What is an individual’s personality? Identify and describe each component of the

Question

What is an individual’s personality? Identify and describe each component of the “Big Five” personality taxonomy. Which component do you believe is the most desirable for an employee to possess (in general) and why? Which component do you believe is the least desirable for an employee to possess (in general) and why? Finally, for the remaining three components, identify a particular type of team where you think each would likely be a beneficial personality trait for a team member to possess and why you believe this is the case.

Explanation / Answer

This five-factor structure has been replicated by Norman (1963), Borgatta (1964), and Digman and Takemoto-Chock (1981) in lists derived from Cattell's 35 variables. Following Norman (1963), the factors were initially labeled: (I) Extraversion or Surgency (talkative, assertive, energetic) (II) Agreeableness (good-natured, cooperative, trustful) (III) Conscientiousness (orderly, responsible, dependable) (IV) Emotional Stability versus Neuroticism (calm, not neurotic, not easily upset) 7 (V) Culture (intellectual, polished, independent-minded) These factors eventually became known as the “Big Five” (Goldberg, 1981)--a title chosen not to reflect their intrinsic greatness but to emphasize that each of these factors is extremely broad. Thus, the Big Five structure does not imply that personality differences can be reduced to only five traits. Rather, these five dimensions represent personality at the broadest level of abstraction, and each dimension summarizes a large number of distinct, more specific personality characteristics Testing the Big Five in a Comprehensive Set of English Trait Terms After a period of dormancy during the 1970s and early 1980s, research on the Big Five, and on issues of personality structure more generally, has increased dramatically since the mid-1980s. Factor structures resembling the Big Five were identified in numerous sets of variables (e.g., Botwin & D. M. Buss, 1989; Conley, 1985; DeRaad, Mulder, Kloosterman, & Hostee, 1988; Digman & Inouye, 1986; Field & Millsap, 1991; Goldberg, 1981, 1990; John, 1990; McCrae & Costa, 1985a, 1987; Peabody & Goldberg, 1989; Saucier & Goldberg, 1996b). However, a number of these studies were influenced by Cattell’s selection of variables (Block, 1995), making it important to test the comprehensiveness and generality of the Big Five in more comprehensive variable sets. To update the Allport and Odbert list and to rectify the imperfections of Cattell's reduction steps, Norman (1967) compiled an exhaustive list of personality descriptive terms, which he sorted into 75 semantic categories. Goldberg (1990; see also 1981, 1982) used this list to clarify the nature and composition of these broad factors and to test their stability and generalizability across methodological variations and data sources. Using Norman’s (1967) listing, Goldberg (1990) constructed an inventory of 1,710 trait adjectives that participants could use to rate their own personality. He then scored Norman’s semantic categories as scales and factor analyzed their intercorrelations in the self-rating data. The first five factors represented the Big Five and replicated across a variety of different methods of factor extraction and rotation. Moreover, Goldberg (1990) demonstrated that the first five factors remained virtually invariant when more than five were rotated. To ensure independence from any a priori classification, Goldberg (1990) conducted two additional studies using abbreviated sets of more common terms. In one study, Goldberg obtained self and peer ratings of 475 very common trait adjectives which he had grouped into 131 sets of “tight synonym” clusters. In four 8 samples, the five-factor structures were very similar to each other and to the structure obtained in the more comprehensive list of 1,710 terms, and the results in the self-rating data were virtually indistinguishable from those in the peer ratings. Most important, however, were the results from the search for replicable additional factors. In a more recent study, Saucier and Goldberg (1996b) selected 435 trait adjectives rated by subjects as highly familiar terms; a factor analysis of these adjectives closely replicated the Big Five. Furthermore, a thorough search for factors beyond the Big Five showed that the Big Five were the only consistently replicable factors (Saucier, 1997). Assessing the Big Five with Trait Descriptive Adjectives Goldberg (1990, 1992) distilled his extensive taxonomic findings into several published adjective lists. One of them is a 50-item instrument using the so-called “transparent format” (Goldberg, 1992), which is not used frequently for research but is excellent for instructional purposes (Pervin & John, 1997). For each factor, this measure presents 10 bipolar adjective scales (e.g., quiet-talkative) grouped together under the factor name, thus making the constructs being measured transparent to the research participants. The list used more commonly in research is the set of 100 unipolar trait descriptive adjectives (TDA). Goldberg (1992) conducted a series of factor analytic studies to develop and refine the TDA as an optimal representation of the five-factor space in English, selecting for each Big Five scale only those adjectives that uniquely defined that factor. These scales have impressively high internal consistency, and their factor structure is easily replicated.2 Another adjectival measure of the Big Five was developed by Wiggins (1995; Trapnell & Wiggins, 1990). In his 20-year program of research on the interpersonal circumplex, Wiggins (1979) has used personality trait adjectives to elaborate both the conception and the measurement of the two major dimensions of interpersonal behavior, dominance (or agency) and nurturance (or communion). Noting that the first dimension closely resembles the Extraversion factor in the Big Five, and the second dimension the Agreeableness factor, Wiggins extended his circumplex scales by adding adjective measures for the other three of the Big Five factors (Trapnell & Wiggins, 1990). The resulting Interpersonal Adjective Scales (Wiggins, 1995) have excellent reliabilities and converge well with other measures; they have been used by researchers who want to measure the specific octants of the interpersonal circle as well as the Big Five. 9 The circumplex approach has also been applied to a perennial problem in lexical research on personality factors. One important task is to spell out, with much more precision, those characteristics that fall in the fuzzy regions between the factors. Using 10 two-dimensional circumplexes, Hofstee, De Raad, and Goldberg (1992) have devised a novel empirical approach to represent the space formed by each pair of factors. This approach