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

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The Business of Editing: Creating Multiple Journals Datasets Simultaneously

I have written in past essays (see, e.g., The Business of Editing: Journals, References, & Dollars and The Business of Editing: Cite Work Can Be Profitable) about the Journals macro and how useful it is in my editing work. But the usefulness of the macro has always been tempered by the size of the dataset I am using. For example, the sizes of my current datasets are: American Chemical Society (ACS), 30,922; PubMed/American Medical Association (AMA), 98,669; Chicago/American Psychological Association (APA), 1981; and Harvard, 349. Clearly, my PubMed/AMA dataset is the most useful and reflects the type of projects I usually edit.

The other Journals datasets are increasingly being called on, yet at the moment, with the exception of the ACS dataset, they have too few names to be very useful.

The key to many of the macros in EditTools is the dataset; the larger the dataset, the more powerful the macro that uses the dataset. Consequently, how fast a dataset can be built is important.

Over the different versions of EditTools, changes have been introduced to the Journals Manager that were designed to increase the speed and efficiency with which Journals datasets are built. Originally, each entry variation to the dataset had to be made individually. To speed things up the Multiple Entry process was created. It allowed you to enter multiple variations at one time.

But you were still limited to dealing with a single dataset.

Journals version 7 changes that — now you can add entries to as many as five different datasets simultaneously. In addition, you no longer have to manually create each variation; many variations can be created automatically.

Switching to the Multiple Datasets Entry Screen

The first time you open the Journals Manager in EditTools v7, you will see the same Manager you have seen before (shown below) with one exception — the addition of the checkbox (circled in image):

Original Journals Manager Screen

Version 7 offers the Switch to Enhanced Journals Screen checkbox (#1 above). When you check the box, the dialog changes to the enhanced dialog shown here, which becomes the default:

New Enhanced Journals Manager Screen

If you do not need the multiple-dataset capability, you can return to the original single-dataset capability by checking the Switch to Original Journals Screen (#2), which will become the default journals entry screen again.

The enhanced screen allows journal entries to be added concurrently to as many as five different datasets. When you first open the enhanced screen, the available files are labeled Custom #1 through Custom #5 (#A and #B in above image). However, you can rename these to whatever you would like by double-clicking on the current name in the Always Correct Journal column to open the renaming dialog. For example, double-clicking PubMed/AMA (#3) opens the renaming dialog shown here:

Renaming Dialog

Enter the new name in the provided field (#4), and click OK. The name will be changed immediately to the new name, both in the Always Correct Journal column (#3) and at the corresponding name in the File Data to Show fields (#5).

The enhanced screen can be used to enter a single title, just as in the original screen. In the example shown below, the journal name being entered is Physiol Meas (#6). That form is fine for PubMed/AMA (#7), but not for the other datasets. So, in the fields for the other datasets, the correct forms are entered (#8 to #10). When Add (#11) is clicked, all four datasets are updated simultaneously — a significant timesaver.

Example Journal Entry

It is not necessary to make use of all of the dataset fields. You can use one, five, or any number between. Only those in which the Correct to field has an entry will be updated. In other words, if only the PubMed/AMA dataset is to be updated with the information in #6 and #7, then #8 through #10 are left empty. Clicking Add (#11) updates only the PubMed/AMA dataset — even though three other datasets are identified.

It is important to note that the journal names that appear in #7 through #10 are what the entry in #6 (and the multiple entries that will appear in #8 in the “Multiple Journal Name Entry Dialog” image below) will be changed to. In this example, when Add (#11) is clicked, the Chicago/APA dataset will have added to it the instruction to change Physiol Meas to Physiological Measurement in a document when the Journals macro is run and the Chicago/APA dataset is chosen. Similarly, the ACS dataset will gain the instruction to change Physiol Meas to Physiol. Meas. when the Journals macro is run and the ACS dataset is chosen.

The New Multiple Journal Name Entry Dialog

When the Multiple Entries button (#12 in the “Example Journal Entry” image above) is clicked, both the original and enhanced screens give access to the new Multiple Journal Name Entry dialog shown here:

Multiple Journal Name Entry Dialog

This dialog is different from the dialog that appears in in earlier versions of EditTools. The new Multiple Journal Name Entry dialog offers new options, many of which can be preset as default options, that are designed to make entry of multiple items into a single or multiple datasets quick and easy.

Previously, you had to manually enter trailing punctuation; now you can either individually set the trailing punctuation each time or preselect some (or all) (#1) as the default (#2). (If you copy text and paste it in the Text to Add field [#6], and in doing so include ending punctuation, you can tell the macro to ignore that trailing punctuation by checking the Ignore punctuation at the end of entry string box [#5].) Also in earlier versions, if a journal name began with “The” and/or included either “and” or “&”, you had to manually change them. For example, if the journal name was The Journal of Rise & Shine, to enter The Journal of Rise & Shine plus Journal of Rise & Shine, The Journal of Rise and Shine, and Journal of Rise and Shine, you had to enter each variation manually. Now you just need to add checkmarks to the Variations (#3) options.

The same is true for the different capitalization options (#4), except that the Title Case option also has options that are accessed by clicking the Edit button (circled in the above image), which opens this dialog:

Journals Title Case Manager

Here you tell the macro which words, when the Title Case option is checked, should always be lowercase unless they are the first word in the journal name. Consider the example shown below (#10). Note the option choices made (#11, #12, and #13). Clicking Add (#14) automatically adds the title and the variations to the main field (#15).

Journals Manager Multiple Entry Options

More than 50 variations are being added concurrently. You can see all of them at the Journals page at the wordsnSync website; we would need to add four additional images here to display them all.

Once you have generated the variations on a journal name that you want, you can add them to one or more of your journal datasets. The combination of the changes in the generation of variations and the ability to concurrently update up to five datasets makes creation of journals datasets a quick, efficient, and easy process.

The new enhanced Journals screen and the improved Multiple Journal Name Entry screen will enable you to build Journals datasets quickly. One thing to note: If a journal name (or variation) already exists in a dataset, a duplicate will not be added. Only unique names are added. Consequently, it does not matter if one of the Journals datasets already has, for example, The Rise & Shine Journal in it; that particular entry will be ignored for that dataset and the remaining variations that are not duplicates, such as The Rise and Shine Journal and Rise & Shine Journal, will be added.

Building datasets in EditTools is easy; building multiple journals datasets simultaneously in EditTools is also easy.

Richard Adin, An American Editor

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