Geographical Stability of Generation Frequency Norms for Russian LanguageTatyana N. Bandurka (bandurka@list.ru)012Olga P.MarchenkoPedagogical Institute of Irkutsk State University (ISU)
,
Nijnyaya Naberejnaya, 6 Irkutsk, 664013RussiaYury G. Pavlov704709
This study was aimed to examine geographical stability of generation frequency norms for semantic categories in Russian language. Participants from three different regions of Russia carried out a standard procedure for generating exemplars of 45 semantic categories. For each exemplar, overall generation frequency was calculated in each of three regions. Correlations of generation frequency data between all three regions were high providing evidence of the geographical stability of these norms in Russia.
It was shown that there are a number of variables, that affect
performance on different cognitive tasks with words. Such
variables include generation frequency ratings
(Battig and
Montague, 1969)
, typicality
(Rosh, 1975)
, imageability
(Chiarello et al., 1999)
, familiarity
(Stadthagen-Gonzalez
and Davis, 2006)
, Age-of-Acquisition
(Johnston and Barry,
2006, Tainturier et al., 2005, Hernandez, Fiebach, 2006)
,
etc. It has been shown that when these variables are not
controlled results of studies might not be valid
(Stewart,
1992)
.
In order to study categorization it is necessary first to
identify which words are used by native speakers in specific
semantic categories (like “A Bird” or “A Tree”), and to
determine generation frequency of these words within
categories. This variable was also named instance
dominance by some researches
(Mervis et al., 1976, Neely,
1977)
. First attempts to create category norms of generation
frequency were made by
Cohen at al. (1957
) in USA. Their
work was continued by Battig and Montague during the
next decade.
Battig and Montague’s (1969)
database, which
contains 56 categories of English language is the most
frequently cited database of generation frequency. The
citation search made by Van Overschelde et al. (2004) on
2002 demonstrated that it was cited over 1600 times in
papers published in more than 220 different journals.
Cross-cultural and linguistic research has revealed that the
content of categories varies across different cultures
(Yoon
et al., 2004)
and that patterns of phenomena and variable
ratings for those categories may also vary with cultural
milieu
(Medin and Atran, 2004)
. Thus using a database, that
was collected from subjects of another culture, is not always
acceptable. That is why similar studies were conducted in
other countries as well, for example in Belgium
(Storms,
2001, Ruts et al., 2004)
, France
(Bueno & Megherbi, 2009)
,
New Zealand (Marshall, Parr, 1996), Canada
(Kantner,
Lindsay, 2014)
, Israel
(Henik & Kaplan, 1988)
, China
(Yoon et al., 2004)
, Great Britain
(Hampton, Gardiner,
1983)
, Spain
(Marful et al., 2014)
, etc.
It is claimed that a number of new objects have been
created since 1969 in some categories such as vehicles etc.
Furthermore, a decline in knowledge about biological
categories during the 20th century has been observed, while
non-biological categories have experienced evolution
(Wolff et al., 1999)
. Thus, Battig and Montague’s database
was updated in 2004
(Van Overschelde et al., 2004)
.
In order to study categorization in Russia as well it was
important to create generation frequency norms for the
Russian language. Some data has been published regarding
13 categories for Russian language in year 1997
(Vysokov
& Lyusin, 1997)
, serving as a starting point for this line of
research. Considering the ongoing changes, evolution of
language content, it was important to enlarge the quantity of
categories documented. Generation frequency database for
45 semantic categories was collected for Russian language
later
(Marchenko, 2011)
. This database was collected in
Moscow. Many of selected categories were the same as in
the study by Battig and Montague. However, some new
categories were included (for example "A Domestic
Appliance", "An Organ of the Human Body").
It has been shown that some categorization phenomena
depend on human experience and can vary between urban
citizens and people who live in close contact with nature
(Medin and Atran, 2004)
. Thus, it is important to take into
account not only cultural but also experiential factors
(Winkler-Rhoades et al., 2010, Taverna et al., 2014)
.
Task that which is used to gather generation frequency
norms can be quite sensitive not only to language and to
culture aspect but to experiential factors as well
(WinklerRhoades et al., 2010). It gives an impression about concept
structure in population. Along with universality of concepts,
it can reveal some differences between subjects, who speak
the same language but live in different countries and have
different environment (Marshall, Parr, 1996), or who lives
in the same environment but belongs to different cultural
groups in the same country
(Winkler-Rhoades et al., 2010)
.
