The Business of Editing: The AAE Copyediting Roadmap VI

So far I’ve created a stylesheet and cleaned the document (see The Business of Editing: The AAE Copyediting Roadmap II), and tagged the manuscript by typecoding or applying styles (see The Business of Editing: The AAE Copyediting Roadmap III), inserted bookmarks for callouts and other things I noticed while tagging the manuscript (see The Business of Editing: The AAE Copyediting Roadmap IV), and created the project- or client-specific Never Spell Word dataset and run the Never Spell Word macro (see The Business of Editing: The AAE Copyediting Roadmap V). Now it’s time to tackle the reference list.

Fixing Reference Callouts

Before I get into the reference list itself, I need to mention another macro that I run often but not on all files — Superscript Me. Nearly all of the manuscripts I work on want numbered reference callouts superscripted and without parentheses or brackets. The projects usually adhere to AMA style. Unfortunately, authors are not always cooperative and authors provide reference callouts in a variety of ways, including inline in parentheses or brackets, superscripted in parentheses or brackets, with spacing between the numbers, and on the wrong side of punctuation. Superscript Me, shown below, fixes many of the problems. (You can make an image in this essay larger by clicking on the image.)

Superscript Me

I select the fixes I need and run the macro. Within seconds the macro is done. One note of caution: It is important to remember that macros are dumb — macros do as instructed and do not exercise any judgement. Consequently, even though Superscript Me fixes many problems, it can also create problems. My experience over the decade that I have been using this particular macro has been that the fixing is worth the errors that the macro introduces, even though they require manual correction during editing. The introduced errors are few, whereas the fixes are often hundreds.

Tip: Superscript Me is a powerful, timesaving (and therefore profitmaking) macro, but as noted above, it is dumb and just as it can do good, it can do harm — especially to reference lists. Before using Superscript Me on the manuscript, move the reference list to its own file. Doing so will ensure that Superscript Me makes no changes to the reference list, only to the main text material, saving a lot of undo work.

Wildcarding the Reference List

By this point, the reference list has been generally cleaned and moved to its own file.

Tip & Caution: Wildcard macros can be a gift from heaven or a disaster from hell. I like to do what I can to ensure they are a gift and not a disaster. Consequently, I move the reference list to its own file. I know I have said this before, but wildcarding is another reason for separating the reference list from the manuscript file. Often what I want changed in a reference list, I do not want changed in the primary text; similarly, what I want changed in the primary text, I do not (usually) want changed in the reference list. But like all other macros, wildcards are dumb and cannot tell text from reference list. It can do no harm moving the reference list to its own file and working on it separately from the main text, so be cautious and move it.

Individual problems, however, have not been addressed. I scan the list to see what the problems are and whether the problems are few or many. For example, if author names are supposed to be

Smith AB, Jones EZ

but are generally punctuated like

Smith A.B., Jones E. Z.

or in some other way not conforming to the correct style, I will use wildcard macros and scripts to correct as many of these “errors” as I can. Wildcards can address all types of reference format errors, not just author-name errors. For example, a common problem that I encounter is for the cite information to be provided in this format:

18: 22-30, 1986.

or

1986 Feb 22; 18: 22-30.

when it needs to be

1986;18:22–30.

These formatting errors are fixable with wildcards and scripts.

Scripts are like a supermacro. A script is a collection of many individual wildcard macros that have been combined into one macro — the script — and run sequentially. One of my reference scripts is shown here:

Wildcard Find & Replace Script

In the image, the active script file (#1) is identified and what it does (broadly) is described in the description field (#2). The wildcard macros that are included in the script and the order in which they will run are shown in the bottom field (#3). Included is a description of what each of the included wildcard macros will do (#4). For example, the first wildcard macro that the script will run will change Smith, C., to Smith C, and the second wildcard macro to run will change Smith, A.B., to Smith AB,.

The wildcard macros were created using the Wildcard Find and Replace (WFR) macro shown below. In the image, the example wildcard macro (arrow) is the same as the second macro in the script above, that is, it changes Smith, A.B., to Smith AB,.

Wildcard Find & Replace

Creating the macros using WFR is easy as the macro inserts the commands in correct form for you (for more information, see the online description of WFR). Saving the individual wildcard macros, assembling them into scripts, and saving the scripts, as well as running individual wildcard macros or scripts, is easy with WFR. (For some in-depth discussion of wildcards, see these essays: The Business of Editing: Wildcarding for Dollars; The Only Thing We Have to Fear: Wildcard Macros; and The Business of Editing: Wildcard Macros and Money.)

