2022: My Year in Astrophotography

31 December 2022

In case you didn’t know, I not only do words and historical linguistics, I’m also an amateur astrophotographer; that is, I take pictures of the night sky. I’ve been doing it, off and on, since 2008, but 2022 is the year that I finally got good at it. This is a compilation of the images I’ve taken during the past year.

I post my images to the Astrophotography section of the Wordorigins website and to Astrobin.com. If you want all the technical details about how I took the images, Astrobin is the place to find them, along with images taken by amateur astrophotographers around the world.

All of these images were taken from my driveway in Princeton, New Jersey, under Bortle 6 (bright suburban) skies.

I started off the year with an image of the:


26 January 2022

An emission nebula in the constellation Monoceros, 5,200 light-years away. This is a false-color image using narrowband filters to cut out light pollution. Emission nebulae consist of ionized gases that emit their own light. The filters cut out all light except that emitted by specific elements. This image uses the “Hubble palette,” assigning light from Hydrogen-ɑ gas to the green channel, from Sulfur-II to the red, and from Oxygen-III to the blue. The color scheme gets its name from its use by scientists using the Hubble space telescope.

This image is a total of 4.17 hours integration time (50 exposures of 5 minutes each), taken with a TeleVue NP127is refractor and a ZWO ASI2600 cooled, monochrome, CMOS camera mounted on my Takahashi EM-200 equatorial mount. I used a set of Baader 6.5-nanometter narrowband filters (H-ɑ, O-III, and S-II). My guide scope was a Sky-Watcher Evoguide 50DX with a ZWO ASI120MM Mini camera (which is the guide scope I’ve used for most of the images here). My capture software running the mount and camera is TheSkyX. Postprocessing used Deep Sky Stacker and Photoshop CC software.

Astrophotography is a challenging hobby. There are three main types of astrophotography: landscape or Milky Way, planetary, and deep-sky. All take practice, use different types of equipment, and require very different techniques. I haven’t done landscape work, which usually combines images of the Milky Way with compelling, earthly foreground objects. It uses a standard camera and tripod, or maybe a star-tracker mount for slightly longer exposures. I do a bit of planetary photography, which I describe below.

A telescope sitting in the driveway of a house

But most of what I do is deep-sky work, nebulae, galaxies, and star clusters. Deep-sky photography requires a mount that tracks and counteracts the rotation of the earth, a telescope, and a camera used for long (several minute) exposures that are integrated into a single, final image. Most people ask what telescope I use, but the most important piece of equipment is the mount. Unless you have a mount that accurately counteracts the rotation of the earth, you get blurred images. Also, a second, smaller telescope, camera, and computer are usually required for autoguiding. The second scope and camera focus on a single star and if it moves, send commands to the mount via a computer to correct for that movement. If done right, it results in an image with round, pinpoint stars with no elongation or trailing. And since the target objects are very dim, the images require considerable postprocessing work to reveal all their glory. (But without adding anything; if you see it in the image, it exists in the night sky.)

Here is the mount that I used for most of these 2022 images, a Takahashi EM-200. On it is mounted my TeleVue 127-mm refractor (660-mm focal length), dew heaters, computer, cooled camera, and filter wheel. The smaller telescope and camera mounted on top comprise the autoguider. I also have a 203-mm Ritchey-Chretien telescope (1,624mm focal length) and a 51-mm refractor (250-mm focal length). A long focal length produces magnified images of small objects, while a short focal length gives a wide-field view. I’ve had the Takahashi mount since 2008, and it has been a champ, but I’ve recently retired it in favor of a heavier-duty and more accurate Paramount MYT. More on that toward the end.


A cloud of brownish-yellow gases with a bright, white core against a starry sky

5–6 February 2022

The Orion Nebula (M42) is some 1,300 light years away. It is the middle “star” in Orion’s sword. This is one of the most popular deep-sky targets, but it is deceptively challenging. It’s easy to find—you can see it with the naked eye even in very light-polluted skies—but the high dynamic range (combination of faint gases on the outside of the very bright core) make it a tough one to image and process.