Category norms collected previously in Moscow were
shown to be reliable
(Marchenko, 2011)
. Nevertheless,
taking into account that Russia covers more than one-eighth
of the Earth`s inhabited land, some differences could be
suggested between distant regions. Thus, before making
inferences and generalizing generation frequency norms
collected in Moscow to the Russian language and the whole
country, geographical stability of these results needs to be
tested. Thus, it is important to test how similar generation
frequency data from distant regions will be. Moscow,
Irkutsk and Ekaterinburg regions were chosen for this aim
(Figure 1).
Moscow is located on a central part of Russia. The city
playing role of political, economic and cultural center in
Russia. Ekaterinburg is located on a borderline between
Europe and Asia on the eastern side of the Ural Mountains.
Wooded hills and small lakes surround it. Irkutsk is one of
the biggest cities of Eastern Siberia. The city lies on the
Angara River not far away from Lake Baikal and
surrounded by rolling hills within the taiga.
Geographical stability of psychometric data is
traditionally tested through correlations between data
collected in different regions.
The following suggestions can be made. Generation
frequency data can be accepted as geographically stable and
reliable when there are high correlations between samples
of different regions. The same level of correlations between
regions provide additional evidence for geographical
stability of generation frequency norms. Strength of
correlations can be related to distance. As cities are closer to
each other, stronger correlation levels can be observed.
Correlations between the Moscow sample and samples of
other cities could be greater than correlation between these
cities as Moscow, being a melting pot due to constant
migration processes, is more similar to other cities culturally
than these cities to each other. On the other hand,
correlation between samples from Irkutsk and Ekaterinburg
could be stronger than between samples from Moscow and
Ekaterinburg and Moscow and Irkutsk as it was suggested
that culture in Moscow is quite different from cultures of
other regions.
Method
Participants 312 students of different universities of
Moscow aged 18-23 years participated in the study as
volunteers (258 females and 54 males, m=19, SD=1.19).
One hundred seven students from Ekaterinburg aged
1823 years (51 females and 18 males, m=19, SD=.94) and one
hundred six students from Irkutsk aged 18-24 years (94
females and 12 males, m=19, SD=1.26) participated in this
study as well. According to Kruskal-Wallis test there were
no significant age differences between samples of these
three regions (Chi-square=3.779, df=2, p=.151). There were
no significant difference in proportion of male and female
participants in samples (Pearson Chi-square=2.178, df=2,
two-sided p=0.337).
All of participants were native Russian speakers.
Procedure The procedure used to gather the Russian
category norms was similar to the procedure of
Battig and
Montague (1969)
. Participants were provided with a small
notebook. The following instructions, were copied verbatim
from
Battig and Montague (1969)
, but were translated into
Russian.
“The purpose of this experiment is to find out what items or
objects people commonly give as belonging to various
categories or classes. The procedure will be as follows:
First, you will be given the name or description of a
category. Then you will be given 30 sec. to write down in
the notebook as many items included in that category as you
can, in whatever order they happen to occur to you. For
example, if you were given the category "seafood", you
might respond with such items as lobster, shrimp, clam,
oyster, herring, and so on. The words are to be written in the
notebook, using a different page for every category. When
you hear the word "Stop", you are to stop writing and go to
the beginning of the next page. You will then be given the
name of another category, and again you are to write the
names of as many members of that category as you can
think of.” The full version of the instruction can be found in
the paper by Battig and Montague of 1969.
The category names were read aloud by the experimenter.
The participants were tested in small groups to be sure that
they could work in a proper way and will not be distracted
by each other. The presentation order of the categories was
randomized and was different in different groups of
participants. The category set for this study consisted of 45
different categories such as various natural kinds ("A Fish",
"An Insect", "A Flower"), artificial kinds ("A Type of
Vehicle", "An Article of Furniture", "A Musical
Instrument"), names ("A Male`s First Name"), activity kinds
("A Profession", "A Sport"), abstract kinds ("A Unit of
Time", "A Unit of Distance"), etc.
SPSS and syntax file for Fisher’s r-to-z transformation
and for comparing Pearson correlations in SPSS
(Weaver,
Wuensch, 2013)
were used for analyses.
