Cultural Beliefs About Societal Change

Abstract

People’s beliefs about where society has come from and where it is going have personal and political consequences. Here, we conduct a detailed investigation of these beliefs through re-analyzing Kashima, Shi, et al.’s (Study 2, n = 320) data from China, Australia, and Japan. Kashima, Shi, et al. identified a “folk theory of social change” (FTSC) belief that people in society become more competent over time, but less warm and moral. Using three-mode principal component analysis, an under-utilized analytical method in psychology, we identified two additional narratives: Utopianism/Dystopianism (people becoming generally better or worse over time) and Expansion/Contraction (an increase/decrease in both positive and negative aspects of character over time). Countries differed in endorsement of these three narratives of societal change. Chinese endorsed the FTSC and Utopian narratives more than other countries, Japanese held Dystopian and Contraction narratives more than other countries, and Australians’ narratives of societal change fell between Chinese and Japanese. Those who believed in greater economic/technological development held stronger FTSC and Expansion/Contraction narratives, but not Utopianism/Dystopianism. By identifying multiple cultural narratives about societal change, this research provides insights into how people across cultures perceive their social world and their visions of the future.

Keywords

social cognition social change beliefs measurement/statistics

One of humankind’s greatest capacities is the ability to engage in mental time travel—to project into the future and the past (Suddendorf & Corballis, 2007). One aspect of mental time travel, our projections about how our group or nation changes over time, has recently been gaining attention in psychology due to its important personal and social consequences. For example, a nation’s history and future goals contribute to people’s sense of national identity (Anderson, 2006; Liu & Hilton, 2005; Reicher & Hopkins, 2001). Believing that one’s nation changes over time in meaningful (rather than chaotic) ways is associated with increased personal well-being and lower alienation (Sani, Bowe, & Herrera, 2008). Believing that society is improving over time can reduce existential anxiety (Rutjens, Van der Pligt, & Van Harreveld, 2009) and increase a sense of personal control (Rutjens, van Harreveld, & van der Pligt, 2010). In more dramatic cases, believing our group is threatened with cultural or actual extinction in the future motivates people to strengthen their group’s traditions and norms (Wohl, Branscombe, & Reysen, 2010).

These demonstrations of the importance of specific beliefs about a group’s past and future give rise to a broader research question about the more general beliefs people hold about how groups and nations change over time. One promising approach has focused on perceptions of how a nation’s typical characteristics (auto-stereotypes) change from the past to the future (Kashima et al., 2009; Kashima et al., 2011). Although such auto-stereotypes are often inaccurate (Terracciano et al., 2005), they are meaningful and consequential, such as in differentiating ingroups from neighboring or competing groups (Realo et al., 2009). Most importantly for the present research, perceived changes in a nation’s character over time have been associated with people’s support for social policies across a wide range of issues such as community building, acting on climate change, and legalizing marijuana (Bain, Hornsey, Bongiorno, & Jeffries, 2012; Bain, Hornsey, Bongiorno, Kashima, & Crimston, 2013; Kashima et al., 2009).

To assess changes in a nation’s auto-stereotypes over time, Kashima et al. (2009) used the established stereotype content dimensions of warmth, morality, and competence (Fiske, Cuddy, Glick, & Xu, 2002; Judd, James-Hawkins, Yzerbyt, & Kashima, 2005; Leach, Ellemers, & Barreto, 2007; Wojciszke, 2005). In an Australian sample, Kashima et al. (2009) identified a consistent pattern that people viewed their society as becoming more competent over time, but declining in warmth and morality. This was dubbed the “folk theory of social change” (“FTSC”). Extending these findings cross-culturally, Kashima et al. (2011) asked participants in China, Australia, and Japan to rate stereotype content dimensions for their society in the past (100 years, 20 years) and in the future (20 years, 100 years). In general, they replicated the finding of FTSC (increasing competence but decreasing warmth/morality over time) across cultures, although with some deviations. In particular, in China, warmth was not expected to decline over time, and morality was not expected to decline in the future.