This is an exposure of 100 minutes of integration time (20×5-minute). Equipment is as above; except I started using PixInsight software for postprocessing instead of Deep Sky Stacker and Photoshop.


A spiral galaxy against a starry sky

12 & 29 April 2022

Spiral galaxy in Ursa Major, approximately 12 million light-years distant. This is a true-color image, using red, green, and blue filters with monochrome cameras.

This image has 4 hours, 25 minutes of integration time. (55×300sec). This time I used my 203mm TPO Ritchey-Chretien telescope to zoom in on the galaxy. I also used two different cameras for this one: ZWO ASI2600 & 1600 cameras. The 2600 is a superb camera, but a defect in quality control resulted in many of them suffering from oil leaking onto the sensor. My camera was out of commission for a while until I acquired the proper cleaning supplies. The problem kept recurring, and at the end of the year ZWO agreed to replace it. Hence, I reverted to my older ASI1600 for this and other images. Such is this hobby; seldom does everything work perfectly at the same time. That’s what keeps you on your toes.


A spiral galaxy drawing stars and gases away from a smaller galaxy

10 & 11 May 2022

Spiral galaxy in Canes Venatici, approximately 31 million light-years distant, and its companion NGC 5195, with which it is interacting. 

Integration time of 7.5 hours (90x300sec). Again, using my Ritchey-Chretien telescope.


Two nebulae, one shaped like North America and another that resembles a pelican

4, 5, & 9 June 2022

Emission nebulae in Cygnus. This is a wide-field image, taken with my William Optics Redcat 51 refractor telescope, focal length of 250mm for a wide-field view, and my ASI2600 camera. This is another narrowband image using the Hubble palette. But for this one (and all the ones going forward), I used a new set of narrowband filters, Antlia 3.5-nanometer H-ɑ, OIII, and SII filters.


Wispy tendrils of gases against a starry sky

14 June 2022.

A supernova remnant in Cygnus, some 2,400 light years distant.

3 hours, 45 minutes integration time. Again, using the Redcat 51, ASI2600, and narrowband filters.


EAGLE NEBULA (M16)

A bird-shaped nebula with pillars of gas at the center

24, 25, 30 June, 3, 10, 14 July 2022  

An open cluster with star-forming nebulae in the constellation of Serpens, some 5,700 light-years distant

This was my longest integration time to date, a total of 22 hours, 52 minutes, 30 seconds integration time, using 450-second exposures of H-alpha, Oxygen III, and Sulfur II. This time I went back to my TeleVue NP127is refractor, which gives me a medium field of view between that of the Ritchey-Chretien and the Redcat 51.   

Close-up of the pillars of gas in the above image

Here is a detail of the above image, showing the “Pillars of Creation,” a star-forming region, in close-up.


Clouds of brown-colored gases around a bright star

19–22 July 2022

Emission nebula surrounding the star Sadr (Gamma Cygni) in the constellation Cygnus. Another mega-integration time: 25 hours, 37 minutes, 30 seconds; 450-second exposures of H-alpha, Oxygen III, and Sulfur II. Equipment as above.


Starless image with a single pillar of gas that resembles an elephant's trunk at the center

3 August 2022

A starless take on the nebula in the constellation Cepheus, about 2,400 light years distant. I’d been trying to get the backfocus right on my telescope. Backfocus is the distance between the last optical element in the imaging train and the camera’s sensor, and if it’s not right, the stars at the edges can appear misshapen. So, this is an image with the stars removed. It has the advantage of making the nebulosity more prominent. It’s common to remove the stars during postprocessing in order to work on the nebulosity, but usually you add the stars back.

Total of 6 hours, 37 minutes, 30 seconds integration time; 450-second exposures of H-alpha, O-III, and S-II. Equipment as above.  


A gas-giant planet with layers of gas running across it

8 September 2022

My first serious attempt to image a planet. Planetary imaging is a very different beast, using a technique called lucky imaging. Atmospheric distortions wreak havoc on planetary images; deep-sky targets are much more forgiving in this respect. To combat this, one takes a video—thousands of frames—and combines only those “lucky” few that happen to be clear into the final image. I’m still learning.

