Category: Uncategorized

In March 2020, I noticed that one of the songs on our 2018 EP started getting a bunch of plays on Spotify. I tweeted about it, asking if anyone knew what I could do to figure out what was going on. Henning Ohlenbusch suggested that it was probably because it was put on a popular playlist, and told me that I could see this in the Spotify Artists profile. He was right.

“Places We’re Not Allowed” had been put on a “Lockdown Playlist”, alongside such other thematically titled songs as “Don’t Stand So Close to Me”. Like most people who care about musicians getting paid, I’m not a fan of Spotify, but it was a fun diversion in those early pandemic days to watch the song get plays, wonder how many it would get, and see where people were listening to it. The graphic above shows that it had gotten 2.5k listeners by April 2020 (the percentage change is presumably due to a bug coming from counting zero as 0.01). As of January 2023 it’s a couple hundred shy of 5k.

Here’s the song on Soundcloud – we put all of our music there so people don’t have to use the streaming services if they don’t want to (and here‘s the Spotify link in case you want to help us get to 5k!).

Through some luck, Les Dérailleurs managed to stay active in the pandemic playing in person as well. Two of us are volunteers with Flywheel, and we were able to rehearse in the big space in Easthampton Old Town Hall, many, many feet away from each other. We also got some drum tracks recorded in there (huge room sound!) that we plan to use in an upcoming release. And just as Flywheel was moving out of that space, we got a very nice invitation from Elizabeth MacDuffie and Mark Alan Miller to play at the 15th Meat for Tea release party in March 2021. It was a virtual event, and Mark prerecorded our segment. Here’s “Places”, which we finally released in January 2023.

My Sounds of Englishes class is taking over my life. This morning I heard my daughter say “cotton”, and I had to make a recording of her and everyone else in the room. She pronounces the second syllable with a vowel, and it sounds something like “in”. You can hear (and see in Praat) the second syllable in isolation in the video. The video also has me and another person pronouncing it with a syllabic nasal as it is pronounced in most North American varieties (I think!), and my daughter’s younger brother doing it with a vowel, and also with a [t] between the vowels, rather than a glottal stop (all of the others have glottal stop rather than [t] as is again probably the way it is said by most adult North Americans).

My daughter’s pronunciation of this type of word appears to be a feature of at least some varieties of Western Massachusetts English. I first heard about it maybe 10 years ago when a student in Sounds of Englishes pointed it out. More recently, I was at a dinner with non-linguist friends and they mentioned that one of their kids pronounces “kitten” in this Western Mass way (they are from elsewhere originally), and the other does not. Coincidentally, a couple days after that, I came across Joey Stanley’s excellent blog post on Utah English, in which this is a well known, and somewhat stigmatized, pronunciation. As far as I know, there is no stigma attached to the Western Mass vowel+nasal pronunciation.

Update Nov. 6, 2022: A 2021 paper by Eddington and Brown looks at production of vowel+nasal second syllables in words of this type in four states, and also at how these productions are perceived in terms of speaker characteristics (e.g. education, place of residence). It’s seeming increasingly like it’s everywhere, but that people think it’s a mark of their own region’s dialect.

Update Dec. 13: It seems my daughter has this vowel in other unstressed syllables too. In terms of phonetic transcription, she seems to vary between [ɨ] and [ə] in the second syllable of “salad”, but has consistent [ɨ] in “cotton”. On alternations between these vowels, see the “Rosa’s roses” paper (my daughter seems to have [ɨ] for the second syllable of both of “Rosa’s” and “roses”). Also, I just reread the first paragraph of this post and it’s a weird mix of trying to write for a general audience and for linguists. Oh well…

There are a lot of vowels in English, and they don’t seem to be comfortable in the space they are in. They are constantly moving, pushing (or pulling) each other around. The Great Vowel Shift, which happened from about 1400 to 1700, is responsible for a lot of the mess in the English spelling system, with written letters having multiple pronunciations (how many ways can “ough” be pronounced? Ought, though…), and vice versa (how many ways can you write the vowel sound in “ways”?).

Less well known are the modern vowel shifts, but the more they are studied, the more likely it seems that are happening everywhere English is spoken. William Labov first documented the Northern Cities Shift, which can make “buses” produced by someone in Chicago or Detroit sound like “bosses” to most other North Americans, and “block” sound like “black”.

The Canadian shift (see the concluding paragraph below on its current name) has largely gone in the opposite direction of the Northern Cities Shift. Because of this, when I first moved to Western Massachusetts from Canada, a potential landlord thought I was telling him I had a cot (and seemed puzzled that I thought he needed that information) when I was in fact telling him I had a cat.

A 2022 study by Matt Gardner and Rebecca Roeder provides a particularly clear picture of the Canadian shift in their Figure 8. Each of the arrows corresponds to a vowel whose pronunciation differs according to the age of the speakers (which is called a change in “apparent time”). The speakers are all from Victoria British Columbia, and range in age from 14 to 98.