In reflecting on these findings, and in particular the different pattern for Chinese, we began to ponder the question: Is there really just one narrative of social change? It is a question traditional analytical techniques cannot adequately answer. Kashima et al. (2011) used analysis of variance to compare mean ratings of warmth, morality, and competence across time points. This provides useful information, but group means could equally reflect a single shared belief about change, or mask the existence of several distinct cultural narratives about change over time. This issue is highlighted by the divergent Chinese findings in Kashima et al., where the lack of decline in warmth over time for Chinese implies that they do not hold the FTSC as strongly as other cultures. However, it is also possible that many Chinese people do hold the FTSC strongly, but some also hold a different narrative of societal change involving warmth increasing into the future, offsetting the typical FTSC effect.

To identify whether there is one or multiple narratives of societal change within and across cultures, we used an under-utilized technique in psychology—three-mode principal component analysis (e.g., Kiers & Van Mechelen, 2001; Kroonenberg, 1983) to re-analyze data from Kashima et al. (2011). However, before explaining this technique in detail and why it is uniquely suited for this task, we will first review research, mainly from outside psychology, suggesting that people may indeed hold multiple narratives of societal change.

Narratives of Societal Change

Here, we describe different beliefs about societal change that we expect to identify, based on empirical and theoretical grounds. The first pattern relates to the main finding from psychological research in this area—the “FTSC,” and the others are derived primarily from historical and philosophical sources.

Narrative 1: FTSC

As described above, the FTSC refers to the belief that people in society are becoming more competent over time, but also less warm and moral (Kashima et al., 2009, 2011), which is linked to perceptions of economic/technological development (Kashima et al., 2011). Given that this has been identified in the only empirical work in this area, it is expected to be a significant, and probably dominant, narrative about societal change.

Narrative 2: Utopianism/Dystopianism

A second narrative about societal change reflects a common historical and philosophical theme that has received little attention within psychology—utopianism (and its converse, dystopianism). Simply, a utopian view is the belief that society is getting better in all ways, and a dystopian view is that society is getting worse in all ways. These ideas provide the basis for two of what Hardin (1993) dubbed the three “great historical paradigms” (p. 23) of societal change—the idea of “progress” where society is improving (Utopianism), and “golden age” where society is on the decline (Dystopianism; the third paradigm, “Endless Cycle,” is described below). Utopianism is aligned with Enlightenment thinking, viewing society as moving closer and closer to a perfect state. In terms of stereotype content, Utopianism would be observed by a pattern where people were seen as less warm, moral, and competent in the past, and warmer, more moral, and more competent in the future. The reverse, Dystopian pattern would be represented by viewing people as warmer, more moral, and more competent in the past, and becoming less warm, moral, and competent in the future. Utopian/Dystopianism diverges from the FTSC in that competence and warmth/morality are seen to change in the same direction rather than in opposing directions. Utopianism and Dystopianism differ from each other merely in the direction of change—whether warmth, morality, and competence as a whole are seen as increasing or declining over time.

Narrative 3: Expansion/Contraction

A third narrative of societal change has also received scant attention within psychology. This is the idea that people’s capacities, both positive and negative, expand or contract in society over time. Some philosophers have pointed to how people’s capacity to enhance their “better” nature may be inescapably linked with greater capacity for its more negative aspects. This idea was captured by Nietzsche (1882/2001):

. . . what if pleasure and displeasure were so tied together that whoever wanted to have as much as possible of one must also have as much as possible of the other—that whoever wanted to learn to “jubilate up to the heavens” would also have to be prepared for “depression unto death.” (pp. 37-38)

Applied to society as a whole rather than Nietzsche’s intra-individual conception, an Expansion narrative suggests that positive and negative aspects of society will polarize—becoming more extreme in both positive and negative directions over time. An analogy can be made with wealth in society, where increasing income inequality fits an Expansion narrative—the rich become richer, the poor become poorer. In the present case, Expansion applies to a group’s stereotypical characteristics rather than wealth—over time, society as a whole is expected to exhibit greater competence and incompetence, greater warmth and coldness, and greater morality and immorality.

