5 Reasons Why Plagiarism Detection Goes Wrong
It’s the nightmare of every student and every writer. You submit a project that you’ve worked hard on, and your instructor or your editor comes back to say that they suspect that your work has been plagiarized.
You’re left wondering what happened. Though you didn’t intentionally plagiarize, you’re now facing potential consequences, which, for a student, can include a failing grade, suspension or, in extreme cases, expulsion.
Sometimes, the issue is a fundamental misunderstanding about how one should write an original piece. As we’ve seen time and again, authors often attempt to “write” new works by editing existing ones. Writing in a cleanroom is the only approach authors should take if they want to avoid plagiarism in their work.
However, sometimes, the instructor or the editor gets it wrong. They see plagiarism where no plagiarism exists. There are a myriad of reasons that this can happen, but they all lead to stress and headache for the author. In some cases, they can even lead to unfair punishments.
Some of those reasons were highlighted in a recent Reddit thread in the r/facepalm subreddit.
There, user Fanhanzy posted an anonymous person’s story about being accused of plagiarizing their own work. This brought out others who told their stories of being falsely accused of plagiarism in school. It’s clear that, for the accused, these moments still sting when they look back on them.
As such, it’s important to understand some of the most common errors made when using plagiarism detection software and how they can be prevented moving forward.
Mistake 1: Blindly Trusting the Software
Plagiarism detection software can be an amazing tool. Such tools can be invaluable in finding duplicate text across a wide variety of sources, far outstripping what any human could do on their own.
However, they’re not magical tools that determine whether or not a work is plagiarized. They need a human to evaluate the findings and make that determination independently.
Despite that, it’s very common to see statements such as “Anything below X% is fine” or “Anything above X% is plagiarized.” Those statements are simply untrue.
Plagiarism detection software finds matching text. Not plagiarism. A human still needs to determine if the text is cited correctly, is common language that doesn’t indicate a problem, or is otherwise not an indication of plagiarism.
Blindly trusting the software is a sure-fire path to both miss plagiarism that did happen and to making false accusations. They are tools to aid in the analysis, they do not perform the analysis themselves.
Mistake 2: Not Checking the Sources
If you’re checking an older work, it’s important to look at the sources carefully. Some of them may actually be newer than the work you’re looking at, meaning that the “source” is actually plagiarizing or referencing the work you’re looking at.
This is why plagiarism analyses should be done before a work is published. However, that’s not always practical and, when it isn’t, it’s important to examine any overlaps carefully to ensure that they are actually evidence of plagiarism.
However, this is not always possible and, in cases where others may have copied from the work you’re checking, it’s important to closely examine the source matches so that you can determine which came first and who copied whom.
In short, failure to examine the sources can result in (easily disproven) false allegations.
Mistake 3: Not Eliminating Innocent Overlaps
Depending on the software used and how it is configured, it may highlight duplicate text that isn’t an issue at all.
For example, some tools highlight words that are fully quoted in the work. This includes words that are in quotation marks and words in blockquotes or even in the footnotes/comments.
Even if it does disregard quoted content, titles, long names and common language elements (in particular common language within a particular niche) are also not causes for concern. However, they are often highlighted and, in some cases, can represent a large chunk of the text.
Just like one shouldn’t blindly trust the findings of the software, one shouldn’t blindly trust the highlighting of it as even the best tools will spot text that, while matching, is not an issue.
Mistake 4: Not Having Proof
In the Reddit thread, many commenters shared stories about how they or someone they knew were accused of plagiarism without any real proof.
Teachers claimed that essays were “too well written” or showcased too much knowledge on the subject. However, rather than investigate those intuitions, they made accusations without any real evidence to support their claims.
However, those claims are meaningless without actual evidence. In many cases, there are other explanations for why the work was as good as it was, even if the student hadn’t reached that level in the past.
This is not to say that intuition has no role in fighting against plagiarism. However, it should guide one’s investigation, not one’s accusations. Doing so not only risks making false allegations, but those allegations are going to harm students who either received ethical help or simply worked harder on the paper.
In short, these allegations discourage students from working harder or significantly improving their work, the opposite of what instructors are supposed to do.
Mistake 5: Not Eliminating Inappropriate Sources
Finally, when performing a plagiarism check, there are some sources that a work should never be considered or compared against.
One example of this, which came up multiple times in the Reddit thread, were instructors who accidentally compared a completed work against earlier drafts of it. This included one case where a dissertation was flagged as plagiarized because it was too similar to its draft summary.
However, comparing an author’s most recent work to their previous work is, by itself, also risky. Though it’s understandable that instructors and editors want a new work and not simply a student handing in an old assignment a second time, it’s not uncommon for two similar works by the same author to have overlapping language, even if both works were written independently.
Eliminating inappropriate sources ensures that any matching text that is found is worth investigating. Otherwise, the analysis itself is tainted and whoever is performing it has to take extra steps to eliminate the sources as they go through it.
Bottom Line
Performing a plagiarism analysis is a lot of work and, though technology has done a great deal to streamline the process, there’s no substitute for a human performing a proper analysis based on those findings.
Most of the time, the problem is that teachers and editors don’t perform their due diligence. Either due to a lack of time or lack of concern, works go unchecked and plagiarism is missed until it is too late.
However, it’s also possible for one to be overzealous when pursuing plagiarism and make simple mistakes that can result in false accusations.
Simply put, a plagiarism allegation is a serious accusation. Even people who can quickly prove their innocence remember and are hurt by the accusations years and even decades later.
While plagiarism does have real harm when it comes to the integrity of education, it’s also important to acknowledge the harm that false plagiarism accusations can have.
So, it’s important to not only carry out plagiarism checks, but to carry them out correctly. Unfortunately, there are no shortcuts here. But it is incredibly important that we get this right.
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