By the end of this unit you should:
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Some of the errors in this category are likely to be considered the most serious by reviewers. The core aim of academic and scientific writing is to convey data, information and/or knowledge with zero distortion of meaning, and so errors that cause degradation of meaning need to be avoided. When checking your draft using the accuracy filter, there are six error types to look out for. Each of the error types are listed below.
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There are two main citation styles: author-year and numeric (as in this example). The corpus example is a citation from the source listed as the first item in the reference list indicated by the number in square brackets. There is, however, an error within the citation itself. When copying the number in figures, the writer omitted the final zero, and so the population became 10 times smaller. This type of careless error can cause severe confusion. In this example, readers may either believe the incorrect figure or work out that the figure is incorrect. Through this careless copying error, the writer may have created a negative impression, which could lead the reviewer to succumb to the cognitive bias known as the horn effect and be unduly influenced by this error. Copying errors are easy to avoid by being systematic. For example, when using the copy-and-paste function, doublecheck that the first and last words or numbers have been included. It is more difficult to make selection errors when using the arrow keys to control the cursor than manipulating a mouse, which relies on fine motor skills, and so the arrow keys are the recommended method of selection. Should it be necessary to copy onto paper, make sure that not only the final numbers or words are included, but that other copying errors do not creep in due to ambiguity caused by poor handwriting. Sixes and zeros may be mistaken for each other, particularly when zeros are not exact ovals.
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When writing a research article, the content of the draft may change significantly. This could be due to changes decided by the writer, but also may be the result of changes suggested or insisted on by co-authors, reviewers, editors or proofreaders. Mistakes in lists are commonplace. The number of items in the list should reflect the number of items that follow. For example, in the list above, initially there were only two items, but apparently a third item was added after the second without changing the introductory sentence which still only lists two items. This type of error appears obvious, but is easily missed by writers. However, people who read this without having seen earlier versions can easily notice such errors.
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The past has already occurred, the present is occurring now, but the future has yet to come. Although we may attempt to predict the future, we cannot be certain. Even simple events in the future may not happen due to unforeseen circumstances. The modal verb will tends to be used to show the certainty of a future action or state. In the example above, the writer expresses certainty. This could become true, but should a natural disaster, war or other event happen, would the claim still hold? Claims that are overly bold can be hedged in three ways. First, the certainty level can be reduced to show a degree of probability, e.g. using modal verbs such as: could, may or might. Second, the scope of the claim can be limited to one that will be certain (or at least no-one could prove otherwise). Third, a condition can be attached to the claim, to add a proviso.
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Claims about a characteristic of all members of a particular group are problematic. Is it possible to finish the corpus example in a way that is not contentious? Here are some suggestions to consider.
The first claim, a, presents an either-or dichotomy in which women cannot be men. In logic the law of noncontradiction states that two propositions A is B and A is not B cannot both be true. However, this law assumes shared definitions of both A and B. Definitions of women and men vary depending on religious, political or scientific beliefs. Thus, the term women can be interpreted in different ways depending on the beliefs related to biological sex and gender, it can be argued that a person born a biological male can undertake gender reassignment and become a woman. The second claim, b, is also problematic as some people with Swyer syndrome are born with XY chromosomes but have female genitalia and identify as female. The third claim, c, is not contentious, since by definition the term women has three elements of meaning: female, adult, human and plural. When making claims about a groups, it is necessary to play devil’s advocate and identify whether it is possible to argue against the claim. If it is, then consider adding modality, limiting the scope or adding a conditional.
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The probability value, p, is used to show the probability of finding equivalent or more extreme results while assuming the null hypothesis is true. In short, the smaller the p value the higher the statistical significance. However, reported p values tend to be either p < 0.05 or p < 0.01. These values are often considered sufficient to claim statistical significance when conducting hypothesis testing. In this example, the mistake was a typographic error that was not noticed in proofreading. The probability of 50% means that the result is random and no significance can be claimed, and the article will most likely be rejected.
Read.
Users of WYSIWYG text processing software, such as Microsoft Word, are used to receiving help from spelling and grammar checkers. Problems can, however, occur when the language settings of the document or sections of the document are not set to English. For example, when pasting text from a non-English document, it is possible to accidently change the language settings, which means that the English words in that section will not be checked. The situation appears even worse for users of LaTeX, which is a plain text editor. This means that writers do not see what their text looks like until it is compiled into a pdf. A key problem for novice uses of LaTeX is not using a spellchecker, since with many free LaTeX editors, spellcheck is not included by default. In the corpus example, Microsoft Word was unable to identify that form should have been from. Checking spelling and grammar in one’s own writing is particularly difficult given the screen-memory interference issue. In short, writers may not necessarily read what is currently written but may read what had been written.
More corpus examples of spelling and grammatical errors
Suggested revisions
In each case the spelling and grammatical errors have been corrected.
Make sure that you check your writing for the following types of errors: