Osgood, Charles E. Probing subjective culture. Journal of Communication, 1974, 24 (1): 21-35 and 82-100. Reprinted in Charles E. Osgood and Oliver C.S. Tzeng. 1990. "Language, Meaning, and Culture, The Selected Papers of C.E. Osgood." Charles E. Osgood and Oliver C.S. Tzeng (Eds.). New York: Centennial Psychology Series.
My interpretation of Osgood’s light analogy
Intensity of light waves
1 White ----------- Grey ----------- Black 0
Wavelength is subjectively perceived as hue
0.00014 mm ---------------------------------- 0.00035 mm
violet blue green yellow orange red
Such pure colors are fully saturated. However, they are seldom encountered outside the laboratory.
Perception of colors
The human eye does not function like a machine for spectral analysis, thus a mixture of red and green light of the proper intensities appears exactly the same as spectral yellow, although it does not contain light of the wavelengths corresponding to yellow.
Primary colors
Any color sensation can be duplicated by mixing varying quantities of red, blue, and green. These colors, therefore, are known as the additive primary colors. If light of these primary colors is added together in equal intensities, the sensation of white light is produced.
Red + blue + green = white
Red + green =
yellow
For the Interested, test color mixing:
http://www.exploratorium.edu/exhibits/mix_n_match/
Osgood analogy to meaning
Center, the meaningless origin
Length of the vector @ saturation
=> degree of meaningfulness
Direction of the vector => creates a three-dimensional space
up – down @ brightness (amount of light = lumen)
ð up: WHITE and GOOD down: BLACK and BAD
left – right @ hue
ð left: RED and Hate right: BLUE and LOVE
Called immaterial traits by anthropologist
Values, feelings, and most generally meanings
Objective culture:
GNP, number of cars, frequency of suicides
It was and still is assumed by many scientists that language
determines thought. Language determines how we perceive, how we think and how we
formulate our implicit philosophies.
Overhead
1. Producing qualifiers that describe 100 nouns
100
common nouns that existed the 27 language/culture communities were selected.
Each
of the 100 subjects (in each community) was asked to give a qualifier for each
of the 100 nouns on a list.
100
(nouns) * 1 (adjective) * 100 subjects
10,000 Qualifiers were then ordered in term of
A) common ó uncommon
B)
representativeness of qualifier
The
best 50 qualifiers and their polar opposites were used for field testing
2.
Cross Cultural Field Test
Subjects of the 27
different cultures rated the same 100 common culture concepts on these 50
bipolar scales.
A.)
Psycholinguistic definition of similarity of meaning.
For each concept, all
50 bipolar scales were correlated inter-culturally.
Scales with highest correlation were treated as translation equivalent.
=> Statistically
this is a factor analysis.
B.)
Factorization (of qualifiers):
For all cultures E,
P, and A are the three main factors
Four strongest
qualifiers for each factor are used to represent this factor => Pancultural
SDs,
Example:
E- scale
nice
--------
ugly
good
--------
bad
sweet
---------
sour
helpful
---------
not helpful
Factor Analysis
· Addresses the problem of too many IVs
· Tries to minimize the number of IVs that establish factors (groups) that maximize explanation power.
Cluster Analysis
· Addresses the Problem: which IVs explain a group
· Grouping of IVs that maximize homogeneity within groups while maximizing heterogeneity between groups.
Overhead
Process
in Summary:
·
Original
10,000 qualifiers in 26 language cultures
·
Ranked
according to frequency of use (commonness) and representativeness => 50
(pairs of?) qualifiers
·
Factor
analysis => three factors: EPA dimensions
(Two
times) four qualifiers that best describe each dimension
"But
why E, P and A? The most important question today, as in the day of the
Neanderthal, about the sign of a thing are:
first,
is it good or bad for me? (is it a cute Neanderthal female or a sabertooth
tiger?);
second,
is it strong or is it weak with respect to me? (is it a sabertooth tiger or a
mouse?);
third,
is it an active or a passive thing? (is it a sabertooth tiger or merely a pool
of quicksand that I can carefully skirt?).
Survival of the
species has depend on answers to such questions (p.247)."
overhead
Semantic differential:
Qualifier (adjective) ---------- Entity (noun) ---------Qualifier (adjective)
good ----------------------------- Mother ---------------- bad
The later final product pf Charles Osgood:
Three Scales with two to three qualifiers
Evaluation: good, nice - bad, awful
Potency: big, powerful - little, powerless
Activity: fast, young, noisy - slow, old, quiet
Overhead
Heise example: Imagine yourself in a room.
Wall in front POWERFUL
Ceiling GOOD
Left QUITE things Right LIVELY things
Floor BAD
Wall in back WEAK
II. Tool using
Atlas of 620 common concepts rated by 26 language-culture communities.
2.) Examples U.S. Japanese in Table 8.5
Intercultural differences are larger than intracultural differences:
Accepting things is culturally unstable (high variance) for Japanese, but not so much for Americans.
Comparing the standardized composite scores of EPA, the concept is very similar in both cultures.
Adolescence is culturally unstable (high variance) for Americans, but not for Japanese
Comparing the standardized composite scores of EPA, the concept is very different in both cultures.
Disclaimer: The documents linked to other sources on the WWW, others than http://www2.tltc.ttu.edu/Schneider2/ and its subdirectories, do not necessarily express the views of Texas Tech University or Dr. Andreas Schneider. @Copyright 2008 Andreas Schneider