On Sep 21, 2019, at 1:14 PM, I (jim saxe <jim.saxe(a)gmail.com>) wrote, in response to
Rich Sbardella's question about tempos for (New England) squares vs. for contras:
My impression, though I don't have solid data to
back it up, is ...
To illustrate the difficulties of gathering solid data on such matters, here's a
report on an attempt I made back in 2012 to gather some data about tempos for contra.
I'll first give a rough description of my methodology, as best I remember it, then a
tabulation of the data, and finally some comments, including speculation about possible
flaws, limitations, and unanswered questions. I think it will be obvious that the similar
comments might apply to any proposed attempt to gather information about square dance
tempos.
* * * * * * * * * * * *
Methodology:
To gather some data on contra dance tempos, I decided to time a bunch of YouTube videos of
contra dances. I typed "contra dance" (in quotes) into the YouTube search box
and looked at the results in the order they we presented, but excluding some for various
reasons, as described below.
To measure tempos, I used a stopwatch capable of taking multiple "lap" (a/k/a
"split") times. My procedure was to start timing at the last beat of A2 in the
first repeat of the dance/tune (or the earliest place I could identify a "last beat
of A2" in videos that started partway through a dance) and then to press the
lap/split button at the last beat of A2 in various later repeats of the tune. Given the
time interval between two such corresponding beat in different rounds of a 32-bar
(64-beat) tune, it's a matter of simple arithmetic to estimate the tempo. By starting
and ending my timings at end of A2, I avoided timing the ritards that bands sometimes play
near the end of B2 on the last round of a dance. I also avoided dealing with the question
of whether bands really play the first beat of A1 just one beat-time after the last beat
of a four-beat intro.
Because I wanted to get accurate tempos despite inevitable slight inaccuracies in the
timing of my button pushes, and because I wanted to investigate whether bands tend to
speed up or slow down over the course of dance, I excluded short videos. In particular, I
didn't include any video where I couldn't time an interval of at least 10 x 32
bars. If I recall correctly, I also excluded videos of total length under seven minutes.
As a result many of my timing go from the middle of the very first round of a dance to the
middle of the very last round.
There were a few other videos I exclude besides ones that I decided were too short. I
don't have a complete record of the reasons, but I think there were some that had cuts
instead of being recorded in a continuous take, and there was at least one and maybe more
where the sound quality and/pr the nature of the music was such that I couldn't feel
confident of taking accurate timings. If I came across something like an hour-long
documentary about some festival or dance camp, I would not have bothered listening to the
whole thing on the chance that it would include a 10+-round continuous segment of a dance.
I may also have excluded additional videos from Concord, MA, after including five of
them.
* * * * * * * * * * * *
Tabulation of timings:
I timed a total of 40 contra dane videos before I ran out of steam. I list the reuslts
below in increasing order of averqge tempo. Each line of the list has the form:
AV_TEMP (START_TEMO, END_TEMP) YT_ID LOCATION; STAFF
where
AV_TEMP is the average tempo over the full interval timed
(at least 10 x 32 bars)
START_TEMP is the average tempo of the first 4 x 32 bars timed
END_TEMP is the average tempo of the last 4 x 32 bars timed
YT_ID identifies the YouTube video. Prepending
"https://www.youtube.com/watch?v=" will give the full URL.
Note, however, that some videos may have become unavailable
since 2012.
LOC identifies the city (if known to me) and state or province
where the event in the video occurred. It occasionally also
includes a parenthesized note identifying a special event.
STAFF identifies the band and caller (if known to me)
111.2 (112.4, 110.1) 8_x0P1q3Ef8 New Bern, NC; Core Sounds w/ Margie Misenheimer (sp?)
112.2 (112.1, 112.3) 7NKP-7axG0A Pasadena, CA; Perpetual e-Motion w/ Susan Michaels
112.5 (106.3, 118.1) OktHlZjB1h0 Beaufort, NC; Spalding(s)/Trobley(s)/Edwards w/ Margie
Meisenheimer (sp?)
113.0 (112.0, 113.6) uj5Q3vi9aWI Glen Echo, MD; Elixir w/ Nils Fredland
113.9 [113.1, 113.5] I4bqYv5md4k Pikesville, MD (advanced session); Taylor among the
Devils w/ Gaye Fifer
114.1 (112.0, 115.0) whWbNuiEPlc White Springs?, FL (FL Folk Festival); ??? w/ Andy Kane
114.1 (114.4, 113.9) -dkbaXztbKc Carrboro, NC; Swallowtail w/ George Marshall
114.4 (113.1, 115.3) NyUZ-UpliBI Greenfield, MA (8-hour dance 11/11/2007); Crowfoot w/
???
114.4 (113.5, 115.3) PLPo55jseX0 Carrboro, NC; The Elftones w/ ???
114.8 (115.7, 113.8) _1Pm_1ooEVM Saratoga Springs, NY; Flurry Festival Orchestra with
Quena Crain
115.1 (116.5, 114.0) f6ax6pgtcNc Greenfield, MA (techno-live); Perpetual e-Motion/Double
Apex/?DJ Improper w/ Nils Fredland
115.1 (113.8, 116.1) AbLQpc_I2gY Portland, OR; Calico w/ Tim Gojio
116.0 (116.4, 115.4) 6YJBNKZRDs4 Montpelier, VT; Patton/Hazzard-Watkins/Vallimont w/ Will
Mentor
116.0 (114.3, 117.4) VqNXvwL9FpE Santa Barbara, CA (after Harvest Moon); Notorious w/ Sue
Rosen
116.4 (114.7, 118.7) iObycSCwHnM Austin, TX (flash mob); C. Peterson/N. Quiring w/ Marc
Airhart
116.7 (114.6, 119.2) vb3N0KXYq0A Lawrenceville, NJ; Rum & Onions w/ Gaye Fifer
116.8 (111.4, 122.0) -HbIOg-rHr0 Winston-Salem, NC; The McKenzies w/ MaggieJo Saylor
116.9 (115.8, 117.7) 3XsaFEPsw20 Chicago, IL; Elixir w/ Nils Fredland
117.0 (116.4, 117.2) M6ckA0cNl3Q Lenox, MA; Crowfoot w/ ???