This one used my Ritchey-Chretien scope and a ZWO ASI290MM camera, with infrared, red, green, and blue filters. I used the infrared frames as a luminance channel. Postprocessing was with Autostakkert and RegiStax software.


A gas-giant planet with rings around it

8 September 2022

Saturn on the same night as Jupiter with the same equipment, only I also used WinJupos software in postprocessing. This one came out much better.


A large, spiral galaxy against a starry sky

15 September 2022

Widefield shot of the nearest major spiral galaxy, 2.5 million light years distant. Andromeda is massive, taking up about 3 degrees in the night sky—that’s 6 full moons across, but so faint that you only see the bright core with the naked eye, if light pollution permits even that.

This one was taken with my portable rig: my Redcat 51 refractor and Canon D6 Mark II (modified) DSLR camera, mounted on a Sky-Watcher StarAdventurer GTi star tracker. The camera is modified to extend the spectrum it captures deeper into the red so it can capture Hydrogen-ɑ emissions. I also used an Optolong L-Pro light-pollution filter.

Total of 1 hour, 9 minutes integration time (23×180-second exposures)    


A cloud of red and teal gases that resemble a human eye against a starry sky

23 September 2022

Also called the Eye of Sauron, this is a planetary nebula some 650 light-years distant in the constellation Aquarius. Planetary nebula is a misnomer, dating to the eighteenth century when astronomers thought these objects resembled planets. They are formed by dying stars sloughing off gases.

For this one I used a cooled, color, astronomy camera, a QHY183C, my Optolong L-Pro light-pollution filter, and my TeleVue NP127is refractor. Integration time was 3 hours (36×300 seconds).


HEART & SOUL NEBULAE (IC 1805 & IC 1848)

Two red nebula, one resembling a human heart, against a starry sky

23 September 2022

Emission nebulae in Cassiopeia, some 7,500 light-years distant.

I ran two different imaging rigs this night. This second one was taken with my portable rig, using an Optolong L-Pro filter. 5 hours, 56 minutes, and 16 seconds of integration time (167×128 seconds).


A spiral galaxy against a starry sky

27 September 2022   

This is the third spiral galaxy in our local group, the others being Andromeda and our own Milky Way. At 2.73 million light-years, it's the most distant object that can be seen with the naked eye.

Total of 8 hours, 20 minutes integration time (100×300 seconds) with LRGB filters, using my TeleVue NP127is refractor and ASI2600 camera.    


Two nebulae, one resembling a lobster's claw and the other containing what looks like a soap bubble

8–11 October 2022

Emission nebulae in Cassiopeia, some 7,100 to 11,000 light-years distant

Total of 26 hours, 45 minutes integration time, 214×450-second exposures of Hydrogen-α, Oxygen-III, and Sulfur-II, using my TeleVue NP127is refractor and ASI2600 camera.

Here is a detail of the above image showing the “bubble.”


LUNAR ECLIPSE

A composite of images of the full moon, running from gray on the left, gradually disappearing in to blackness, until the final image of a red moon

8 November 2022

Composite of images from the first half of the eclipse. I didn't get the second half because of sunrise. For this one, I just used a tripod, my Canon 6D Mark II with my Redcat 51 telescope as the lens, and a 4× Barlow lens for magnification. Various exposure times at ISO 1600.


Gray and orange nebulae with a cloud of black dust resembling a horse's head at the center

4 December 2022

A telescope sitting in a driveway

Dark and emission nebulae in Orion; the bright star is Alnitak, the leftmost star in Orion’s belt. Total of 6 hours, 30 minutes integration time, 39×10-minute exposures of Hydrogen-α, Oxygen III, and Sulfur II. 

This image was also processed using Russell Croman’s BlurXterminator tool, which is an AI program that conducts deconvolution, sharpening stars and nebulae. Deconvolution is a laborious and painstaking process that is difficult to get right. This tool makes it simple. I expect it will improve my images no end going forward.

This image is also the first light using my new mount, a Paramount MYT equatorial mount. Here is my Paramount with my TeleVue refractor mounted on it. The red camera at the end is the ASI2600, which is attached to a filter wheel that holds the various filters I use. The red box on top is the SkyX Fusion computer that runs the rig. Since this picture was taken, I’ve added a Moonlite Nitecrawler electronic focuser, which keeps the telescope in focus as conditions change throughout the night.


