|
These
resources are primarily intended for anyone wanting (or having) to
carry out music reception tests based on unguided association procedures (Chapter 6 in Music’s Meanings).
I hope that the VVA response grids
included in these resources (both the overview and the detailed
version) can give some idea of how VVAs (verbal-visual
associations, i.e. single concepts derived from your test responses)
can be organised so you can easily find out and present how much of what
respondents imagined when hearing the reception test examples you gave them. It's
obviously better if you group, say, romance together
with love
than with alphabetical neighbours like Rome, Rommel or Romania, more
useful if love is nearer
romance than
lousey, louts, low-life
or Lwenbru.
Responses in the form of unguided associations obviously need to be discretised into individual
concepts so that, for example, love in an
original response like <The
femme fatale whispers "I love
you" while waving her cigarette holder over their drinks>
and romance in <Typical Hollywood romance or
thriller from 1950s in black and white> can both be
categorised as indicative of the same (or similar) love and romance
connotations in response to the same music. That sort of classification
may be relatively unproblematic but some concepts, not
least proper names, are not so simple. How, for example, would
you categorise Lwenbru?
Does it sort under Drinks
and other comestibles because it's a beer (category 2642 in the detailed
grid), or under Germany
(for obvious reasons, 3716
in the grid) or under Advert (8231, because
your respondent refers to a TV commercial), or do you count it in all
three? There's no room here to account for "polysemic VVAs",
"context-contingent VVAs" or for any of the other problems involved,
nor to discuss possible solutions. Instead I respectfully refer readers
to pages 107-152 (esp. 125, ff.) in Ten Little Title Tunes
for a more substantial treatment of these issues.
Still,
one point may be worth making: you obviously have to think
musogenically, not just verbally, when dealing with VVAs. The word abandon, for
example, means both leave
in the lurch (e.g. an abandoned
child, 1236) and letting yourself go
(with great abandon,
no holds barred, yippee!, 105).
Those two states require very different music, as do over (as in Over the
Rainbow), over
(riding over the
prairie), over
(as in the party's over)
and over
(as in a dark cloud over the
city). Response words arise out of the music and should be
treated accordingly.
If
you are conducting a reception test as part of your graduate or
postgraduate research I think you would find good use for all the resources
listed as links at the top of this page.
If you're including a reception test in an undergraduate assignment
you'll probably get by with just the two online grids (see next) and the Excel files (see later on).
 VVA
response grids
Two response
grids, both based on the VVA taxonomy in Ten Little Title
Tunes, are included in these online resources: [1]
a Basic
VVA response grid; [2] a Detailed VVA response grid.
The original VVA taxonomy has four
levels of categorisation and most VVAs were given a suitable
four-digit code. Romance,
for example, is in category 1112
which it shares with lots
of love but not with just love (1111, could be brotherly
or parental), nor with tender
or gentle (1117). However, despite
those important musogenic nuances of love (romance is not always tender
and it is definitely unhealthy to confuse parental with
romantic love), all those related concepts do belong to the
same three-digit category 111
(love and kindness)
which is distinct from other positive three-digit categories like Joy and festivity (113) or Lightness and openness
(115) and at the
other end of the affective spectrum from 121 (Emnity and aggression)
or 125 (Darkness, encumbrance,
clandestinity and miasma).
Basic
grid
The
Basic VVA response grid
gives a good overview of the principal categories in the VVA taxonomy from Ten Little Title Tunes.
It lists the numbers and labels of all the three-digit
categories in the four-digit hierarchy. Hovering with your cursor for
second over almost any of the highlighted numbers or letters reveals
examples of concepts contained below that higher-level of abstraction
(two- or three-digits). For example, hovering over 111 (Love & kindness)
under 11 (Positive affect)
reveals the text "incl. romance, sensuality, sensitivity, tenderness"
while hovering over 121
(Emnity)
under 12 (Negative affect)
displays the message "hate, rage, aggression, implacability, etc." - a
different kettle of musical fish if ever there was.
Clicking rather
than just hovering over the sort of links just mentioned will take you
to the relevant place in the Detailed response grid where you can check
categories at the four-digit level, as explained in the paragraph
before last (here) and
next.
