Jane Austen. 36. Emily Bronte. 57. Agatha Chri.rtie. 100 .... over the other names. For example, in addltion to the two mentioned above, Agatha Christie, Sherlock ...
Perceptual and Motor Skills, 1995, 81, 1331-1338. O Perceptual and Motor Skills 1995
BIAS IN THE ESTIMATED FREQUENCY OF NAMES
'
STUART J. McKELVIE Bishop's University
Summary.-Sixty-three undergraduates listened to a list of 26 names (13 famous men and 13 nonfamous women or 13 famous women and 13 nonfamous men), then judged how many men's and women's names there seemed to be. Subjects gave higher estimates for the gender that was famous, an effect size that was moderate (d=0.53). However, this effect of fame availability was not greater for famous men than for famous women as predicted from the hypothesis of a male-fame stereotype.
What is the relationship between the actual and perceived frequency of events? According to Lechelt (1971), number discrimination can be accounted for by three processes. Both "subitizing" which occurs within the imme&ate span of apprehension (less than eight items) and "counting" which occurs with more than seven items and with sufficient exposure time lead to accurate discrimination. However, when the number of events exceeds the span of apprehension and cannot be counted, perceived frequency is based on "estimating," where the judgments may be biased by nonnumerical variables. For example, subjects accurately judged number of taps to the skin when fewer than six taps were presented with higher intensity (Lechelt, 1974a); however, they underestimated with lower intensity, and the effect was exaggerated with a fast rate of presentation and with more than six taps. Judged numerosity of taps was also affected by the pattern of presentation when more than six taps were given at faster rates (Lechelt, 1974b). Although these studies show that estimated frequency was influenced by nonnurnerical physical properties of the stimulus, the effect of a cognitive variable has also been demonstrated. Nelson and Lechelt (1970) found that third-grade children accurately judged the number of dimes and aluminum slugs when less than six were flashed for 40 msec. However, as the number rose from 6 to 12, the number of dimes but not the number of slugs was increasingly overestimated by children who were socioeconomically less favored. Similarly, university students increasingly overestimated the number of dimes but not the number of slugs as the number rose from 6 to 16 (Lechelt, 1971). These results show that judged frequency is a function of value, a higher-order cognitive process (Nelson & Lechelt, 1970). Other frequency judgments also seem to be influenced by cognitive Thanks are due to Dr. Thomas M. Nelson for sug escin the span of attention theoretical f~amewotk.Reprints of chis article can be obtained k o m Euarc J. McKeMe, Department of Bishop's University, Lennoxvde, Quebec J I M 1T3, Canada. e-mail: smckelvi@ E X 2 ~ ~ p s . c a
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processes. For example, Lichtenstein, Slovic, Fischoff, Layman, and Combs (1978) found subjects correctly judged that strokes cause more deaths than chabetes but they incorrectly judged that accidents cause more deaths than strokes. T o account for such findings, Tversky and Kahneman (1973) argued that people base such frequency estimates on the ease with which events can be recalled (the availabhty heuristic). Ease of recall may be affected by various factors which, in turn, wdl influence how often the event is thought to occur. Thus, if certain events are more familiar, perhaps through publicity (Lichtenstein, et al., 1978), their frequency may be overestimated To test this hypothesis, Tversky and Kahneman (1973) invest~gatedthe effect of farnharity on judged frequency of names. Subjects heard a list with names of 19 famous women and 20 less famous men or of 19 famous men and 20 less famous women, after which they judged the relative frequency of male and female names. Because the number of names exceeded the span of apprehension and because subjects were not initially warned that frequency would be judged and therefore did not count the names, this task requires Lechelt's (1971) process of "estimating" which could be biased by the cognitive variable of fame. Indeed, 80 out of 99 subjects indicated that the gender of famous names was more frequent than the gender of less famous names. Unfortunately, Tversky and Kahneman did not ask subjects to give a precise frequency estimate of the number of male and female names. In addition, they &d not separate their results by gender of famous names. Because there is a gender stereotype that associates fame with men rather than with women (Banaji & Greenwald, 1995), it might be expected that the effect of fame on estimated frequency would be greater for famous male than for famous female names. Although there is objective evidence that men are more U e l y to reach high levels of achievement than women [93% of the entries in Who's W h o in America (1988) are men (Banaji & Greenwald, 199511, this statistic may partly reflect a male bias in c o m p h g names (McHenry, 1980, cited by Banaji and Greenwald, 1995). Banaji and Greenwald (1995) also found that, when subjects were asked to glve their first response to "a famous person," 84% produced a male name and only 16% a female name. This demonstrates an association between males and fame and, more specifically, that famous male names were easier to recall than famous female names. The present experiment was designed to measure the size of the effect of fame on estimated frequency for each gender of famous name. It was hypothesized that subjects would give a higher numerical estimate for the gender of the name that was famous than for the one that was not famous and that this effect would be stronger with famous male names than with famous female names.