Orange nebula that is said to resemble a map of California

9 December 2022 

Emission nebula in Perseus, some 1,000 light-years distant. Some people think this nebula resembles a map of California, hence the name; I don’t see it, but to each their own. A total of 9 hours integration time, 27×20-min exposures of Hydrogen-α, Oxygen III, and Sulfur II. This one used my Redcat 51 on the Paramount MYT, and my ASI1600 camera (my 2600 having been sent back for replacement due to the dreaded oil leak problem).  

Amazingly, the Paramount managed 20-minute exposures with no star trailing and did this without the help of a second guide scope. The Redcat has a wide field of view, which is more forgiving, but even so, this is amazing performance in a mount. I can’t wait to see what this mount allows me to do in 2023.


An orange nebula with a teal center

12–13 December 2022

My final image of the year: the emission nebula in Cassiopeia which I had previously imaged above alongside its companion, the Heart Nebula. A total of 17 hours integration time, 51×20-min exposures of Hydrogen-α, Oxygen III, and Sulfur II, using the Redcat 51 and ASI1600 camera. Again, no guide scope or camera.


I’m looking forward to what 2023 will bring, and I’m wishing you all the best for the new year. 

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ChatGPT vs Wordorigins.org Smackdown

Drawing of a computer casing with the label “HAL 9000” and a red camera lens

Depiction of HAL 9000, the artificially intelligent computer in Stanley Kubrick’s 1968 film 2001: A Space Odyssey

What happens when an AI tries to do etymology?
21 December 2022

A new large-language-model, artificial-intelligence (AI) engine, ChatGPT, has debuted. When one types a query into the AI, it returns a response in grammatically correct and sensical English. It has caused a bit of a stir. For one thing, there are those who are foretelling the end of human writing, or at the least the end of the of the first-year university essay. (Mark Liberman over at Language Log has a non-sensational summary of the debate, including links to various articles opining on the AI and its impact, and an assessment of the ability to detect whether or not an essay was written by the AI.) But from my playing around with it, ChatGPT is indeed an impressive step-forward in machine-produced, natural language, but the fears, moral panic, and click-bait headlines it has inspired are overblown, at least for the immediate future.

The AI is really quite remarkable. It produces intelligible, grammatically and (mostly) idiomatically correct English sentences and paragraphs. For instance, I typed How are you doing? into the engine and got this response:

As an artificial intelligence, I don't experience emotions in the same way that humans do. I am a computer program designed to assist with tasks and answer questions to the best of my ability. Is there something specific you would like to know or discuss?

While this response would pass the Turing test, many other responses, while correct English, are problematic. I asked the AI a series of questions about the origins of various words and phrases. Most of the responses would earn the grade of D in my first-year composition course. A typical response to a question about the origin of a term is:

The phrase “an exception that proves the rule” is a common saying that is used to indicate that an exception to a rule or generalization actually serves to confirm the rule or generalization. The phrase is often used to emphasize that a particular exception does not invalidate a rule, but rather serves to demonstrate its validity.

The phrase “an exception that proves the rule” is believed to have originated in the late 16th century, and it is thought to have been derived from the Latin phrase “exceptio probat regulam,” which means “the exception confirms the rule.” The phrase was originally used in the context of legal reasoning, and it was used to indicate that an exception to a rule actually served to confirm the rule's validity.

Over time, the phrase “an exception that proves the rule” has come to be used more broadly in everyday language to refer to any exception that serves to confirm a rule or generalization.

The response is very general and does not contain citations for the sources of information. The AI’s responses are often structured in the three-paragraph “hamburger” essay format of introduction, body paragraph, and conclusion that is favored by high school and first-year university students. In this case, the introductory paragraph is merely a literal reading of the phrase. The body contains three facts, the date, the Latin origin, and the origin in legal contexts. The conclusion is simply a restatement of the introduction. This one is remarkable only in that the facts are basically correct, if superficial and cursory.