Although less obvious from typical Western discourses about society, people may also hold the converse view that society and its people are increasingly “shrinking” or “pulling into themselves” compared with the past. One suggestive example comes from Japan, where there is an increasing phenomenon of “hikikomori” (Furlong, 2008), where people withdraw from society for extended periods, dramatically contracting their social network with less opportunity to engage with the world in both positive or negative ways. Applied to society as a whole, a Contraction narrative suggests that in the future, people will display warmth, morality, and competence less than in the past, but at the same time will be less likely to display coldness, immorality, and incompetence—they will display less of the positive characteristics, but also less of the negative characteristics.

Narrative 4: Endless Cycle

Hardin’s (1993) third great historical paradigm is “endless cycle,” where society oscillates around a constant level with no overall progress or decline. This belief was common in pre-Christian times (Gray, 2004), and may still be held by some people today. An endless cycle pattern is non-linear; for example, people may believe morality today is much lower than in the past, but will increase into the future, or warmth may presently be at a “high-point” that was lower in the past and will decline in the future. The 400-year time span in the present study is expected extent to be long enough to identify an endless cycle narrative, or at a minimum to identify non-linearity over time in beliefs about change.

Three-Mode Principal Component Analysis

To identify whether there are multiple narratives about social change held within and across cultures, we used three-mode principal component analysis (see Kiers & Van Mechelen, 2001; Kroonenberg, 1983, 2008). Like “standard” principal component analysis, it is a descriptive technique involving a trade-off between parsimony (fewer components) and variance explained. However, it is designed for data sets that have three ways or “modes” in which data can vary, such as across participants (Mode 1), across ratings (Mode 2, for example, stereotype content items), and across contexts (Mode 3, for example, past and future time points). Thus, it is ideally suited for a deeper analysis of Kashima et al.’s (2011) data.

The strength of three-mode principal component analysis is in identifying a solution that best summarizes these relationships across all three modes of the data (participants, stereotype content, and time), and especially in identifying how the three modes interact. For example, it can identify whether some participants see warmth and competence as positively related in the past but negatively related in the future (one pattern of participant × stereotype × time relationships), whereas other participants see warmth and competence as consistently negatively related across time (a different pattern of participant × stereotype × time relationships). As this technique is relatively uncommon in psychology (but for an example, see Kroonenberg & Kashima, 1997), we will demonstrate these aspects when describing the analysis and results.

Explaining Narratives of Societal Change

In addition to identifying narratives about societal change, this research investigated social and demographic factors to help understand who holds these beliefs and why. Three factors were examined: perceptions of economic/technological development, age, and gender.

Economic/Technological Development

One of the most prominent changes over the past 200 years has been economic and technological development, and it is expected to play a great role in how society changes into the future. Thus, people’s perceptions of economic and technological development may affect their beliefs about societal change, including how it may change their nation’s character. There is already some evidence that this is the case. Perceptions of increasing competence and declining warmth/morality (FTSC) were shown to be associated with perceptions of economic and technological development (Kashima et al., 2009; Kashima et al., 2011). As the present research uses Kashima et al.’s (2011) data, we expect the same association between FTSC and development to be observed, and we examine whether development accounts for country differences in how strongly people hold the FTSC narrative.

We also propose a positive association between development perceptions and Utopianism, as public perceptions may be influenced by the belief that development implies improvement and progress. Thus, technological and economic development may be seen as indicators of movement toward a better society with better people. However, the association between economic development and improvement in society is increasingly challenged in public discourse (Gray, 2004), particularly in the context of critical contemporary issues such as climate change (Hjerpe & Linner, 2009). Hence, this association may now be relatively weak.

The Expansion/Contraction narrative also has theoretical links with economic and technological development, as greater development should lead to greater possibilities to express both positive and negative human characteristics. Economic development has been argued to have simultaneously good and bad effects on society, for instance, according to Rodrik (1998), “The world market is a source of disruption and upheaval as much as it is an opportunity for profit and economic growth” (p. 156). In technology, new social media such as Facebook provide positive opportunities to share interests with more people (enabling warmth), but also makes it easier for people to engage in online abuse and bullying (such as “trolling”), undermining warmth. Thus, people may see advances in economic and technological development as “enablers” that allow both the positive and the negative elements of society to emerge to a greater degree in the future than in the past.