With some projects I get lucky and the authors only have a few references that are a formatting mess and when there are only a messy few, I fix them manually rather than run the macros.

Fixing Page Ranges

If the references are in pretty decent shape (formatwise) so that I do not need to run WFR, I will run the Page Number Format macro (shown below) to put the page range numbering in the correct format For example, the macro will automatically change a range of 622-6 to 622–626, 622–6, or 622.

Page Number Format

Making Incorrect Journal Names Correct

At long last it is time to run the Journals macro. As my journals datasets have grown, they have made reference editing increasingly more efficient. It takes time to build the datasets, but the Journals Manager (shown below) lets me build multiple datasets simultaneously.

The Journals Manager

As shown in the image, I can build five datasets (arrows) simultaneously. My primary dataset — AMA with Period — has 212,817 journal entries (see circled items).

Tip: Move the reference list to its own file to shorten the time it takes to run the Journals macro. The larger your journals dataset, the more time the Journals macro requires to complete a run. Each iteration of the Journals macro searches from the top of the document to the end as it looks for matches. Leaving the reference list in the manuscript means the macro has that much more to search. In a recent timing test of the Journals macro using my primary dataset and a 50-page document with 110 references without separating out the list, the macro was still running after 2 hours and was not near completion. Running the Journals macro with the same dataset and on the same reference list — but with the list in its own file — took less than 10 minutes. (Think about how long it would take you to manually verify and correct 110 Journal names.)

The Journals macro searches through the reference list for journal names and compares what is in the reference list against what is in the chosen dataset. If the name in the reference list is correct, the macro highlights it in green (#5), as shown below; if it is incorrect, the macro corrects it and highlights the change in cyan (#6). All changes are done with Tracking on.

The Reference List After Running Journals Macro

The Journals macro does two things for me: First, if the incorrect variation of the journal name is in the dataset, it corrects the incorrect journal name so that I do not have to look it up and fix it myself (see #6 above). If the incorrect variation is not in the dataset, the macro makes no change. For example, if the author has written New Engand J. Med but that variation is not in the dataset, it will be left, not corrected to N Engl J Med. When I go through the reference list, I will add the variation to the dataset so it is corrected next time. Second, if the journal name is in the dataset, it highlights correct names, which means that I know at a glance that the journal name is correct and I do not have to look it up (see #5 above).

It is true that the names of some of the more frequently cited journals become familiar over time but there are thousands of journals and even with the frequently cited ones with which I am familiar, correcting an incorrect name takes time.

It is important to remember that time is money (profit) and that the less time I need to spend looking up journal names, the more profit I make.

After I run the Journals macro, I open the Journals Manager (see above) and I go through the reference list, doing whatever editing is required and fixing what needs fixing that my macros didn’t fix. Because of the current size of my journals datasets, there aren’t usually many journal names that are not highlighted. When I come to one that is not highlighted either green (indicating it is correct) or cyan (indicating it was incorrect but is now correct), I look up the name and abbreviation in the National Library of Medicine online catalog and other online sources. When I locate the information, I add it and the most common author variations (based on my experience editing references for more than 30 years) to the five datasets via the Journals Manager.

I take the time to add the journal and variations because once the variations have been added, I’ll not have to deal with them again. Spend a little time now, save a lot of time in the future.

In addition to editing the references for format and content, I also keep an eye out for those that need to be removed from the reference list and placed in text — the personal communication–type reference — and for those that need to be divided into multiple references. When I come across one, I “mark” it using a comment. For example, using the Insert Query macro (which is discussed in the later essay The Business of Editing: The AAE Copyediting Roadmap X), I insert the comment shown below for unpublished material:

Query for Unpublished Material

When I come to the in-text callout during the manuscript editing, I move the reference text to the manuscript, delete the callout and the reference, and renumber using the Reference # Order Check macro (which is discussed in the later essay The Business of Editing: The AAE Copyediting Roadmap VIII).

Now that the Journals macro has been run and the references edited, the next stop on my road is the search for duplicate references, which is the subject of The Business of Editing: The AAE Copyediting Roadmap VII.

Richard Adin, An American Editor

EditTools & My Editing Process: Part II

Part I introduced the preediting steps (Steps 1 to 3). Part II discusses the remaining two preediting steps (Steps 4 and 5) and then discusses the first editing step (Step 6) in my editing process, which is editing the references.

Step 4: Moving the References

Most of the projects I work on have extensive reference lists. Sometimes a chapter will have a relatively short reference list of 50 or so, but most are at least 100 references, and sometimes are more than 1,000 references.