The vowel from “cat” is represented by TRAP in Fig. 8. This diagram is plotting vowels according to acoustic measurements that correlate with the height and frontness of the tongue. Vowels closer to the top of the vowel plot are produced with the tongue higher in the mouth, and vowels further to the left are articulated with the tongue further to the front of the mouth. So the new pronunciation of TRAP has a lower, less front vowel.

In the Northern Cities Shift, the TRAP vowel has moved frontwards and up, towards the DRESS vowel. You can hear this in a speaker from New York City saying “bad”, or a speaker from Chicago saying any short-a word. In the Canadian shift, the vowel has gone in the other direction, towards what you might be familiar with in many Boston speakers’ pronunciation of “father”. The relatively back position of the Canadian TRAP vowel may be part of why it is used in the Canadian pronunciation of “pasta”, since it is not far from the Italian vowel in that word.

Surprisingly, another recent study, published by Monica Nesbit and James Stanford in 2021 finds that the TRAP vowel has shifted in the Canadian direction in Western Massachusetts rather than in the Northern Cities direction. This is shown in a pair of vowel plots in their Figures 5 and 6, showing the positions of the vowels for the oldest and their youngest speakers. This diagram uses BAT for the TRAP vowel. For the older speakers, it is remarkably high and front relative to DRESS, but for the younger speakers it is quite a bit lower and a bit less front.

This raises a puzzle for me: why did my young interlocutor mistake my Canadian “cat” for “cot” if we had the same TRAP vowel? My guess is that Western Mass is home to wide range of vowel systems, including those of natives of other areas with Northern Cities-style raised TRAP and fronted LOT vowels. There is probably also some regional variation within Western Mass along the I-91 corridor. Meghan Armstrong-Abrami, a linguist native to East Hartford, says she thinks people from Holyoke and Springfield often sound similar to Hartford speakers. It would also be useful to know exactly where the Canadian and Western Mass vowels are relative to each other: we can’t tell by comparing these vowel plots since they use different scales.

If you want to hear a Western Mass speaker, you can listen to a podcast of Bill Dwight, who has been called the spirit of Northampton (he was born in Holyoke). The students in my UMass “Sounds of Englishes” class and I will be listening to him and analyzing his speech, and it will interesting to see where it lands in the crowded English vowel space.

As you may have noticed in the figure caption for the Canadian shift, it has now been given the name of low-back-merger shift. The renaming has happened for two reasons. First, it’s clearly not just a Canadian thing: as well as the new Western Mass example, it’s long been known to have happened in California. Second, the new name gives information about an important characteristic of these shifts that we haven’t gotten to yet: that the lowering of the TRAP/BAT vowel is accompanied by the merging of the THOUGHT and LOT vowels (low back vowels). For Canadians, and increasing numbers of speakers in the United States, “cot” (a LOT word) and “caught” (a THOUGHT word) are pronounced the same. And in the vowel plots above from both Canada and Western Mass, you can see that the older speakers produced the THOUGHT and LOT vowels differently, and the younger ones produced them the same. The Western Mass case is particularly interesting because it seems to reverse the chronology of the change from what happened in Canada: according to Nesbit and Stanford, the lowering of the TRAP vowel happened before the the merging of the THOUGHT and LOT vowels.

Update 11/24: Just got myself a copy of Edward McClelland’s How to Speak Midwestern, which is a wonderfully accessible, informative, and fun introduction to the Northern Cities Shift and much more. I read it in one sitting, and feel like he got the linguistics right – I also learned a lot.

Update 12/3: Here is a plot of Bill Dwight’s vowels from a word list reading. As in the above plots, the labels indicate mean values for the vowel classes. He falls in between the two generations whose vowel plots are shown above, in having TRAP lowering but no THOUGHT/LOT merger. TRAP lowering first is the order Nesbit and Stanford infer from their statistical analysis of a larger set of speakers. He was born in 1955, in between the birth years of the older and younger speakers.

And here is a plot of mine: a more centralized and slightly lower TRAP than Dwight, a lower and more central BAN, and no LOT/THOUGHT contrast (or MARY/MERRY/MARRY).

The fact that my TRAP is between Dwight’s LOT and TRAP may well be related to the cot/cat confusion I experienced. It is also interesting that Dwight’s TRAP is not as low and central as the younger speakers in the Nesbitt and Stanford study. It seems likely that TRAP would only be that low and central if LOT is in the further back and higher part of the space, as it is for me and the younger Western Mass speakers.

I sent out a tweet with the slight hope of finding samples of the Martha’s Vineyard diphthong centralizing/raising that Labov studied. Edward Flemming pointed me to Labov’s 2009 Charles Homer Haskins Prize Lecture, which features audio of Donald Poole from 1961, and five other participants in Labov’s research: Jacob Schissel, NYC 1963; Larry Hawthorne, South Harlem 1967; Celeste Sullivan, South Philadelphia 1973; Jackie Garopedian Chicago 1986; Latasha Harris, West Philadelphia 2001. The talk is about what Labov learned from these people, about the nature of language, and much more.