Conversely, economic “contraction” (recession or depression) may be associated with a broader “societal” contraction. With fewer economic resources, people may be seen as less capable of acting in either good or bad ways. Such contraction might be observed in countries that experienced recession over recent periods (e.g., Japan) more than in countries that have continued to grow even in the face of a worldwide downturn (e.g., Australia, China).

The one pattern we do not expect to be related to development is “endless cycle.” People holding an endless cycle narrative are likely to see development as illusory, and so are unlikely to view societal change in terms of economic and technological advance.

Demographic Associations

Associations between beliefs about societal change and basic demographic variables (age, gender) were also examined. We have no strong expectations about relationships, but this analysis can provide useful information about whether particular elements of society use these narratives more than others, or whether these narratives reflect common cultural understandings held across the community in each culture. Thus, these analyses will help establish the generalizability of these beliefs about societal change within and across cultures.

Method

We re-analyzed data from Kashima et al. (2011, Study 2), obtained from 320 participants from three countries (Australia, n = 100; China, n = 126; Japan, n = 94), who completed surveys in their native languages. Participants were directed to consider what their society was like at 2 periods in the past (100 years ago, 20 years ago) and will be like at 2 periods in the future (20 years from now, 100 years from now). They rated society at each time point on characteristics reflecting stereotype content model dimensions (warmth, morality, competence; Fiske et al., 2002; Judd et al., 2005; Leach et al., 2007), balanced for valence: warmth (warm, likeable, unfriendly, insensitive), morality (honest, sincere, dishonest, untrustworthy), and competence (competent, skilled, unintelligent, disorganized). Each characteristic was rated using an 11-point scale (−5 = a lot less than now, 0 = about the same as current, and +5 = a lot more than now).

Economic/technological development was assessed using four items, rated in each past and future context, using the same scale: industrialized, technologically advanced, wealthy, and scientific. An economic/technological development index (Development) was created by computing the average score for these items at both future time points, and subtracting the average score for these items at both past time points. Thus, a higher score denotes greater development in the future compared with the past.

Additional study details can be found in Kashima et al. (2011).

Results

We performed a three-mode principal component analysis (Kroonenberg, 1983, 2008) using a specialized computer program (3WAYPACK; Kroonenberg, 2009). Eight instances of missing data (from 15,360 data points, or 0.05% of the data set) were replaced with the mean rating of all participants across all time points for the corresponding variable.

Identifying the Best Fitting Model

A three-mode scree plot was used to identify the best fitting model (Kroonenberg, 2008). This compares the relative fit of models with different numbers of components, by comparing the residual variation (error) relative to the number of components to identify the model with the best trade-off of smallest residuals with fewest components. Two models provided acceptable trade-offs: a 4 (participant) × 3 (trait) × 2 (time) solution (explaining 52% of the variation), and a 3 (participant) × 3 (trait) × 1 (time) solution (explaining 46%). For the 4 × 3 × 2 solution, the fourth participant component had no clear interpretation, and the remaining participant components were consistent with the 3 (participant) × 3 (trait) × 1 (time) solution, so the latter model was selected for investigation. As this model involves only a single time component, indicating a unidimensional structure, this shows there was insufficient evidence for an “endless cycle” or other curvilinear pattern (the 4 × 3 × 2 solution also showed little evidence of curvilinear patterns over time).

Representing Patterns

The three participant components denote three patterns in how participants associated traits with time. A common way to interpret three-mode models is to plot these trait × time patterns for each participant component (“joint biplots”; Kroonenberg, 2008, pp. 273-276), which project the traits and time points onto the same dimensional space. The dimensionality of these plots is determined by the mode with the lowest number of components (in this case, time, with its single component). This led to creating one-dimensional joint biplots relating traits and time points, with a separate plot for each of the three participant components.