ESTIMATED FREQUENCY OF NAMES: BIAS
Participants Fifty-eight (29 male, 29 female) undergraduates privately judged the fame of 124 names. From these judgments, two experimental lists were formed, 13 famous men's names plus 13 nonfamous women's names (referred to as famous men) and 13 famous women's names plus 13 nonfamous men's names (referred to as famous women). Sixty-three members of a psychology methods class were assigned randomly to the two list conditions (9 men and 23 women for famous men, and 13 men and 18 women for famous women). Their frequency estimates were obtained in two group sessions. The 52 experimental famous and nonfamous names were selected from the first set of 124 names by equating perceived fame of male names and female names. Names of 31 men and 31 women who were thought to be famous were initially obtained from various sources, e.g., Cambridge Biographical Dictionary (1990). They represented a number of categories such as politicians and leaders, e.g., Ronald Reagan, Margaret Thatcher, Bishop Desmond Tutu, and Mother Teresa, authors, e.g., Lewis Carroll and Beatrix Potter, and entertainers, e.g., Dustin Hoffman and Jane Fonda. Artificial nonfamous names were constructed to match each of the famous names on length, alliteration, and ethnic origin. For example, matches for Ronald Reagan, Margaret Thatcher, Bishop Desmond Tutu, and Mother Teresa were Wiharn Wood, Melissa Badger, Father Walter Manwela, and Lady Martha, respectively. The 31 matched sets are shown in Table 1. The 124 names were presented in one of four random orders to 58 subjects who judged whether they had heard of the person (yes or no), rated their confidence in this decision on an 8-point scale (4. Certain that you are correct in saying yes or no, to 1. Guessing), then stated what they thought the person was known for if they had answered yes. Perceived fame for each name was scored on an 8-point scale were 8 meant yes/4 and 1 meant no/4. Another point was given if subjects answered what they thought the person was known for and a final point was awarded if this answer was correct, e.g., politician. Thus, each name's subjective fame was scored from 1 (certain never heard of) to 10 (certain heard of and reason for fame correctly identified). . The 31 matched sets were inspected to find 13 sets in which perceived fame was higher for the famous than the nonfamous names and,-for each type of name, was similar for male and female names. Total perceived-fame scores for each subject were then treated with a 2 (Gender of Subject) x 2 (Fame of Name) x 2 (Gender of Name) mixed-model analysis of variance with repeated measures on the last two factors. With alpha set at .05, the
Famous Male
Male
Female
Margaret Thalcber Williarn Wood M elissa Badger 100 3 7 Indira Ghandi Ivan Boyarski Rosa Shastri 91 10 0 Golda Meir Mustafa Hussad Ruth Silverman 43 33 5 Mary Magdalene Jonathan Seligman Donna Desroisiers 76 5 2 Mother Father Walter Monwela Lndy Teresa Martha 98 2 3 Mary Baker Eddy Janet Foss Hinton Milton Burns 5 33 0 Gertrude Stein Tony Leshner Annabelle Rosenzweig 0 31 0 Margaret Anvood James Bloscovitch Elizabeth Spence 2 79 5 BealrIx Potter Donald Scarr Isabella Andrews 52 0 2 Jane Austen Frank Tennant Kathy Evans 36 7 12 Emily Bronte Harold Stevens Sarah Brink 2 2 57 Agatha Chri.rtie Bruce Brown Alice Liddell 100 0 0 Louisa May Frederik Guntar Nanc Brooks Alcort Hagan debb 26 2 1 Lody Macbeth Casper Elliot Madam Georgina 91 9 5 Florence Nightingale Cecil Nkwama Grace Finch 84 0 3 Meryll Streep Scott Stephens Angela Gorse 91 10 2 Marilyn Monroe Hugo Dean Marion McKenzie 100 3 9 Sophia Loren Pete McCoy Sylvia Rossi 91 3 10 latie Fonda Dick Tannenbautn Joan Ericsson 100 14 12 Katherine Hepburn Steven Thomas Patricia Wood 90 5 7 (continued on next page) 52 italicised names were used as stimuli (13 sets) in the present experiments.