In the questions I asked, the AI occasionally got the origin correct. In addition to the exception that proves the rule, it also correctly sourced big bang to astronomer Fred Hoyle in the 1940s. And the response to my question about gaslight correctly flagged Patrick Hamilton’s play as the source, later popularized by the 1944 movie starring Ingrid Bergman. But correct facts and specificity were not usually the case.

In some cases, the AI plumped for a long-debunked false etymology. And it did so on my very first query when it gave the port out, starboard home origin for posh. When asked about the origin of the whole nine yards, the AI came up with the following:

The phrase “the whole nine yards” is thought to have originated in the United States in the mid-20th century. There are a few different theories about its origin, but the most widely accepted one is that it refers to the amount of fabric used in a military uniform. According to this theory, a standard U.S. Army uniform required about nine yards of fabric, so if someone had “the whole nine yards,” they would have a complete and fully outfitted uniform.

Another theory is that the phrase refers to the length of a football field, which is 100 yards. If someone goes “the whole nine yards,” they are going all out or giving their all.

It is also possible that the phrase “the whole nine yards” is simply a colorful and vivid way of saying “everything” or “all of it,” without any specific meaning or reference to a particular quantity.

First, the dating is wrong. I’ve seen many different fabric-related hypotheses, but the military uniform version is a new one on me. And as the AI phrases it, the football hypothesis makes no sense—how is going nine yards giving one’s all on a hundred-yard field? The hedging, as in thought to have and is also possible, is also typical of the answers generated, and also of first-year university essays. If it had emotions, I would say the AI lacks confidence in its answers.

In a few instances, the AI pointed to supposed Old English words as the origin. It came close with threshold, saying it comes from:

“þresceold,” which is a combination of the words “þresc,” meaning “threshold,” and “ceold,” meaning “cold.”

While the spelling is wrong, þerscold is indeed an Old English word and the source of the Present-Day English word. But the breakdown of the syllables is wrong.

In other instances, the AI gave fictitious, and sometimes laughable, Old English roots. For instance, of fuck it said:

The word “fuck” is believed to be derived from the Old English word “fōc,” which means “goat.”

Goat?! Where did that come from? The Old English word for goat is gat. Fōc is not a word found in the extant Old English corpus.

Sometimes it gets the origin mostly correct but makes other errors, as in the origin of the name of the element americium:

Americium is a synthetic chemical element with the atomic number 95 and the symbol Am. It was discovered in 1944 by a team of scientists at the University of California, Berkeley, led by Glenn T. Seaborg. The element was named “americium” in honor of the United States, where the element was discovered and first produced.

The name “americium” is derived from the Latin word “America,” which was the name of the region of the world now known as the Americas. The name “America” was chosen by the Italian explorer Amerigo Vespucci, who explored the region in the early 16th century and claimed it for Spain. The name “americium” was chosen for the new element because it was discovered and first produced in the United States, which is located in the Americas.

Vespucci did not name the continents; they were named for him. And there is also weird usage in the Latin word “America,” which was the name of the region of the world now known as the Americas; the Latin name did not exist until Europeans made their way there and named the region for Vespucci. Also, the naming of the element was more nuanced than simply naming it for the United States.

Or there is the case of political sense of lobby, which the AI correctly traces to the nineteenth century Britain and does not repeat the false story of the origin in Washington, DC hotel lobbies. But then it says lobby comes from the Old French word “lob,” which means “a place where one can lounge,” which is just wrong.

Or the linguistic term snowclone, which the AI correctly dates and credits to Geoffrey Pullum, but which also says:

The term is a play on the word “snowclone,” which refers to a type of fossilized snowflake that is preserved in ice or permafrost.

Now this sense of snowclone might very well be an obscure technical definition (although I’ve never heard of it), but it is definitely not the inspiration for the linguistic term.

But giving factually incorrect and long-disproven information is something that undoubtedly will be corrected as the AI improves. The AI does not search the internet; rather it relies on training data that has been fed to it by the developers, and garbage-in/garbage-out, as the saying goes. With better training data, the AI will make such mistakes less often. At least in writing aimed at a general audience. I’m more skeptical of its ability to produce acceptable writing aimed at experts in a field.