Results and Discussion
The same procedure of data analysis as in previous works
was used
(Battig and Montague, 1969, Storms, 2001)
. No
distinction was made between singular and plural or
masculine and feminine versions of exemplars. Legible
responses that were nonmembers were not removed from
1 MI –Correlations between Moscow and Irkutsk samples.
ME - Correlations between Moscow and Ekaterinburg samples.
IE - Correlations between Irkutsk and Ekaterinburg samples.
the list. For each exemplar, overall generation frequency
was calculated.
Correlation between cities were calculated for further
comparison. All words (even these, which were named only
one time) were used for this analysis. All Pearson`s
correlations were significant, p<.001. Correlations are
presented in Table 1.
Data can be accepted as geographically stable as
correlations between the three regions were very strong.
Pearson correlations were chosen in order to apply
Fisher’s r-to-z transformation to compare correlations.
Correlations were compared later using Fisher method for
independent samples
(Steiger, 1980. Meng et al., 1992.
Weaver, Wuensch. 2013)
. Results of that comparison is
presented in Table 2. Correlations which were significantly
(p<.05) and insignificantly different were coded and
Chisquare was applied.
There were more correlations between Irkutsk and
Ekaterinburg data which did not differ significantly from
correlations between Moscow-Ekaterinburg and
MoscowIrkutsk data (Pearson Chi-square=8.022, df=1, p<.01 - IE
and ME; Pearson Chi-square=11.756, df=1, p<.001 - IE and
MI).
Thus correlations between the Moscow sample and
samples of other cities are not stronger in general than
correlation between these cities and it can`t be suggested
that Moscow is more similar to other cities culturally than
these cities to each other. According to these data,
correlations between samples from Irkutsk and Ekaterinburg
were no stronger, than correlations between samples from
Moscow and Ekaterinburg and Moscow and Irkutsk, thus
culture in Moscow is not quite different from cultures of
other regions.
In order to test if there are connection between distance
and strength of consistency for generation frequency norms
correlations between data from cities, which are closer to
each other (like Moscow and Ekaterinburg, Ekaterinburg
and Irkutsk) were compared to correlations between cities,
which are located on a greater distance from each other (like
Moscow and Irkutsk). Frequency of correlations between
Moscow and Ekaterinburg data which did not differ
significantly from correlations between Moscow and Irkutsk
was almost the same as frequency of correlations which
were significantly different (Pearson Chi-square=.556, df=1,
p=.456). Correlations, which were significantly different,
analyzed separately from insignificant correlations.
Frequency of stronger correlations between Moscow and
Ekaterinburg in comparison to correlations between
Moscow and Irkutsk data did not differ from frequency of
weaker correlations (Pearson Chi-square=1.80, df=1,
2 MI-ME - comparison of correlation coefficients between
Moscow and Irkutsk sample with correlation coefficients between
Moscow and Ekaterinburg sample.
IE-ME - comparison of correlation coefficients between Irkutsk
and Ekaterinburg sample with correlation coefficients between
Moscow and Ekaterinburg sample.
IE-MI - comparison of correlation coefficients between Irkutsk and
Ekaterinburg sample with correlation coefficients between
Moscow and Irkutsk sample.
p=.180). There were no stronger correlations between
Ekaterinburg and Irkutsk data in comparison to correlations
between Moscow and Irkutsk data (Pearson
Chisquare=11.756, df=1, p<.001). Frequency of greater
correlation between Irkutsk and Ekaterinburg data in
comparison to correlations of Moscow and Irkutsk data
were equal to frequency of lower correlations (Pearson
Chisquare=.818, df=1, p<.366) Thus, the strength of
correlations is not related to distance. There were no
significantly stronger correlation levels for cities which are
closer to each other.
A Four-footed
Animal
A Fruit
A Girl`s first name An InsectA Kind of FoodA Kitchen Utensil A Male`s First Name
A Mammal
A MetalA Musical
Instrument
A Nonalcoholic
Beverage
A Part of the
Human Body
A Plant
A Precious Stone A ProfessionAn Organ of the Human Body A ReptileA ScienceA Sport
As correlations between the three regions are strong,
geographical stability of generation frequency norms for
Russian language can be suggested. Nevertheless, this work
was aimed to prove geographical stability and further
analyses can be continued in order to study regional
specificity of concepts with more sensitive statistic methods.