Ronald Reagan 100 Nikjta Kruschev 62 Gamal Abdul Nassar 29 Judas Iscarior 52 BIshop Des~nond Tutzi 90 Brigham Young 34 Carl Sandberg 34 Ralph Gusrafson 19 Lewis Carroll 43 Thomas Hardy 52 Henry Fielding 29 Graham Greene 19 Hans Chr~stian Anderson 72 Sherlock Holmes 100 lVelson Mandela 97 Robert Redford 100 Charles Bronson 98 John Wayne 93 Duslin Hofinan 100 Spencer Tracy 76 Note.-The
Nonfarnous Female
1335
ESTIMATED FREQUENCY O F NAMES: BIAS TABLE 1 (CONT'D) PERCENTAGE OF 58 JUDGES ~DENTIMNG 3 1 MATCHED SETS OF FAMOUS A N D NONFAMOUS NAMESAS FAMILIAR Famous Male Douglas Fairbanks 74 Napoleon Bonaparte 97 Julius Caesar 100 Alexander Fleming 29 ]ohn D e w q 40 mile Durkheim 40 Carl Lewis 95 John Lennon 100 Mick Jagger 98 Rudolf Nureyev 43 Louis Arvzstrong 93
Nonfamous Female
Male
Donald Brett Mary Pickford 57 3 Marie Anfoinette Jean-Louis Etienne 97 10 Joan of Arc Vicfor Norman 98 16 Marie Curie Colin Foster 76 5 James Dobson Maria Montessori 26 14 Margaret Mead Hans Overmeir 59 5 Florence Curt Squires Graith-Joiner 69 5 Yoko Ono Tom Lawrence 97 3 Tina Turner Me1 Jasper 98 0 Margot Fonteyne Joseph Brozek 16 7 Ella Fifzgerald Philip Hutchinson 74 5 Mean Percentage Identdied
Female Angela Peters 2 Jzilie Lessard 9 Marie-Andrbe Lefhre 14 Janine Sauvk 3 Paula Pollini 7 Jane Jones 5 Cathy Baylor Townsend 3 Mia San 3 Fforefto Fox 0 Joy Duprk 2 Susie O'Briera 3
31 Sets 68.0 71.1 7.1 4.5 Experimental Sets (13) 86.7 88.6 6.1 5.6 Nole.-The 52 italicised names were used as stimuli (13 sets) in the present experiments.
only significant effect was fame (F,,, = 2092.44, MS,= 865.19). Other Fs were less than 1.4. The four mean scores (maximum= 130) for men and women judging male and female famous names were very similar (111.69 to 114.57) and were all greater than the corresponding mean scores for nonfamous names (23.95 to 24.55). Thus, famous names were perceived as more familiar than nonfamous names, and famous and nonfamous names were matched by gender of name for both male and female judges. Table 1 also shows the percentage of judges who recognized each name. For the 13 experimental sets, which are underlined, the mean percentage recognition was 86.7% and 88.6% for famous men and famous women, respectively, and 6.1% and 5.6% for nonfamous men and nonfamous women, respectively. These 52 names were formed into two lists of 26 containing ei-
ther 13 famous men and 13 nonfamous women (famous men) or 13 famous women and 13 nonfamous men (famous women). Procedure Participants listened as names from one of the experimental lists were read at a 4- to 5-sec. rate. Subjects then indicated if it seemed that (a) there were more men's than women's names, (b) there were more women's than men's names, or (c) that there was the same number of men's and women's names. Finally, subjects were told that there were 26 names on the list and that they should estimate how many men's names and how many women's names there seemed to be.