While I can easily see a future version of this AI producing solid, Wikipedia-style responses, its writing lacks style and affect. It’s bland and boring. I suspect this will be a harder problem to solve than just getting the facts right. Perhaps it will eventually be able to produce something that someone wants to read. At present, the AI seems to be programmed to avoid writing creative pieces. I asked it to write me a poem about Christmas and it spit out Clement Moore’s A Visit from St. Nicholas (without crediting Moore). Others, however, report that the AI does produce original, albeit bad, poetry.

Crediting sources will also be a tricky problem for the AI to solve. It’s one thing to give Hamilton the credit for Gaslight or Hoyle for big bang, but to actually follow a trail of scholarly works and properly credit the ideas within that discourse is quite another.

To be sure, the AI poses a problem for teachers of writing in that students will undoubtedly use it as a vehicle for plagiarism, but in its present incarnation it is not all that scary and does not presage the “end of the college essay” as some have predicted. The AI’s answers are very superficial, and a bit more care in phrasing essay prompts will go a long way toward defeating any attempts at plagiarism. The AI also gives the same response each time a question is posed, and the developers have produced a tool to help identify texts that have been produced by the AI (I have not tested this tool). And teachers can embrace it as an in-class tool to help students identify and edit sub-standard writing and superficial arguments. With a little bit of ingenuity on the part of composition instructors, the AI as it exists today and in the immediate future will be no more a threat to academic integrity than the myriad human-based essay mills already are.

All problems aside, it's an impressive achievement, and it will get better with time, but the doomsaying is overblown.

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From Barflies to Bitcoin: How Words Map Our Modern Era

Cover of From Barflies to Bitcoin: How Words Map Our Modern Era

by David Wilton, cover and illustrations by Ania Wilton

Did you know that the word musher, meaning a person who travels the Arctic by dog sled, makes its English language debut in 1900, at the height of the Klondike gold rush? And in the 2010s people were engaging in a different kind of treasure hunt by swiping right and inviting someone over to Netflix and chill? The words that enter the language in any given year can be a key to the zeitgeist[*]of the era.

From Barflies to Bitcoin: How Words Map Our Modern Era[†] is a linguistic treasure hunt of sorts, examining each year of the twentieth century, plus the opening decades of the twenty-first, for the neologisms that make their appearance during them. In so doing, the book provides a chronological history of the period through the words that were coined during it. For example, here are some words that appear in various years:

1901: dognapper, jai alai, motorism, Ms, pizzeria, pointillism

1950: aqualung, brainwashing, LSD, microfiche, Orwellian, Scrabble

2001: Blu-ray, bromance, CRISPR, Homeland Security, iPod, sext

Word lovers will enjoy combing through it for odd terms or words that appear surprisingly early or late, while history buffs will see events unfold before them, and looking up the particular years that the reader has lived through will evoke feelings of nostalgia and bring to mind the fads and fashions of that earlier era.

The book is written for the general reader in an accessible style, organized into short, annual sections that make it appropriate reading for a commute. Yet it is meticulously researched, with a notes section and bibliography at the end will provide references for those readers who want to follow up on the research. The primary reference is the Oxford English Dictionary, and I used the online version of that dictionary to assemble the preliminary lists of words for each year. I then went on to other reference works, such as Green’s Dictionary of Slang, the “Among the New Words” column of American Speech, and other sources to see where antedatings are available and modified the lists accordingly. The selection of words to represent each year is subjective, based on how they represent historical and cultural trends, whether they appear surprisingly early or late, or whether they are simply odd and interesting in and of themselves.

From Barflies to Bitcoin is available from Amazon.com.

 

[*] English borrowed Zeitgeist, literally “spirit of the times,” from German in 1848, a year that was racked with revolutions across Europe and during which Karl Marx and Friedrich Engels published the Communist Manifesto when “a spectre [was] haunting Europe.”

[†] Barfly (1906) is a habitual patron of a drinking establishment. Bitcoin (2008) is a form of cryptocurrency.

To Oxford or Not to Oxford? That is the question.