Detailed
grid
Both
grids are based on 8,442 VVAs collected in the early 1980s from over
600 individuals (mainly Swedes and Latin Americans) responding to ten
different film and TV title tunes. The totality of those respondents'
imagination on hearing those pieces is too complex to classify in any
semantically exhaustive way, so the Detailed
VVA response grid offered
here is presented solely as a
source for ideas. It is in
no way intended as some sort of watertight taxonomy. More
importantly, the grid deals with just an infinitesimal part of all the
VVAs imaginable in response to any other music heard by other
populations at other times and in other places (see Cultural specificity caveats). Of
course, the more the
grid presented here can help sort any issues of response classification
the better, but I have absolutely no illusion that it can do much more
than just offer a few ideas: 1% of something is, I believe,
better than 99% of nothing. Here's a concrete example of the problem.
Let's
say I've included an extract of industrial music in a reception test
and that one of the respondents writes <Dystopian robot in a
disused factory> and that I discretise the response
into five VVAs: [1] dystopian,
[2] robot,
[3] in
(yes!), [4] disused
and [5] factory.
Opening the Detailed VVA grid
and using my browser's Find
function (Cntrl-F) I uncover only two of those concepts in the grid: in
(in category 3020 - indoors
rather than out, a small but significant musogenic difference) and factory
(category 353 - Urban buildings and locations).
What do I do with the other three VVAs in the response?
Dystopian
is the hardest nut to crack. It's clearly negative (category 12 in the Basic grid
overview), with connotations of oppression and darkness (125), but dystopias are
always set in the not-so-distant future (389)
and dystopian
is also a literary and cinematic genre (84).
Frankly, I probably wouldn't worry too much about dystopia as
a genre but I would consider entering some sort of cross-reference to
the concept under Future
time. Still, I would probably end up by putting dystopia
primarily in category 1250
with darkness
and gloom.
Robot is
slightly easier. Assuming it's like Robocop or the Terminator, this
robot is a single 'male' being (211)
rather than just a machine (2660)
but it's a being that doesn't fit in any of the existing 211 (single
male) subcategories. The only solution to that problem is to
invent the new four-digit category 211S ('S' for Sci-Fi) to
include male-gendered robots, humanoids, cyborgs, extraterrestrials and
suchlike, or to open one under 201 (201S,
for example) to include all such beings, culturally gendered or not.
Finally, disused
is not too difficult to classify since it clearly belongs to category 125 (includes decaying, dirty, rotting, ill);
or, failing that, 128
(includes mess,
shambles, chaos).
To
get a general idea of the VVA taxonomy, either use the Basic grid or click here to scroll through
the detailed table.
For
ideas about classifying particular response concepts (VVAs):
[1] open the detailed
grid and use your browser's FIND and
FIND NEXT functions (Cntrl-F in Firefox) to locate occurrences of the
VVA you're looking for;
[2] check the position of any occurrence of interest in
relation to the surrounding four-, three-, two- or one-digit
categories. Then decide if its placement in the grid strikes you as
useful or not.
Tip. Just enter the
first part of a word if you don't find exactly what you're looking for.
For example, enter |embrac| rather than
|embrace|
or |embracing|
because the concept might be listed as
either one or the other.
Warning. As the
dystopian robot example shows, you should not be surprised if you don't
find the VVA you're looking for in the Detailed response grid. It's
based on responses from 0.0000001% of the world population to
0.00000001% of the music circulating in the early 1980s when the
reception tests were conducted (see Cultural
specificity caveats). In fact, you might well find you need
to construct your own grid for a very different set of musical,
cultural and social conditions. In which case I recommend the blank but
headed Excel spreadsheets explained next.
Excel DIY response grids
For
reasons already explained, you may well find it more practical to
construct your own grid for classifying VVAs. If you have only ten or
fifteen respondents you can probably do everything 'by hand' but as
soon as you have much more than that and an average of 3 or 4 VVAs per
person it's definitely worth keeping track of responses in a
spreadsheet or database. In such cases you'll need three tables. If you
don't know how to set up a spreadsheet or database, or if you want to
make life easier you can downlod three templates, either one at a time (1
2
3)
or all three packed into one ZIP
file.
Table 1
should include the unique but anonymous identity (a number will do) of
each respondent and any
demographic or personal information of relevance to your study, e.g.
age, gender, nationality, education, whether they consider themselves
to be fans of the music you're asking them to respond to (if that's
important to your study), if they're musicians (if you're interested in
that aspect) or politically active (if that's part of what you're
investigating). A spreadsheet like Table 1 is
easy
to construct using Microsoft Office Excel. Perhaps you can adapt this one to your
needs? You should start with either Table 1 or Table 2 when
you input your data. You don't need Table 1 if there's only one music
example in your reception test (see explanations for Table 2).