RESULTSA N D DISCUSSION Table 2 shows the number of subjects choosing whether men's names or women's names or neither were perceived as more frequent. A chisquared test on these numbers was significant [x,'(N = 63) = 18.451. Whereas 50% of subjects indicated that there were more men's names than women's names with famous men and nonfamous women, 61.3% indicated that there were .more women's than men's names with famous women and nonfamous men. Over-all, 59.5% of subjects chose as more frequent the gender that was famous. This percentage is lower than the 80% reported by Tversky and Kahnernan (1973), perhaps because an equal response was permitted here. Indeed, approximately 30% of subjects chose it in each conhtion. Another possibility is that the effect of fame availabhty was stronger for American students in California in the early 1970s than for Canadian students in Qukbec in the early 1990s (the present data were collected between 1991 and 1993). TABLE 2 NUMBER OF SUBJECTS J U D G I N G THE REUT~VE NUMBER OF MEN'S AND WOMEN'S NAMESI N EACH CONDITION (I'ERCENTAGES I N BRACKETS) Condirion
n
Judgment
More Men f Yo Famous Men Famous Women
32 31
16
2
50.0 6.4
More Women f Yo 6 18.8 19
61.3
Equal Menmomen
f
%
10 10
31.2 32.2
A 2 (List) x 2 (Gender of Subject) x 2 (Fame of Name) mixed-model analysis of variance with repeated measures on the last variable was conducted on the estimated frequencies of men's and of women's names. Only the effect of fame was significant (F,,,,= 15.27, MS,= 17.34). Subjects gave a higher estimate for famous names than for nonfamous names (see Table 3). The standardized effect size of this difference was d= 0.53, which is close to Cohen's (1977) "medium" guideline of 0.50.
1337
ESTIMATED FREQUENCY OF NAMES: BIAS TABLE 3 MEANESTIMATED NUMBER O F MALE A N D FEMALE NAMESIN EACHCONDITION Condition
n
Famous Names
Nonfamous Names
d
Famous Men Men Women Men and Women Famous Women Men Women Men and Women Note.-Maximum score = 26
Although the interaction between list and fame was not significant, Table 3 also shows that the effect size for famous female names (0.67) was slightly higher than the effect size for male names (0.39), which is consistent with the slightly higher percentage of subjects choosing women's over men's names for famous women's names (61.3%) than men's over women's names for famous men's names (50.0%). This trend occurred for both male and female subjects. These findings contradct the hypothesis that estimates would be affected by a male-fame stereotype which would have exaggerated the fame availabhty effect with famous men's names. Of course, it can be problematical to defend the null hypothesis, particularly if the study does not meet the requirement of a "good effort" to demonstrate an effect (Frick, 1995; Rousseau & Standmg, 1995). Ln this case, the experiment may not have had sufficient power to detect a stronger effect of fame for male names than for female names. Tversky and Kahneman (1973) presented 19 or 20 names of each gender, whereas there were only 13 here. Moreover, Table 1 shows that there was variation among the percentages of people who recognized the famous names. Some, e.g., Ronald Reagan and Margaret Thatcher, were recognized by all judges, whereas others, e.g., Lewis Carroll and Beatrix Potter, were recognized by only about half of them. An effect of gender might have occurred with more names that were all very well recognized and with more male and female subjects. It was also interesting to observe how well judges recognized the com~ l e t elist of supposedly famous names. By coincidence, four of the names were also rated for farnharity by other undergraduates (West & Stanovich, 1991). The two percentages of recognition-accuracy (saying yes) were quite similar (West and Stanovich first): Marie Curie (78, 76), Nelson Mandela (89, 97), Margaret Mead (70, 59), and Louis Armstrong (98, 93). However, in the present study, accuracy varied quite widely over the other names. For example, in addltion to the two mentioned above, Agatha Christie, Sherlock