13 February 2022

Meme claiming the sentence After beating the Steelers, Tim Tebow thanked his parents, God and Ms. Trunchbull is confusing

Meme claiming the sentence After beating the Steelers, Tim Tebow thanked his parents, God and Ms. Trunchbull is confusing

A bunch of comments about the use, or lack thereof, of the Oxford comma have been appearing in my Twitter feed as of late, so I thought I’d put my thoughts on the subject here, rather than responding to a multitude of threads.

First, let me state for the record that I prefer to use the Oxford comma. I use it in my writing.

That said, unless I’m working as a copy editor where the house style is to use it, I do not insist that others do so. And I never think that someone who opts not to use it is a lesser writer. That is because whether or not use the Oxford comma is a style choice. Ultimately, it makes no difference.

For those who are uninitiated into the sacred rites of punctuation, the Oxford, or serial, comma is the comma that appears before the final item in a list. Example: the phrase bacon, ham, and eggs uses the Oxford comma; the phrase bacon, ham and eggs does not. It is called the Oxford comma because the house style of Oxford University Press is to use it. Most of the publishers in Britain do not call for its use (which is why Oxford is singled out); while most of those in the United States do call for its use in the material they publish.

For those who insist on its use, as well as for those who insist it not be used, should take note of this last fact. The vast majority of people in Britain and United States get along just fine without a single, hard-and-fast rule. If it truly made a difference, there would be a unified rule.

That said, there are individual instances where the use or lack thereof of the Oxford comma can create confusion. Hardcore advocates love to point these out, but most of the examples they choose to highlight are not really confusing. The instances where genuine confusion can arise are rare.

Meme claiming the sentence I had eggs, toast and orange juice is confusing

Meme claiming the sentence I had eggs, toast and orange juice is confusing

One meme that has circulated claimed that the following sentence is confusing:

After beating the Steelers, Tim Tebow thanked his parents, God and Ms. Trunchbull.

The problem with this example is that absolutely no one would seriously entertain the idea that Tim Tebow was the offspring of the supreme deity and Ms. Trunchbull. There is nothing confusing about this sentence.

Another even more absurd example is a meme that claims the following sentence is confusing:

I had eggs, toast and orange juice.

The meme says that this sentence is a claim about eating eggs that is addressed to toast and orange juice. Again, the idea that a person would be speaking to breakfast food is silly. There is nothing confusing about this sentence.

A somewhat more astute example can be seen in a meme that claims that the following phrase is confusing:

the US president, a racist and a misogynist

Meme stating that the phrase the US president, a racist and misogynist refer is confusing

Meme stating that the phrase the US president, a racist and misogynist refer is confusing

If one is referring to Jimmy Carter or Barack Obama, there is no confusion. No serious person is going to label either of these men as racist or misogynist; the sentence refers to three people. But if the president in question is, say, Woodrow Wilson or Donald Trump, then a reader may legitimately be confused as to what is meant. But note, the confusion results whether or not the Oxford comma is used. Using an Oxford comma in no way guarantees clarity of expression.

The confusion results not because of the present or absence of a comma but because a comma is too weak to support the weight of the meaning. The sentence needs to be recast to take the semantic weight off the comma.

A more mundane, and probably more likely, example is the following pair of sentences:

Alice, Betty’s grandmother and Charles attended the wedding.

Alice, Betty’s grandmother, and Charles attended the wedding.

Both of these sentences can be confusing if one does not know the relationship between Alice and Betty. There is no confusion if one knows whether or not Alice is Betty’s grandmother. What is missing here is context, specifically who the intended reader is. If one is writing to someone who knows Alice and Betty, then the sentence is perfectly clear. If not, then the sentence or passage needs to be rewritten to make the relationship clear.

Go ahead and use the Oxford comma or not, whichever is your preference. Ideally, you should be consistent in your style choice, but consistency is no guarantee of clarity. You can’t expect your readers to remember whether or not your practice is to use the Oxford comma. Unless you’re writing the next Finnegans Wake, it’s your job as writer to make things clear for your readers.

And whichever style you chose, do not admonish others for making a different choice. It’s wrong, pedantic and annoying.

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