After the preliminary steps and before running Never Spell Word (Step 5), I move the reference list to its own file. I do this for several reasons. First, some of the macros that I use during editing can affect the references, creating undo work for me. Moving the references to their own file avoids this problem.

Second, I like to edit with Spell Check on. However, Spell Check sees many author names and foreign spellings in journal names and article titles as misspellings. That wouldn’t matter except that it often leads to the message that Spell Check can’t be used because there are too many spelling errors and so Word will turn off Spell Check — for the entire document. By moving the references to their own file, I almost always avoid that particular problem. (Yes, I am aware that I could turn off Spell Check just for the references — for example, by modifying the styles used in the references, which is what many editors do — but I like Spell Check to be on even for the references.)

Third, I want to be able to run my Journals macro unimpeded and as quickly as I can. The more material the Journals macro has to run through, the longer it takes to complete.

Fourth, I want to be able to run Wildcard Find & Replace on the references without having the macro also affect other parts of the document.

And fifth, moving the references to their own file makes it easier to check text reference callouts against the references because I can have both the primary document and the references open concurrently and on different monitors.

I do not edit the references in this step; I simply move them to their own file.

Step 5: Project-Specific Never Spell Word

The next preedit step is to create my project-specific Never Spell Word (NSW) dataset, which is shown below. Every project has its own NSW dataset (#13). The only time I use a previously created dataset is when I have edited a previous edition of the book. I assume that word usage decisions made in previous editions will continue in the current edition. This is generally reinforced when the client also sends me a copy of the stylesheet I prepared for the prior edition (or tells me to use it, knowing I have it available on my website). I do, however, go through the NSW dataset to make sure there are no changes that need to be made as a result of changes in the applicable style guide or in other pertinent guidelines (e.g., changing over-the-counter and OTC to nonprescription).

Never Spell Word dataset

If I cannot use a previously created NSW dataset, I create a new one using the Never Spell Word Manager shown above. Note that when I speak of the NSW dataset, I am really speaking about the one tab in the Manager — the Never Spell Words tab (circled). Although the other tabs are part of the NSW macro, they are not project specific as I use them; however, they can be project specific, as each tab can have multiple datasets, and the tabs also can be renamed.

In the example NSW, the dataset has 70 items (#15). These items were specifically mentioned by the client or the author(s) (e.g., changing blood smear to blood film, or bone marrow to marrow) (#14), or things I noticed that will need changing (e.g., changing Acronyms and Abbreviations that appear in this chapter include: to Acronyms and Abbreviations:) (#14). As I edit and discover more items that should be added, I add them through this Manager.

The NSW macro has multiple tabs, some of which may not be relevant to the current project. Running the NSW macro brings up the NSW Selector, shown below. Here I choose which tabs to run. The default is Run All, but if I need to run only the NSW and Commonly Misspelled Words tabs for the particular project, I check those two and click OK and only those two parts of the macro will run.

Never Spell Word Selector

After the NSW macro is run, it is time to begin editing.

Editing Steps

Step 6: The References

My first task is to edit the references that I moved to their own file in Step 4. I deal with the references before editing the text so I can determine whether there are “a,b,c” references (e.g., 57a, 57b) or if the references are listed alphabetically even though numbered. This is important to know for setting up the Reference # Order Check macro, found on the References menu and shown below, for tracking callout order and for renumbering if needed.

Reference # Order Check

After I set up the Reference # Order Check macro, it is time to look at the references and see if the author followed the required style. Occasionally an author does; usually, however, the author-applied or -created style is all over the place. So the next macro I run is Wildcard Find & Replace (WFR) (shown below) and the appropriate scripts I created using WFR. The scripts focus on specific problems, such as author names and order-of-cite information (e.g., year first or last).

Wildcard Find & Replace & WFR Scripts

The scripts cure a lot of problems, but not all of them. Following the scripts, I run the Journals macro. Depending on which dataset I use, running the Journals macro may well fix nearly all of the journal names.

After running the Journals macro, I go through the references one by one, looking for remaining problems that need fixing, such as completing incomplete citations. If I come across a journal that was not in the Journals dataset, which I know because it is not color coded, I verify the journal’s name. I also go to the Journals Manager enhanced screen, shown below, so I can add the journal to multiple datasets concurrently.

Journals Manager Enhanced Screen

Once I have finished editing the references, it is time to begin editing the main text (Step 7), which is the subject of Part III.

Richard Adin, An American Editor

_______________

Looking for a Deal?

You can buy EditTools in a package with PerfectIt and Editor’s Toolkit Plus 2014 at a special savings of $78 off the price if bought individually. To purchase the package at the special deal price, click Editor’s Toolkit Ultimate.