Plagiarism

There are two kinds of dishonesty in research:

     1. falsification of data
     2. plagiarism

1. Falsification of data is the deliberate manipulation, adjustment, and misrepresentation of data to
prove your hypotheses and arguments ("draw your curves, then plot your data").

2. Two kinds of plagiarism:

     a. intentional
     b. unintentional

     2a. Intentional: to borrow data, arguments, quotes from someone else's work or study without
crediting them; representing these data or ideas as your own. You do not need to credit what is
accepted knowledge (eg., names, dates, anything about which there is no disagreement...column 1
of the RPBL model); but you must footnote unique data, arguments, or opinions.

     2b. Unintentional: borrowing someone else's argument or framework and using it as your
own. This is plagiarism even if you use your own words for that argument or framework. It is not
dishonest to reinterpret the work of another researcher, to add data and dimensions to work already
achieved, or to rework data analysis to come to new conclusions. But you must represent that this
is what you are doing, and identify what part of this work is original with you and what part was the
work of another.

     As a general rule, cite everything you look at more than casually in your bibliography so that
unconscious adaptations are accounted for there at least.

     Penalties in higher education for falsification and/or plagiarism are serious, including job
loss, fines for infringement of copyright, and dismissal from academic programs. This is the single
worst offense in the academic world, and reactions to it are usually swift and angry.