There were no evidence for connection between strength
of correlations and geographical distance. Correlations
between Moscow sample with samples from the other two
cities were not greater than between these cities. Correlation
between Ekaterinburg and Irkutsk data were no stronger
than between data from these two cities and Moscow. This
fact suggests stability of generation frequency norms in
Russian database and domination of the same culture around
the whole area of the country. Similar pattern was observed
for English language when comparison of category norms
collected in different regions of the same country conducted
(Battig and Montague, 1969)
. English and Chinese category
norms of different age groups within a culture were also
similar
(Howard, 1980, Yoon et al., 2004, Gutchess et al.,
2006)
. As norms of generation frequency are geographically
stable, the same generation frequency norms can be used for
Russian language around the whole country.
Acknowledgments
This work was supported by Russian Humanitarian
Foundation, grant “Cultural specificity and universality of
normative ratings for words and pictures” 14-36-01309.
Battig
,
W.F.
, &
Montague
,
W.E.
(
1969
).
Category norms for verbal items in 56 categories: a replication and extension of the Connecticut category norms
.
Journal of Experimental Psychology Monograph
,
80
(
3
),
1
-
45
.
Bueno
,
S.
&
Megherbi
,
H.
(
2009
).
French categorization norms for 70 semantic categories and comparison with Van Overschelde et al.'s (2004) English norms
.
Behavior Research Methods
,
41
,
1018
-
1028
.
Chiarello
,
C.
,
Shears
,
C.
,
Lund
,
K.
(
1999
).
Imageability and distributional typicality measures of nouns and verbs in contemporary English
. Behavior Research Methods, Instruments, &
Computers
,
31
(
4
),
603
-
637
.
Cohen
,
B. H.
,
Bousfield
,
W. A.
, &
Whitmarsh
,
G. A.
(
1957
).
Cultural norms for verbal items in 43 categories (Tech. Rep.No. 22)
. Storrs, CT: University of Connecticut.
Gutchess
,
A.H.
,
Yoon
,
C.
,
Luo
,
T.
,
Feinberg
,
F.
,
Hedden
,
T.
,
Jing
,
Q.
,
NisbettR.E.
(
2006
). Park D.C.
Categorical organization in free recall across culture and age
.
Gerontology
,
52
(
5
),
314
-
323
.
Hampton
,
J. A.
,
Gardiner
,
M. M.
(
1983
).
Measures of internal category structure: a correlation analyses of normative data
.
British journal of Psychology
.
74
.
491
-
516
.
Henik
,
A.
, &
Kaplan
,
L.
(
1988
).
Category content: Findings for categories in Hebrew and a comparison to findings in the US
.
Israel Journal of Psychology
,
1
,
104
-
112
.
Hernandez
,
A. E.
,
Fiebach
,
Ch. J.
(
2006
).
The brain bases of reading late learned words: Evidence from functional MRI
.
Visual Cognition
,
13
(
7
/8),
1027
-
1043
.
Howard
,
D.V.
(
1980
).
Category Norms: a Comparison of the Battig and Montague (1969) Norms with the responses of adults between the ages of 20 and 80
.
The Journal of Gerontology
,
35
(
2
),
225
-
231
.
Johnston
,
R.A.
, &
Barry
,
Ch.
(
2006
).
Age of acquisition and lexical processing
.
Visual cognition
,
13
(
7
/8),
789
-
845
.
Kantner
,
J
,
Lindsay
,
D. S.
(
2014
).
Category exemplars normed in Canada
.
Canadian Journal of Experimental
Psychology/Revue canadienne de psychologie expérimentale,
68
(
3
), Sep,
163
-
165
.
Marchenko
,
O.P.
(
2011
).
Psycholinguistic Database for Russian Language In: Kokinov
,
B.
,
Karmiloff-Smith
,
A.
,
Nersessian
,
N.J
. (eds.)
European Perspectives on Cognitive Science
. New Bulgarian University Press.
Marful
,
A.Díez
,
E.Fernandez
,
A.
(
2014
).
Normative data for the 56 categories of Battig and Montague (1969) in Spanish
.
Behavior Research Methods. Aug27
Marshall,
C. E.
,
Parr
,
W. V.
(
1996
)
New Zealand norms for a subset of Battig and Montague's (1969) categories
. New
Zealand Journal of Psychology
,
25
(
1
),
24
-
29
.
Medin
,
D.L.
, &
Atran
,
S.
(
2004
).
The native mind: biological categorization, reasoning and decision making in development across cultures
.
Psychological Review
,
111
(
4
),
960
-
983
.