Table 2
should include the unique but anonymous identity of each respondent and
the identity of each
example you're testing (if there's more than one). It should also
contain the complete original answer given for each music example by
each respondent. Maybe this
table will be useful for that purpose. No interpretation is
required on your part to input data into Tables 1 and 2. You'll need
both Tables 1 and 2 if you have more than one or two examples to save
yourself the trouble of re-entering demographic information for each
respondent for each music example. If you only have one or two examples
you can include all the demographic and personal data in Table 2 and
skip Table 1.
Table 3
should include the unique number identity of each respondent, the
identity of each
example you're testing (if you're testing more than one) and each
single VVA that you extract from the complete original answers
collected in Table 2. This
Excel table can house that data. Since, as already shown,
you would probably want romance
to sort under the same category as love
rather than with its alphabetical neighbours Roman and Romania, you'll
need to number your categories so you can, using Excel's column sorting
facility (top right in Excel), sort the data by category code so as to
see at a
glance how much of what (love
and romance,
for example) was imagined in conjunction with which tune by which
respondents.
Tips
-
If you're unsure
about how to discretise complete responses into single VVAs, read pp.
122-147 in Ten Little Title Tunes
and/or check the VVA grids as suggested above.
-
When entering
respondent IDs, tune IDs and category codes into Table 3, and if you're
using numbers, start each code with a letter (e.g. |R01| for respondent
#1, |C1234| for category 1234, |T1| for tune #1) so that
Excel doesn't treat them as numbers to be added up or averaged.
-
If you have more
than 9 respondents or songs, put a zero in front of numbers under 10 so
that Excel can sort your data in the right order, or else 2 will be listed
after 19 whereas 02 will be in the right place. If you have more than
99 respondents,
you'll need to number the ones under 100 with one or two leading zeros
(e.g. 001, 002..., 010, 011..., 099, 100, etc.).
- You
can adapt the
columns in the Excel files according to your own needs. Of course,
delete any template data I've included by way of example.
-
It's quite a good
idea, if you want to keep column labels at the top of your Excel
spreadsheets, to preceed each label with an exclamation mark because
|!| sorts alphabetically before anything you can produce on
your keyboard except for Space.
-
Make good use of
the column indexing facility in Excel. Remember that you can sort on
one column, say on VVAs, to get data into that order then sort on
another, say Category number, to produce a listing in order of
VVA category with each individual VVA in alphabetical order
inside each category.
Cultural
specificity caveats
The
resources presented here are largely based on a very limited and
specific set of cultural circumstances: the imagination
of 562 Scandinavians aged 15-60 and 45 Latin Americans aged
mainly 20-30, male and female, mostly interested in music, and
responding, in the early to mid 1980s, to ten extracts of stylistically
mainstream title themes from principally UK or US film or TV
circulating in those media at various times between 1951 and
1985. Such a high degree of cultural specificity
implies the following.
- Historical
location categories 387 and
388 (recent
history and today/modern),
altered here to fit the year 2010, will be in constant need of
adjustment. Obviously, in 1983 or 1984 the 1970s were
recent and the 1980s up-to-date, today and modern.
- Geographical categories
37
(location) and 87
(production location) are subdivided quite
ethnocentrically due to the specificity of the musical and/or
audiovisual material on
which the grid is based and of the respondents' own cultural
environment.
- The
under-respresentation of women in the material is indicative of the
responses collected
and of the sort of audiovisual production imagined in conjunction with
the ten test pieces. This imbalance is discussed under the
heading Gender
and ideology on pages 666-679 in Ten
Little Title Tunes.
- Since
the music examples used in the reception test were related to moving
images and since subjects were explicitly asked to include visual
elements in their responses, it is possible that the VVAs at the base
of the materials presented here have more of a visual than,
say, auditory, tactile, spatial or kinetic bias. The epistemological
and methodological reasons for such visual bias are set out on pp.
108-110 in Ten Little Title Tunes
and on pp. 83-100 in Kojak - 50 Seconds of TV Music.
Moreover,
remembering that it took a large team of well-financed experts a good
decade to come up with the UNICODE system of international character
encoding for computers, it would be absurd to think that a single
individual with a full-time job could come up with an interculturally
viable taxonomy for every imaginable visual-verbal response to music.
That's why I urge those interested in classifying reception test responses from unguided association procedures to either adapt (add, delete, alter) the grids
provided here and here or to construct their
own (see here).
Philip
Tagg
Huddersfield (UK), 8-14 June 2010
TAXONOMY: DEFINITION
|