specifies facets that reflect various combinations of two factors. The facets differ in whether they are more closely related to one or the other factor. For example, there are two facets that reflect high Agreeableness and high Conscientiousness, but they differ in which of the two factors is given prominence. Thus, the responsibility facet represents agreeable Conscientiousness, whereas the cooperation facet represents conscientious Agreeableness (Hofstee et al., 1997). Cross-Language and Cross-Cultural Studies The results reviewed so far suggest that the Big Five structure provides a replicable representation of the major dimensions of trait description in English. The five-factor structure seems to generalize reliably across different types of samples, raters, and methodological variations when comprehensive sets of variables are factored. Generalizability across languages and cultures is another important criterion for evaluating personality taxonomies (John, Goldberg, & Angleitner, 1984). Taxonomic research in other languages and cultures can determine the usefulness of a taxonomy in other cultural contexts and test for universals and variations in the encoding of individual differences across languages and cultures (Goldberg, 1981). The existence of cultural universals would be consistent with an evolutionary interpretation of the way individual differences have become encoded as personality categories into the natural language: if the tasks most central to human survival are universal, the most important individual differences, and the terms people use to label these individual differences, would be universal as well (D. M. Buss, 1996; Hogan, 1983; see also D. M. Buss, this volume). Similarly, if cross-cultural research reveals a culturally specific dimension, variation on that dimension may be uniquely important within that culture’s particular social context (Yang & Bond, 1990). Although central from the vantage point of the lexical approach, cross-language research is difficult and expensive to conduct, and until the last decade it was quite rare. In the initial comprehensive taxonomic studies, English was the language of choice, primarily because the taxonomers were American (see John et al., 10 1984, 1988); later studies have been conducted in a broader range of languages. In this section, we review a number of issues in cross-language and cross-cultural research on personality structure: underestimates of cross-language congruence due to translation inequivalence and factor instability; rules for including trait terms; prototypic versus discrete category structures; the imposed-etic design; the combined emic-etic approach; and whether the Big Five are in fact universal. Underestimating cross-language congruence. One of the difficulties in cross-language research involves translations. Often, researchers working within their indigenous language have to translate their concepts into English to communicate their findings but not being bilinguals themselves, much slippage occurs in the translation process. For example, one wonders why “temperamental” was a definer of Extraversion in German until one realizes that the German trait was probably temperamentvoll which has nothing to do with temper but means “full of life and energy,” as in vivacious. Similarly, frizzante (translated as sparkling) was not related to brilliant intellect, but instead seems to mean something like the English word bubbly. An initial study of German-American bilinguals, which provided support for cross-language generalizability (John et al., 1984), directly addressed the issue of translation equivalence. The unique advantage of the bilingual design is that sample differences can be controlled and that translation checks can be made at the level of individual items because the same subject provides descriptions in both languages. Indeed, even after using a standardized back-translation procedure, John et al. (1984) found that several carefully made translations were inadequate (with item-translation correlations approaching zero), suggesting that mistranslations, undetected in monolingual investigations, can lead to severe underestimations of crosslanguage generality. To permit empirical estimates of factor similarity, Hofstee, De Raad, and their colleagues have used translations of terms as a way to compare factor solutions across languages. For example, Hofstee et al. (1997) identified 126 words that could be translated between English, Dutch, and German. Hofstee et al. used them to assess factor congruence coefficients among all pairs of factors in the three languages. Their findings are illuminating in that they showed substantial congruence across these three Germanic languages. With the exception of the Openness factor in Dutch and English, the pairwise congruence coefficients all exceeded .70. 11 Strangely, Hofstee et al. interpreted these levels of cross-language congruence as “disappointing” (1997, p. 27). In fact, this interpretation seems strange given that it seems to contradict Ostendorf’s own conclusions based on the direct comparisons available in his well-designed study. Thus, we have to disagree with Hofstee et al.’s pessimistic conclusions. The empirically observed congruence coefficients reported by Hofstee et al. (1997) can be interpreted only if one assumes that the translations were perfectly equivalent. Yet, Hofstee et al. note repeatedly that “few adjectives have the same precise meaning, even across these three closely related languages” (p. 24). Thus, the findings that looked “disappointing” to them must be severe underestimates of the true congruence. Moreover, it is important to note that even within each language sample, factor structures are never perfectly stable, either. What happens when we correct the cross-language congruence coefficients at least for the unreliability of the factor structures within each language? The English-German congruence coefficients now range from .84 to .93, impressive values given that they are not corrected for the imperfect translations; moreover, the correspondence for the fifth factor was .93, suggesting that the Intellect or Openness factor was defined almost identically in these two languages. The English-Dutch and German-Dutch congruence coefficients were very similar, and suggested the same conclusions: congruence was substantial for the first four factors (.88 to .97) but not the fifth (.50 to .53). In short, these reanalyses of Hofstee et al.’s data suggest that translation-based comparisons across languages are heuristically useful but should not be interpreted in terms of absolute effect sizes. These results also suggest that the fifth factor in Dutch is defined differently than in the other two languages, and explanations for this finding need to be sought.

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