Holmes, Robert Redford, Marilyn Monroe, Dustin Hoffman, Jane Fonda, Julius Caesar, and John Lennon were perfectly recognized. O n the other hand, fewer than 30% of the judges recognized Henry Fielding, Alexander Fleming, Gamal Abdul Nassar, Mary Baker Eddy, Graham Greene, Maria Montessori, Louisa May Alcott, and Margot Fonteyne. I was personally surprised that only 52% of undergraduates at a small liberal arts university had heard of Julius Iscariot. The latter numbers raise questions about the cultural literacy of our students. In summary, this experiment confirms Tversky and Kahneman's (1973) effect of fame availabihty on the judged frequency of male and female names and indicates that its size is moderate. It also supports Lechelt's (1971) analysis of discrimination of number, according to which estimating can be biased by cognitive variables. However, the effect of fame was not greater for famous men than for famous women with either male or female subjects. The effect of gender may have been concealed by methodological factors, but this result suggests that the male-fame stereotype may not operate with Canadian university students. REFERENCES BANAJI. M. R.. &GREEN\VALD. A. G. (1995) Implicit gender stereotyping in judgments of fame. lozrrnal of Personalify and Sonal Psychology, 68, 181-198. Cambridge Biographical Dicfionary. (1990) Cambridge, Eng.: Cambridge Univer. Press. COHEN,1. (1977) Sfa/tstical power analysts for the behavtoral sciences. (Rev. ed.) New York: Academic Press. FRICK, W. (1995) Accepting the null hypothesis. Memory G Cognition, 23, 132-138. LECHELT. E. C. (1971) Spatial numerosiz discrimination as contingent upon sensory and extrinsic €actors. Perception & Psycbop ysrcs, 10, 180-184. LECHELT, E. C. (1974a) Pulse number discrimination in tactile spatiotemporal patterns. Perceptual and Mofor Skills, 39, 815-822. LECHELT, E. C. (1974b) Stimulus intensity and spatiality in tactile temporal numerosity discrimination. Perception, 3, 297-302. LICHTENSTEIN, S., SLOVIC, P., FISCHOFF, B., LYMAN, M., &COMBS,B. (1978) Judged Frequency of lethal events. lournal of Experimenfal Psychology: Human Learning and Memory, 4 , 551-578. NELSON, T. M., &LECHELT, E. C. (1970) Socioeconomic status, value, and response to number. Perception & Psychophysics, 8, 76-80. R o u s s ~ ~ F., u , &STANDING. L. (1995) Zero effect of crowdin on arousal and performance: on 'proving' rhe null hypothesis. Perceptzral and Motor s k i l l , 81, 72-74. TVERSKY, A., &KAHNEMAN, D. (1973) Availability: a heuristic for judging frequency and probabiliry. Cognifive Psychology, 5, 207-302. WEST,R. F., &STANOVICH, K. E. (1991) The incidental acquisition of information from reading. Psychological Science, 2, 325-329.
Accepled November 20, 799J
This article has been cited by: 1. Paul K. Miller, Louise Rowe, Colum Cronin, Theodoros M. Bampouras. 2012. Heuristic Reasoning and the Observer's View: The Influence of Example-Availability on ad-hoc Frequency Judgments in Sport. Journal of Applied Sport Psychology 24, 290-302. [CrossRef] 2. Sefa Hayibor, David M. Wasieleski. 2009. Effects of the Use of the Availability Heuristic on Ethical Decision-Making in Organizations. Journal of Business Ethics 84, 151-165. [CrossRef] 3. Mario Pandelaere, Vera Hoorens. 2006. The effect of category focus at encoding on category frequency estimation strategies. Memory & Cognition 34, 28-40. [CrossRef] 4. STUART J.McKELVIE, ANDREA DRUMHELLER. 2001. THE AVAILABILITY HEURISTIC WITH FAMOUS NAMES: A REPLICATION. Perceptual and Motor Skills 92:2, 507-516. [Citation] [PDF] [PDF Plus] 5. Stuart J. McKelvie. 1997. The Availability Heuristic: Effects of Fame and Gender on the Estimated Frequency of Male and Female Names. The Journal of Social Psychology 137, 63-78. [CrossRef]