We will describe the basic details of interpreting joint biplots relating traits and time points for each participant component, which are shown in Figures 1 to 3. All figures use the same scale, so loadings across figures are equivalent. We will describe how to interpret these biplots using Figure 1. The origin (center) represents the neutral scale midpoint (“the same as today”)—traits associated equally with the past and future across the sample would be located at this position. Time points are indicated by arrows (black arrows for 20 years into the past [20p] and future [20f], and gray arrows for 100 years into the past [100p] and future [100f]), with arrow length indicating how strongly the pattern of traits applies to that time point. All patterns were held more strongly at 100-year time points (gray arrows) than 20-year time points (black arrows), meaning more distal time points were seen as more extreme versions of the patterns than at proximal time points.

Figure 1.

Component 1: Folk theory of social change (all countries).

Figure 2.

Component 2: (a) Utopianism (relatively more typical for Chinese and Australians) and (b) Dystopianism (relatively more typical for Japanese).

Figure 3.

Component 3: (a) Expansion (relatively more typical for Chinese and Australians) and (b) Contraction (relatively more typical for Japanese).

The position of the traits along the continuum shows how strongly each trait was associated with each time point. Traits to the right of the continuum are associated positively with the future and negatively with the past, with the distance from the origin indicating the strength of association. The position of traits can extend beyond the arrows, as arrows represent the direction (and strength relative to other time points), and the position of the traits represents how strongly they are associated with that direction.

Traits are labeled by stereotype content dimension (W = warmth, M = morality, and C = competence) and valence (+ or −). For example, W+ is a positive warmth trait, and C− is a negative competence trait. Three traits did not correspond to their theoretical dimensions across time, so are given different codes to highlight where they diverge from expected patterns: disorganized (theoretically C−, displayed as D−), likeable (W+, displayed as L+), and insensitive (W−, displayed as I−). Discussion of these specific traits is deferred until the main analyses are described, as the analyses help explain these anomalies.¹

For each component, every participant has a participant loading, indicating how strongly their data fit the trait–time associations shown in the corresponding jointplot. Table 1 shows the average participant loading within each country on each participant mode. Stars indicate that the average loading was significantly different from zero in that country (one-sample t tests, where zero represents the overall belief that traits in the past and future are no different from today). Significant country differences in strength of loadings on each component are indicated by different subscripts in each row, for example, significant differences were found between all countries on Utopianism/Dystopianism. This information about participant loadings is used to help interpret the components.

Table 1.

Mean Participant Component Loadings for Each Culture.

	Explained variance in sample (%)	China	Australia	Japan
Folk theory of social change	27	.48***_a	.37***_b	.34***_b
Utopianism/Dystopianism	12	.22***_a	.06*_b	−.12***_c
Expansion/Contraction	7	.07*_a	.05**_a	−.04_b

Note. Stars indicate significance of single-sample t tests comparing mean co-efficient loadings with zero (representing no change). Subscripts within rows indicate differences in mean participant loadings (p < .05).

p < .05. **p < .01. ***p < .005.

Participant Component 1: FTSC

Figure 1 shows the first component of participant responses, explaining 27% of the total variance. The lines for the time points show that perceptions of the past and future were opposed, and that this pattern was stronger for the more temporally distant ratings—the more distant past and future were seen as more “extreme” versions of the near past and future.

We illustrate the correspondence between traits and time points using the morality traits. The location of the two positively valenced morality traits (M+) on the far left of the Figure 1 (aligned with the 20 and 100 years in the past) indicates that positive morality was associated much more strongly with the past than with the future. Conversely, the negatively valenced morality traits (M−) were associated with the future more than the past. This reflects a pattern of declining morality over time—moral traits (M+) were seen as more typical in the past than the future, and immoral traits (M−) were seen as more typical in the future than in the past. A similar pattern was identified for warmth (excluding anomalous indicators, L+ and I−, which were seen to change little over time). Competence showed the reverse pattern, with positive competence indicators (C+) associated more with the future than the past, and one negative competence indicator (C−) associated more with the past than the future. That is, competence was seen to be more typical in the future than in the past. The divergent negative competence indicator (D−) was associated slightly more with the future than the past.

