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These codes are Code of Ethics and Professional Conduct and the Software Engineering Code of Ethics and Professional Practice, respectively, and some of their guidelines are presented below: From the Code of Ethics and Professional Conduct (ACM): [3] Contribute to society and human well-being.
This index of ethics articles puts articles relevant to well-known ethical (right and wrong, good and bad) debates and decisions in one place - including practical problems long known in philosophy, and the more abstract subjects in law, politics, and some professions and sciences.
A code of practice is adopted by a profession (or by a governmental or non-governmental organization) to regulate that profession. A code of practice may be styled as a code of professional responsibility, which will discuss difficult issues and difficult decisions that will often need to be made, and then provide a clear account of what behavior is considered "ethical" or "correct" or "right ...
Retrieved from "https://en.wikipedia.org/w/index.php?title=List_of_ethics_topics&oldid=553439727"
Medical ethics is an applied branch of ethics which analyzes the practice of clinical medicine and related scientific research. [20] Medical ethics is based on a set of values that professionals can refer to in the case of any confusion or conflict. These values include the respect for autonomy, non-maleficence, beneficence, and justice. [21]
It is the violation of scientific integrity: violation of the scientific method and of research ethics in science, including in the design, conduct, and reporting of research. A Lancet review on Handling of Scientific Misconduct in Scandinavian countries provides the following sample definitions, [ 1 ] reproduced in The COPE report 1999: [ 2 ]
In all versions of Python, boolean operators treat zero values or empty values such as "", 0, None, 0.0, [], and {} as false, while in general treating non-empty, non-zero values as true. The boolean values True and False were added to the language in Python 2.2.1 as constants (subclassed from 1 and 0 ) and were changed to be full blown ...
In statistical hypothesis testing, a type I error, or a false positive, is the rejection of the null hypothesis when it is actually true. A type II error, or a false negative, is the failure to reject a null hypothesis that is actually false. [1] Type I error: an innocent person may be convicted. Type II error: a guilty person may be not convicted.