The ACLS site currently only hosts the audio, and the slides were not available on Labov’s website, so I asked him for them. He graciously shared them with me, and you can get them from this link. He also gave me permission to make a video with the synced audio, which you can see in the above embedded YouTube video, or download as an .mp4 file from this link.

Laurel Mackenzie pointed me to a Wayback machine archive of an ACLS web page that has the complete transcript of the talk, the figures, and the audio.

Josef Fruehwald shared some memories: “[I] was lucky to be there for the talk, unforgettable…When he spoke about the little girl who would fight in school, you could hear a pin drop.”

The talk really is fantastic. My Sounds of Englishes students are now listening to the whole thing, and I’ve given them this assignment:

This video is a restropective of Bill Labov’s career, and serves as a fantastic introduction to the field he essentially created, sociolinguistics. He chooses to foreground 6 of the people he worked with as participants in his research. We get to hear each of these people speaking. Labov discusses both the importance of *what* they were saying, and aspects of linguistic structure.

For each one, please:

1. Write a short reflection of your own on what they are saying.

2. Say something about the linguistic structure of the speech.

For most of them, Labov does talk about the study he was doing, so for them, you can simply summarize. In those cases, include Labov’s discussion of social factors. For the ones that Labov does not discuss in terms of structure, you will have to make your own observations.  For each of the 12 answers (6 each), write just 2-4 sentences. Submit your response as a .pdf.

Assignment for Ling 370 Fall 2022

UMass Amherst released weekly new case counts throughout the 2021-22 school year. The following is a comparison of the UMass new case counts to those from the MassDPH for Hampshire County. Most of the UMass cases are presumably also Hampshire County cases. The DPH uses declared county of residency; although the declared residency of the UMass cases is not publicly available, it seems likely that at least 3/4 of the UMass cases appear in the Hampshire County data. The Hampshire County population is 160,830 in the 2019 census, and the UMass population is 29,300 faculty, staff and students according to campus communication from the Public Health Promotion Center (Sept. 16, 2021). The UMass population that reports Hampshire County as their residence thus likely makes up about 20% of the county population.

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To compare the case numbers from these partially overlapping populations, we can take the standard approach of relativizing the raw numbers to population size, as rates per 100,000 people. 100 new cases per week per 100K and above is considered “high” in the CDC transmission levels, and 200 per 100K is the bar used in their community levels along with hospitalization data. The above graph converts the raw weekly numbers (see the end of this post for those numbers and their source) to per capita rates using the populations from the last paragraph. The UMass rates in this graph range from a low of 34.1 per 100K for the week ending November 19th to a high of 1556.3 for February 15th.

New case rates are affected by testing, and because there was likely much more (asymptomatic) testing in the UMass population than in the general Hampshire County population, the actual relative disease prevalence was likely somewhat lower than these per capita rate comparisons would indicate. (Test positivity has the reverse bias: more testing tends to lead to a decreased percent positive.) It is therefore generally more informative to focus on changes in relative new case rates across time than to compare UMass to Hampshire County at a single point in time.

At some points, the UMass per capita rates were lower than Hampshire County – this was true from the week ending October 5 2021 through to the end of the first semester, with the exception of November 9th. (It was also true during the winter break, but the UMass population was of course much lower during this period, so these rates are artificially low). Since there was more testing at UMass, it is likely that there was in fact less disease prevalence there than in Hampshire County as a whole during the first semester after the first month. It is probably relevant that the UMass population had a much higher vaccination rate than the general Hampshire County population, that an indoor mask mandate was in place throughout the first semester, and that UMass was using wastewater surveillance testing with adaptive PCR testing.

The UMass per capita rates were also much higher at some points. This was the case at the beginning of both semesters. The first day of classes in the second semester was January 25. The UMass rate two weeks later was 1419.8 per 100K, compared to 477.5 for Hampshire County. The UMass rates approximated the Hampshire County ones in the middle of the semester, but were more than double on April 5th (348.1 vs. 121.9). The pattern of much higher UMass rates generally continued through to the end of the spring semester. It could well be relevant that the UMass Amherst indoor mask mandate was lifted March 9th.

It is not impossible that the changes in relative new case rates across time are due at least in part to changes in testing, but this seems especially unlikely to have played much of a role in the dramatic increase in the UMass cases relative to Hampshire County in the second part of the second semester. There appear to be no publicly available data that could be used to explore this possibility (see below).

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Data details

UMass data are from https://www.umass.edu/coronavirus/dashboard. They are currently unavailable at that site; the data for these graphs was copied from the presentations available during the 2021-22 school year. All of the data used for these graphs can be found in the Numbers file at this link; other formats available on request.

MassDPH data are from the downloadable dashboard data at https://www.mass.gov/info-details/covid-19-response-reporting. UMass cases seem to appear in the MassDPH data with a report date of about two days later, so the Hampshire County weeks in these graphs were chosen to end two days later, on the Thursday. The dates in the graphs are the Tuesdays.

The raw new case counts are shown below. The UMass data for April 28 (165 new cases) and May 3 (188) are the updated counts supplied the week after. They were originally given as 132 and 156 respectively. There were no UMass data released November 23 or December 28. The numbers from November 30 and January 4 were 77 and 360 respectively. They have been split over the two weeks.

