On Sep 21, 2019, at 1:14 PM, I (jim saxe <[email protected]>) 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
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