Meng
,
X.
,
Rosenthal
,
R.
,
Rubin
,
D. B.
(
1992
).
Comparing correlated coefficients
.
Psychological bulletin
,
111
,
172
-
175
.
Mervis
,
C.B.
,
Catlin
,
J.
,
RoshE.
(
1976
).
Relationships among goodness-of-example, category norms and word frequency
.
Bulletin of the Psychonomic Society
,
7
,
283
-
284
.
Neely
,
J.H.
(
1977
).
Semantic priming and retrieval from lexical memory: Roles of inhibitionless spreading activation and limited-capacity attention
.
Journal of Experimental Psychology: General
,
106
,
226
-
254
.
Rosh
,
E.
(
1975
).
Cognitive representations of semantic categories
.
Journal of Experimental Psychology: General
,
104
,
192
-
233
.
Ruts
,
W.
,
De Deyne
,
S.
,
Ameel
,
E.
,
Vanpaemel
,
W.
,
Verbeemen
,
T.
,
Storms
,
G.
(
2004
).
Dutch norm data for 13 semantic categories and 338 exemplars
. Behavior Research Methods, Instruments, and Computers,
36
,
506
-
515
.
Stadthagen-Gonzalez
,
H.
, &
Davis
,
C.J.
(
2006
).
The Bristol Norms for Age of Acquisition, Imageability and Familiarity
.
Behavior Research Methods
,
38
,
598
-
605
.
Stewart
,
F.
,
Parkin
,
A. J.
,
Hunkin
,
N. M.
(
1992
).
Naming impairments following recovery from herpes simplex encephalitis: Category-specific?Quarterly Journal of Experimental Psychology
,
44A
,
261
-
284
.
Steiger
,
J.H.
(
1980
).
Tests for comparing elements of a correlation matrix
.
Psychological Bulletin
,
87
,
245
-
251
.
Storms
,
G.
(
2001
).
Flemish category norms for exemplars of 39 categories: A replication of Battig and Montague (1969) category norms
.
Psychologica Belgica
,
41
,
145
-
168
.
Tainturier
, M.-J.,
Tamminen
,
J.
,
Thierry
,
G.
(
2005
).
Age of acquisition modulates the amplitude of the P300 component in spoken word recognition
.
Neuroscience Letters
,
379
,
17
-
22
.
Taverna
,
A. S.
;
Waxman
,
S. R.
; Medin,
D. L.
,
Moscoloni
,
N.
&
Peralta
,
O. A.
(
2014
).
Naming the living things: linguistic, experiential and cultural factors in Wichí and Spanish speaking children
.
Journal of Culture and Cognition14
,
213
-
233
.
Van Overschelde
,
J. P.
,
Rawson
,
K. A.
,
Dunlosky
,
J.
(
2004
).
Category norms: An updated and expanded version of the Battig and Montague (1969) norms
.
Journal of Memory and Language
.
50
,
289
-
335
.
Vysokov
,
I.E.
, &
Lyusin
,
D.V.
(
1997
).
Internal structure of natural categories: generation frequency
.
Psichologichesky Zhurnal
,
18
(
4
),
69
-
77
.
Weaver
,
B.
,
Wuensch
,
K. L.
(
2013
).
SPSS and SAS programs for comparing Pearson correlations
and
OLS regression coefficients Behavior Research Methods45
:
880
-
895
.
Winkler-Rhoades
,
N.
,
Medin
,
D. L.
,
Waxman
,
S. R.
, &
Woodring
,
J.
,
Ross
,
N. O.
(
2010
).
Naming the animals that come to mind: Effects of culture and experience on category fluency
.
Journal of Cognition and Culture
.
10
,
205
-
220
.
Wolff
,
P.
,
Medin
,
D.L.
,
Pankratz
,
C.
(
1999
).
Evolution and devolution of folkbiological knowledge
.
Cognition
,
73
,
177
-
204
.
Yoon
,
C.
,
Feinberg
,
F.
,
Hu
,
P.
,
Gutchess
,
A.H
,
Hedden
,
T.
,
Chen
,
H.
,
Jing
,
Q.
,
Cui
,
Y.
,
Park
,
D.C.
(
2004
).
Category norms as a function of culture and age: Comparisons of item responses to 105 categories by American and Chinese adults
.
Psychology and Aging
,
19
,
379
-
393
. Matlock,
T.
(
2001
).