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Les Dérailleurs have a new EP called 2003. Here is a pre-release version on SoundCloud, followed by the cover art by Luke Cavagnac, and the story of how this recording from 2003 is just being released now (and why it’s being released as Les Dérailleurs). It was released on the streaming services August 1 2022 (release party in Kingston Friday August 5th 3-5 Black Dog patio, Northampton TBA).

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The Story

In 2003 I had been in Northampton Massachusetts for a few years, and was really enjoying the music scene (Thurston Moore playing at a bowling alley!) but hadn’t been able to make any connections with people to play with. I decided I would make some demo recordings to try to make some progress on that.

I had just discovered one-time Buzzcock Howard Devoto’s band Magazine, and loved the way the synths sounded, so I bought a Linn guitar pedal. It’s all over the recordings. I was also aiming for a generally disco punk thing like Gang of Four. I used the drum machine in my Casio keytar for rhythm tracks to play along with that were mostly muted in the final mixes, except a bit in Work this Thing, and one from my Linn pedal that survived in Under There.

My friend and high school bandmate Grant Ethier agreed to add real drum tracks, so I packed up my Apple G3 and Korg mixing board/A-D converter and took them up to Kingston Ontario and set them up in his basement. I told him I was hoping for a sort of disco feel, and we listened to Bohannon, another obsession of mine at the time. He nailed the recordings really quickly, and I left that same day with stereo mixes of the drums (he’s a great sound engineer as well as a great drummer). Funnily, the bass drum head in the picture above is a hand me down from Grant, with the cover image from the Thirteen Engines Perpetual Motion Machine record (gone now, but I still have the Radio Shack disco ball).

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I don’t know if I wound up giving the recordings to any prospective musical partners. I met Frank Sinistra, the Atomica bass player in the picture above, around that time. He and I are still playing music together – including two of the songs in these recordings – 20 years later in Les Dérailleurs. I recently listened to them while working on some new recordings (hopefully to be released by the end of the summer), and enjoyed them, so asked Mark Miller to master them. I knew he would get what we were trying to do – I think he did a great job.

This new NSF grant is currently being processed so this information is here temporarily.

Joe Pater (PI), Gaja Jarosz (co-PI), total costs $386,226

Public summary: Languages are systems of remarkable complexity, and linguists and computer scientists have devoted considerable effort to the development of methods for representing those complex systems, as well as computational methods for learning the system of a given language. This effort is driven by the desires to better understand human cognition, and to build better language technologies. This project draws on the theories and methods of both linguistics and computer science to study the learning of word stress, the pattern of relative prominence of the syllables in a word. The stress systems of the world’s languages are relatively well described, and there are competing linguistic theories of how they are represented. This project applies learning methods from computer science to find new evidence to distinguish the competing linguistic theories. It also examines systems of language representation that have been developed in computer science and have received relatively little attention by linguists (neural networks). The research will engage undergraduate and graduate linguistics students at a public university. Linguistics has a much higher proportion of female students than computer science, and this project aims to address gender imbalance in STEM. 

From a linguistic perspective, learning stress involves learning hidden structure, parts of the representation that are not present in the observed data and that must be inferred by the learner. A given pattern of prominence over syllables is often consistent with multiple prosodic representations. The approach to hidden structure learning used in this project applies the general technique of Expectation Maximization, which in pilot work achieved good results on a standard test set. Intriguingly, many of the languages that this learner failed on in the test set are ones that are in fact cross-linguistically unattested. This project expands the set of tested languages to include more of the range of systems found cross-linguistically, and further explores the possibility that typological gaps have learning explanations. It compares hypotheses about the constraints responsible for stress placement by comparing how well they support the learning of attested systems, and whether they can help explain typological gaps. Pilot work also found indications that a neural network could learn generalizable representations of the data; the project is further testing this method. All of the software developed in this project is being made freely available, as is a database of the stress systems of the world’s languages. 

Presentation to the College of Humanities and Fine Arts’ 5 at 4 series
March 9, 2022

Pater, Joe. 2019. Generative linguistics and neural networks at 60: foundation, friction, and fusion. Language 95/1, pp. e41-e74. 

Leading questions

How is knowledge of language represented?

How is language learned?

The broader questions of how human knowledge is learned and represented have been given two general kinds of answer in cognitive science since the field emerged in the 1950s.

Birth of cognitive science

Did Frank Rosenblatt invent deep learning in 1962?

Remembering Frank Rosenblatt

1980s: Cognitive science as a field

Cognitive science became a recognized interdisciplinary field in the early 1980s, thanks partly to funding from the Sloan Foundation. Barbara Partee of Linguistics collaborated with Michael Arbib of Computer Science to secure Sloan funding to establish interdisciplinary CogSci at UMass Amherst.

