adherence to ethical guidelines is important in conducting research and scholarly publishing, as the end user relies on the integrity of such products in: Conducting further research, Forming professional opinions, and Testifying under oath in a court of law.

The Scientific Method The scientific method is a way to investigative how or why something works, or how something happened, through the development of hypotheses and subsequent attempts at falsification through testing and other accepted means. Falsification refers to subjecting a theory to repeated attacks in order to disprove it – testing it against the case facts or alternative theories.

The Scientific Method The scientific method is a way of ensuring the results obtained when researching something are both valid and reliable. A test is reliable if it consistently yields the same result within whatever margin or error we are willing to accept. A test is valid when the results are reliable and accurate.

Peer Review Peer review is the process of subjecting an authors work, research, or ideas to the scrutiny of others who are experts in the same field. The concept of peer review is that research submitted for publication should be critiqued and that research not meeting acceptable standards should be kept from publication.

Peer Review Authors of academic works also have additional responsibilities. Below are examples of some relevant issues: Reporting standards Data access and retention Originality and plagiarism Multiple, redundant or concurrent publication Acknowledgement of resources Authorship of the paper

Logical Fallacies Logical fallacies are errors in reasoning that essentially deceive those whom they are intended to convince. Researchers and authors must avoid logical fallacies. The following are examples of logical fallacies: Circular reasoning: Using data to prove something that was used to develop the hypothesis; a proof that essentially restates the question. Overgeneralization: Making generalizations to a broad population based on insufficient data.