117.1 (118.1, 117.5) vMr7HcS_orc Concord, MA; Free Raisins w/ Sue Rosen
117.4 (115.1, 119.1) 4yjarzn6CmQ Los Angeles, CA ("alternative music");
Perpetual e-Motion w/ Susan Michaels
118.1 (122.0, 114.1) 6bCn8St1di0 Nashville, TN; Contrarian Ensemble w/ Susan Kevra
118.6 (114.3, 120.4) ERdtTVWegCs Asheville, NC; Crowfoot w/ Bob Isaacs
119.7 (119.2, 120.0) gFXwALN3KEI Shepherdstown, WV; Chance McCoy (fiddle) & ??? w/
???
120.1 (119.2, 121.0) iBt7ZtqJ01s Concord, MA (New Year's Eve); ??? w/ Lisa Greenleaf
120.3 (117.4, 122.8) zPghqCfbwRI Concord, MA; ??? w/ Sue Rosen?
120.3 (118.4, 126.1) cZUtHhMis14 Rutledge, MO (Dancing Rabbit Ecovillage); Old Missouri w/
Terry Rouse
120.6 (119.3, 121.8) T-Lnvod2BV0 Santa Barbara, CA; Crowfoot w/ Jeff Spero
120.7 (117.2, 123.2) TnlJ-bzp6NA Santa Barbara, CA (after Harvest Moon); Notorious w/ Sue
Ro\
121.2 (119.5, 122.9) rUGuLeiE4vY San Luis Obispo, CA (Contra Carnivale 2011); The
Syncopaths w/ Seth Tepfer
121.9 (119.4, 125.5) R4yl39WQlhg Carrboro, NC; Appalachian Storm w/ Beth Molaro
122.4 (121.0, 124.9) H8peDGz-zkc Concord, MA; Yankee Ingenuity? w/ Tony Parkes
122.5 (122.0, 123.1) O3StARgH_fM Wyoming, OH; ??? w/ Kathy Anderson?
122.6 (121.2, 123.3) 4Xy-wfTOgj0 Concord, MA; Nor'Easter w/ Dan Pearl
122.8 (122.3, 122.1) T4h-lXHlL_A Glen Echo, MD; Frog Hammer w/ Donna Hunt
122.8 (122.1, 124.6) n-4L3h265ww Louisville, KY; Coffee Zombies w/ Susan Moffett
123.4 (123.5, 123.4) KevQxr-saFw Greenfield, MA; Perpetual e-Motion w/ Steve
Zakon-Anderson
125.4 (125.4, 125.6) _3fBPtrZ00s Brasstown, NC (winter dance week); The Monks w/ Elwood
Donnelly
125.5 (124.2, 126.0) RsvBiTfY7lI Wyoming, OH; ??? w/ Mike Boerschig?
128.5 (126.6, 128.3) McqIMuGvhAQ Toronto, ON; Rumblestrip w/ Lisa Greenleaf
* * * * * * * * * * * *
Comments:
As you can see, the average tempos (first column) range from about 111 to 128, with a
median of about 117. I believe that the difference between a tempo of 111 and 128 would
feel quite substantial to dancers. The parenthesized numbers suggest that bands tend more
often to speed up than to slow down. There are, however, several cases where they slowed
down, and even a few cases where, unless I made some kind of error, they seem to have sped
up a little and then slowed back down or vice versa, so that number in the first column
isn't intermediate between the parenthesized numbers.
Given the substantial spread of tempos and the relatively small number of videos I've
timed, it seems hard to draw strong conclusions. It's also possible that my sample is
inherently biased, for example over-representing special events and dances in larger
communities, since those may be the events most likely to have people taking videos and
posting them on YouTube.
I haven't seriously investigated possible relationships between tempo and tune types
(marches vs. jigs vs. reels), time of day/evening, geographic region, age mix of the
dancers, inclusion (or not) of squares in local mostly-contra events, the temperature and
humidity of the hall, etc.
For example, I've heard that contra tempos tend to be higher in the midwest (perhaps
due to historical influence of the regional old-time music scene) than in some other
regions. A brief skim of the tabulation above mildly suggests that that may be true, but
I don't think there's enough data there to draw that conclusion with strong
confidence, much less to accurately quantify average tempo differences between and within
regions. I think that reaching clear statistically-supported conclusions would require a
larger sample set of videos and more thought about how to ensure that the sample isn't
biased in a way that might make it seem to indicate a correlation of tempo with region
when it's really indicating something else (e.g., the existence of one very active
local videographer who likes to go to dances with bands that have a reputation for playing
fast).
Raw data about things like age demographic of particular dance communities or temperature
of particular halls on particular evenings could be hard to gather.
I also haven't investigated whether contra tempos have, on average, sped up, slowed
down, oscillated both ways, or stayed about the same over any particular period of years
(or decades), either (inter)nationally or in any locale. In such an investigation, one
might want to use old cassette recordings made by dancers, but one might not be able to
trust that playback speed (possibly on different equipment) is really the same as
recording speed.
--Jim