The fight over the English past tense

Rumelhart and McClelland (1986) present a Perceptron-based approach to learning and representing knowledge of the English past tense (e.g. love, loved; take, took):

Scholars of language and psycholinguistics have been among the first to stress the importance of rules in describing human behavior…

We suggest that lawful behavior and judgments may be produced by a mechanism in which there is no explicit representation of the rule. Instead, we suggest that the mechanisms that process language and make judgments of grammaticality are constructed in such a way that their performance is characterizable by rules, but that the rules themselves are not written in explicit form anywhere in the mechanism.

Rumlhart and McLellan (1986) On Learning the Past Tenses of English Verbs, pp. 216-217

Twenty years ago, I began a collaboration with Alan Prince that has dominated the course of my research ever since. Alan sent me a list of comments on a paper by James McClelland and David Rumelhart. Not only had Alan identified some important flaws in their model, but pinpointed the rationale for the mechanisms that linguists and cognitive scientists had always taken for granted and that McClelland and Rumelhart were challenging — the armamentarium of lexical entries, structured representations, grammatical categories, symbol-manipulating rules, and modular organization that defined the symbol-manipulation approach to language and cognition. By pointing out the work that each of these assumptions did in explaining aspects of a single construction of language — the English past tense — Alan outlined a research program that could test the foundational assumptions of the dominant paradigm in cognitive science. 

Steven Pinker (2006) Whatever Happened to the Past Tense Debate https://escholarship.org/uc/item/0xf9q0n8

Fusion: Optimality Theory

Prince vs. Smolensky

Now: Neural networks’ third wave

Modern computers are getting remarkably good at producing and understanding human language. But do they accomplish this in the same way that humans do? To address these questions, the investigators will derive measures of the difficulty of sentence comprehension by computer systems that are based on deep-learning technology, a technology that increasingly powers applications such as automatic translation and speech recognition systems. They will then use eye-tracking technology to compare the difficulty that people experience when reading sentences that are temporarily misleading, such as “the horse raced past the barn fell,” with the difficulty encountered by the deep-learning systems. 

From Brian Dillon’s 2020 NSF award abstract https://www.nsf.gov/awardsearch/showAward?AWD_ID=2020914&HistoricalAwards=false

This project draws on the theories and methods of both linguistics and computer science to study the learning of word stress, the pattern of relative prominence of the syllables in a word. The stress systems of the world’s languages are relatively well described, and there are competing linguistic theories of how they are represented. This project applies learning methods from computer science to find new evidence to distinguish the competing linguistic theories. It also examines systems of language representation that have been developed in computer science and have received relatively little attention by linguists (neural networks).

From NSF project summary of “Representing and learning stress: Grammatical constraints and neural networks”, Joe Pater PI, Gaja Jarosz co-PI

The Shoestring Covid tracker uses the CDC community transmission levels released as part of their Feb. 12 2021 guidance for school reopening. They are based on a combination of a per capita weekly new case rate and the test positivity rate, as shown in this table:

The Shoestring Covid tracker uses just the new case rate, since the test positivity rate is often not available, and because it usually wouldn’t matter (e.g. it would be very unusual to have a “low” new case rate and the greater than 5% positivity that would change the classification to “moderate”).

These transmission rates can be used for decision making, for communities, businesses and institutions, or individuals. For example, from July 27th 2021 until Feb. 25th 2022, the CDC recommended that masks be worn indoors in communities with substantial transmission or greater, that is, with 50 or more new cases per 100K in a week. On Feb. 19th 2022, Bob Wachter, Chair of the UCSF Department of medicine, published a Twitter thread explaining his reasoning for maintaining a similar level (10 per 100K per day = 70 per week) as a threshold for indoor mask wearing, even given the changed circumstances from mid-2021. (Update 3/24: this piece from Inside Medicine supports the 50 per 100K threshold for universal indoor masking).

On Feb. 25th 2022, the CDC released new community levels and masking guidance. The new metric uses a single new case rate threshold of 200 per 100K per week, combined with the per capita rate of new Covid-19 hospital admissions, and the percentage of staffed hospital beds occupied by Covid-19 patients, to classify communities as having Low, Medium or High levels. The indoor mask recommendation applies for communities with a High level, which is reached when new cases exceed the 200 per 100K per week rate, and there are either 10 or more new admissions per 100K, or 10% or more hospital beds occupied by Covid-19 patients. This is four times the previous new case rate threshold, plus an added hospitalization rate requirement.

The CDC 2022 guidance is controversial. On the day it was released, the president of the AMA issued a statement that included the following:

But even as some jurisdictions lift masking requirements, we must grapple with the fact that millions of people in the U.S. are immunocompromised, more susceptible to severe COVID outcomes, or still too young to be eligible for the vaccine. In light of those facts, I personally will continue to wear a mask in most indoor public settings, and I urge all Americans to consider doing the same, especially in places like pharmacies, grocery stores, on public transportation…

Gerald E. Harmon MD, President American Medical Association, Feb. 25 2022, https://www.ama-assn.org/press-center/press-releases/ama-statement-cdc-covid-19-updates

The new levels are of limited value for individual decision making. For example, at the Medium level, the guidance states that “[I]f you are immunocompromised or high risk for severe disease [t]alk to your healthcare provider about whether you need to wear a mask and take other precautions (e.g., testing)”. The Medium level could occur with any new case rate. Presumably, a healthcare provider’s advice on masking should take the community transmission level into account, but the new CDC guidance provides no basis on which that could be done. In addition, individuals may want to take precautions as new case rates rise, before hospitalizations begin to increase and trigger a change in the CDC 2022 community level. Furthermore, the new CDC guidance gives no help in determining the circumstances under which individuals might want to wear masks to protect community health, as the president of the AMA urges us to do in the above statement.

Published in the Hampshire Gazette Feb. 23, 2022. This open letter was co-authored with Seth Cable, Summer Cable, Michael Stein and Susan Voss, and was also signed by 216 other people that live and work in Hampshire County, listed at the end of this letter. For further information on Covid safety in schools, please see the Urgency of Equity toolkit.

An opinion column published in the Hampshire Gazette on Feb. 17 2022 claims that “even if at one point in the pandemic it was possible to make a reasonable argument for the masking of children in school, that is no longer the case”. We disagree, since the following provides what we take to be a clearly reasonable basis for deciding to continue the school mask mandates until the levels of community transmission subside to a much lower level. We offer this as a statement of views that we believe are widespread, but are usually not made as vocally as those of the opponents of mask mandates and other public health measures.

1. It is reasonable to minimize spread in our community by using school masking. Our children interact with other members of the community, some of whom are relatively vulnerable to the effects of Covid-19 infection. By slowing spread in our schools, we are also slowing spread in our communities. The authors of the opinion column claim that “[t]here are no credible scientific data indicating that masking of children in schools has limited the spread of COVID-19”. They do not say why they do not consider the data presented by the CDC or other data to be credible. It is possible that they consider only data from randomized controlled trials (RCTs) to be credible, since they say in the next sentence that “[n]o randomized controlled trials of mandatory school masking have been carried out”. The CDC and other experts clearly consider sources of evidence other than RCTs to be useful, and it is not difficult to imagine why no RCTs have been run on school masking. For example, Institutional Review Boards may well balk at approving a study with a control group of unmasked students in a community with high transmission. 

2. It is reasonable to characterize the current local level of community transmission as high, and the risk to community health of that transmission as high as well. According to Mass-DPH data, there were 680 new cases in Hampshire County the week ending Feb. 17, which translates to a per capita rate that is over 4 times the CDC’s bar for “high transmission”, and over 8 times the bar for indoor mask wearing. Many of those cases are likely from an outbreak at UMass Amherst, which reported 456 cases in the week ending Feb. 15th. The future impact to the broader community of that outbreak is unknown. The Mass-DPH reports 37 Covid-19 deaths in the last 28 days in Hampshire County, which can reasonably be taken to indicate a high community health risk.

3. It is reasonable to minimize Covid-19 infections in our children. While most children recover quickly from Covid-19 and have mild symptoms, some wind up in hospital, and some die. That the proportion of deaths is lower than in adults, or that the number is lower than child deaths from some other cause, does not make it any less desirable to avoid those deaths. In addition, the long-term effects of these infections is unknown. There are clearly long-term effects of Covid-19 infections in general. We can only hope that childhood infections with Omicron, especially in vaccinated children, will have fewer long-term effects.

4. Mandates maximize the protection of each individual. If everyone in a room wears a mask, the amount of airborne virus is minimized, maximizing the protection for everyone. It is a less effective protection for an individual if others are maskless. This is especially true if that individual does not have the mask perfectly fitted, or occasionally takes it off to eat or drink, circumstances that seem common in a school. Wearing a mask is not just about protecting oneself, it is also for the protection of the community, including its most vulnerable members. For example, universal masking allows children who are immune compromised or otherwise at high risk for severe disease and children who have family members who are immune compromised to attend school when it would otherwise be unsafe to do so. 

5. It is reasonable to decide that real or potential negative effects of masking are outweighed by their positive benefits in minimizing Covid-19 infections. There seems to be no good evidence of negative effects of masking on child development. It is quite possible that speakers of non-mainstream varieties of English (e.g. second language speakers) may be more impacted than others by mask wearing. Real and potential negative effects should be taken into account in any decision about a mask mandate, and attempts should be made to address them when masking is in effect. But it may well be that the benefits of masks outweigh any risks.  

Signed by:

Joe Pater, Northampton resident and Professor of Linguistics, UMass Amherst

Summer Cable, Northampton resident

Seth Cable, Florence resident and UMass Faculty

Susan Voss, Northampton resident and Professor of Engineering, Smith College

Michael Stein, Northampton Resident, Ward 4 School Committee Member

Jennifer Ritz Sullivan, COVIDJustice Leader for Massachusetts with Marked By COVID  Goshen

Suzanne Theberge MPH, Northampton 

Tom Roeper, Amherst

Naomi Gerstel, Professor emerita UMass, resident Northampton

Rene Theberge, Retired Public Health Worker, Florence

Neil Kudler MD, Physician

Kirsten Leng, Resident of Northampton, Associate Professor, Women, Gender, Sexuality Studies, University of Massachusetts Amherst

Jean Potter, Doula, Northampton 

Frazer Ward, Northampton

Erica Kates, Florence, MA

Thomas Wartenberg, Professor of Philosophy, Emeritus, Mount Holyoke College

Jen Davis, Northampton

Lou Davis, Financial Planner and Advisor, Northampton

Wenona Rymond-Richmond, Northampton

Eric Poehler, Northampton

Karen Foster, Ward 2 City Councilor

Erin Kates, Resident of Florence 

Sarah Metcalf, writer, Northampton resident

Christopher Pye, teacher, Northampton resident

Andrew Kennard, Postdoctoral Fellow, UMass Amherst. Amherst resident

Tom Riddell, Northampton

Beth Adel, Teacher and resident of Northampton 

Elliot Fratkin, Professor Emeritus Smith College. Northampton

Sally Popper, Retired, Northampton

Robert Buscher, Northampton

Laura Briggs, Professor, University of Massachusetts and Northampton resident

Maureen Flannery, Northampton

Steven Goode, Northampton

Christopher Golden, parent and NOAA software engineer, Northampton

Hedy Rose, retired educator, Northampton resident

Norma Akamatsu, Social Worker, Psychotherapist, Northampton

Ian Goodman, MD, Pediatrician and Northampton Resident

Angela Silvia, CT technologist, Northampton, MA

Meg Robbins, Resident,  Northampton, MA

Traci Olsen, Northampton

Jennifer L. Nye, Northampton resident and UMass Amherst faculty member (History)

Anisa Schardl, Northampton Public Schools teacher and parent

Janet Gross, Retired

Nicolas Gross, Retired

Matthew Hine, Service Engineer (Aerospace), Northampton

John Selfridge, public school teacher, Northampton

Sara Lennox, Northampton

Jill de Villiers, Professor, Smith College, Northampton resident

Daniel Cannity, Northampton Resident

Rachel Merrell, Teacher

Cora Fernandez Anderson, Assistant Professor at Mount Holyoke College, Amherst resident

Melinda Buckwalter, Williamsburg

Emily Hamilton, Professor of history of science/medicine

Taylor Flynn, Parent & retired professor, Northampton MA

Deborah Keisch, Florence

Adele Franks, Public health physician, retired

Young Min Moon, Professor, UMass Amherst

Jude Almeida, School-Based Social Worker, Northampton resident

Karin Baker, Teacher, Northampton

Meghan  Armstrong-Abrami, Associate Professor of Hispanic Linguistics, Northampton resident

Lynn Posner Rice, Northampton

Justin Pizzoferrato, Father/self employed

Greg Lewis, Public Health Emergency Planner, Northampton

Alyssa Lovell, school-based OTR/L 

Kim Gerould, Northampton

Omar Dahi, College professor 

Kai Simon, Northampton 

Andrea Ayvazian, Pastor, Northampton resident

Jennifer Fronc, UMass Faculty; Northampton resident

Graciela Monteagudo, Senior Lecturer, UMass Amherst, Amherst Resident

Roberta Issler, Retired teacher

Cathy McNally consultant, Northampton

Rachel Wysoker, Northampton

T. Stephen Jones, MD, MPH retired public health physician 

Alison Morse, Educator

Cory Ellen Gatrall, Registered Nurse

John McNally, Attorney and grandparent, Northampton

Jeff Napolitano, Northampton, MA

Rebecca Busansky, Northampton

Rachel Yox, Amherst

Judd Gledhill, Director IT

Meg Bogdan, Parent of Northampton Public School Students

Roz Chapman, Northampton 

Lisa Weremeichik,  Northampton

Charles Dumont, MD MS Pulmonary and Critical Care physician

Tara Dumont, MD Physician

Rebecca Burwell, Professor 

Karen Sullivan, College staff, Northampton

Victoria  Dixon, Disabilities Advocate, Amherst 

Leah Greenberger, veterinarian, Belchertown MA

Annie Salsich, Self-employed 

Gabriel Phipps, Adjunct Professor

Karen Hodges, Florence

Katherine Fabel, DUA and Lecturer, UMass Amherst, Florence MA

Nykole Roche, Northampton resident w/3 kids in NPS

Garrett Warren, Amherst

Annabelle Link, Northampton

Capella Sherwood, Music teacher/ Northampton

Bertha Thorman, Northampton

Neha Kennard, Amherst

Kelly Link, Writer

Lesley Yalen, Florence, MA

David Arnold, UMass Professor of Psychological and Brain Sciences

Kristen Elde, Leeds

Lisa Harvey, Professor of Psychological & Brain Sciences at UMass, Resident of Amherst

Michael Becker, Hadley resident and UMass Faculty

Henry Rosenberg, Northampton

Andrew Gorry, Staff, UMass Amherst

Eddie (Erin) Gorry, UMass Staff, Resident of Florence, MA

Leeba Morse, Grant Writer

Jonathan Knapp, Northampton Public Schools educator

Alexis Callender, Works as faculty in Northampton, Lives in Easthampton

Megan Paik, Northampton

Mary Hoyer, Amherst resident and retired Hartford Public Schools teacher

Terianne Falcone, Writer / teacher

David Ball, Northampton

Renee Spring, Amherst Psychotherapist

Therese Kim, Social Worker

Anand Soorneedi, Amherst

Dorcas Grigg-Saito, Northampton, retired Community Health Center CEO

Erica Deighton, Retired educator, Amherst resident.

Steve Waksman, Elsie Irwin Sweeney Professor of Music, Smith College

Cornelia Daniel, Retired in Amherst

Christine Clark, Dental Hygienist 

Wendy Sutter, Amherst resident

Lijah Joyce, Amherst 

Patricia Maynard, Retired teacher. Northampton resident 

Heather Brown, Educator, Northampton 

Marissa Elkins, Attorney/City Councilor 

Mary Savarese, Retired Teacher 

Peggy Matthews-Nilsen, Amherst (Psychotherapist, Retired)

Julia Frisby, Hatfield MA

Karen Osborn, Anherst

Lisa Moos, Physical Therapist Assistant 

Patricia Duffy, Leverett

Barbara Palangi, Retired

Elizabeth Jimenez, Northampton

Sandy Oldershaw, South Hadley 

Tania Menz, Hatfield Resident, Hadley Family Physician

Kimberly Schlichting, resident of Hadley, teacher in Northampton

Elizabeth Hallstrom, resident of Amherst

Kasey Mimitz, Youth services coordinator

Scarlett Mimitz, Student

Nora Mimitz, Student

Emily Kawano, Non-profit Co-director

Jalen Michals Levy, EMT-B

Andrea Gaus, Farmer, Hatfield 

Melanie Miller, Northampton

Daniel and Angela Dee Amherst

Sandra Torrence, Teacher

Michelle Trim, Faculty at UMass Amherst/ South Hadley

Roberta Pato, Retired teacher, Northampton

Barbara Partee, Amherst resident and Professor Emerita, UMass Amherst

Norma Brunelle, Retired

Raymond R. Brunelle, Retired

Mark Brunelle, Laborer

Joanne Brunelle, Dental Assistant

Barbara Cooper, Retired teacher/librarian

Toni Brown, Hatfield

Faruk Akkus, Faculty at UMass Amherst

Felice Swados, South Hadley

Victoria Rosen, Northampton 

Felice Swados, South Hadley

Victoria Rosen, Northampton 

Jon Wynn, UMass Amherst, Associate Professor, Northampton Resident

Zelia Almeida, RN Pediatric ICU/ Belchertown 

Marci Linker, Occupational Therapist and Northampton resident

Lindsay Whittier-Liu, Northampton 

Sarah Wolfe, Northampton paralegal, resident of Belchertown

Jean Fay, Amherst educator

Lance Hodes, Pelham

Alex Robinson, Amherst

Barry Seth, Student in Amherst

Oliver Dubon, Amherst

Basil  Perkins, College Student

Ivonne Vidal, Belchertown, Attorney 

Tina Cornell, Florence 

Judith Trickey retired

Lisa  Packard, Amherst 

Bennett Lyons, Amherst, MA

Kate Matt, Shutesbury

Anne Hazzard, Amherst

Isolda Ortega-Bustamante, fundraiser; Amherst

Maureen Vezina, Belchertown 

Evelyn Trier, Mount Holyoke College Admission/ Amherst resident & parent

Katherine Kraft, retired, Amherst 

Marshall Cohen, retired, Amherst

Monroe Rabin, retired

George Collison, retired prof

Emilie Hamilton, Amherst

Stefan Gonick, Belchertown

John Hondrogen, retired and still masking in Pelham

David Gross, Pelham

Lili Kim, Amherst

Susan Watkins, Shutesbury

Amelia Vetter, Student, Amherst

Dan Levine, Business Owner

Theresa Ryan, Realtor

Jenny Miller Sechler, Psychotherapist, Northampton

Matthew Levin, retired pre-school/k teacher (Northampton)Hatfield (residence)

Robert Jackson, Amherst

Amy Dopp, Easthampton

Keri Heitner, Amherst

Anita Sarro, Retired Nurse-Attorney

Amy Hirsch, Psychologist

Emily Case, Amherst parent, Hatfield educator

Michelle McBride, UMASS Employee in Linguistics Department

Kimberly Stillwell, Speech Language Pathologist, Northampton

Delia Martinez, Retired teacher-keep masks in schools

Amy Martyn, Florence

Rebecca Leopold,Northampton, retired Amherst-Pelham HS teacher

Alicia Lopez, Teacher, Amherst

Sharon Moulton, Northampton

Louis Faassen, Architect

Scott Billups, Shutesbury

Jacqueline A. Faison, Pelham

Seth Lepore, Arts and Small Business Consultant, Easthampton, MA

Rachel Brod, Northampton

Stephanie and David Kraft, Retired

Jack Howe-Janssen, Florence

Annette Gates Teacher, Crocker Farm Elementary