Overall, Figure 1 reflects Kashima et al.’s (2009) FTSC, with the past associated with higher warmth/morality but lower competence, and the future associated with lower warmth/morality but higher competence. Table 1 shows that this FTSC pattern was typical across all three countries, as the average loading in each country was positive and significantly different from zero. However, Table 1 also shows that Chinese held this narrative of societal change more strongly than both Australians and Japanese.

Participant Component 2: Utopianism/Dystopianism

The second participant component explained a further 12% of the total variance (26% of the explained variance). All countries differed significantly in their average loading on this component (see Table 1). Chinese and Japanese samples showed strong orientations in opposing directions, with Australians showing relatively weaker but positive loadings.

Figure 2 shows the associations between traits and time points for this component. Although this is a single component, people with positive and negative loadings on this component have opposite associations. To aid interpretation, Figure 2(a) shows the relationship for participants with positive loadings (typically Chinese and Australians), and Figure 2(b) shows the relationship for participants with negative loadings (typically Japanese), involving “mirroring” the position of traits to reflect the negative loadings. Figure 2(a) shows that all positive traits, regardless of stereotype content dimension, were associated more with the future than the past, and all negative traits were associated more with the past than the future. This is clearly interpretable as Utopianism—a belief that people will be better in the future than the past across all stereotype content dimensions—more moral, warmer, and more competent. This was the typical pattern for Australians, and especially for Chinese.

Figure 2(b) shows the contrasting pattern, typical for Japanese, with positive traits associated more with the past than the future, and negative traits associated with the future more than the past. This is clearly interpretable as a Dystopian narrative of societal change.

Participant Component 3: Expansion/Contraction

The third participant component explained 7% of the total variance (15% of explained variance). Notably, the “anomalous” traits emerged most strongly on this component, with “disorganized,” “insensitive,” and “likeable” showing the three strongest loadings (see Note 1). This component also differed significantly across countries (see Table 1). Chinese and Australians showed positive loadings on this component (Expansion), whereas Japanese were significantly lower, trending toward Contraction. We created two figures to aid interpretation of country differences (Figures 3(a) and (b)).

Figure 3(a) shows the Expansion pattern more common for Chinese and Australians. Most traits, both positive and negative, were rated as more typical in the future than the past, with others maintained at least at similar levels as today. For example, participants associated the future with not only greater competence (C+) but also greater incompetence (C−). Figure 3(b) shows the contrasting Contraction pattern, more typical in Japan, with both positive and negative traits seen as more typical in the past than in the future.

We note that Expansion should not be confused with disagreement about how traits will change over time, such as some people believing competence/warmth/morality will increase and others that it will decrease. This would be identified in Component 2 (an increase reflected in positive participant loadings, a decrease indicated by negative participant loadings). Rather, Expansion represents a shared belief that society as a whole will exhibit both greater positive and negative traits in the future (e.g., greater warmth and greater coldness), although this need not correspond to believing every individual in society will show this pattern.

Explaining Beliefs About Societal Change

The three-mode principal component analysis identified three distinct and theoretically meaningful cultural beliefs about social change, and participant component scores indicated the extent to which people held these beliefs. However, component scores are specific to particular samples and do not lend themselves to scales that can be used in other research. Therefore, we used the original variables (after removing the three divergent variables) to create indices of each narrative of social change that can be used more easily in future research. These were related to sociological beliefs and demographic variables to further understand who holds these beliefs and why they may do so.

An FTSC index was created using the following formula: (Mean Past Warmth/Morality − Mean Past Competence) + (Mean Future Competence − Mean Future Warmth/Morality), omitting the three divergent items.² To compute past/future Warmth, Morality, and Competence scores, we subtracted the mean of the negative indicators of each dimension from the mean of its positive indicators. Higher scores represent stronger endorsement of the FTSC: rating warmth/morality as more typical than competence in the past, and competence more typical than warmth/morality in the future.

An Utopianism index was created using all items: (Mean Past Negative − Mean Past Positive) + (Mean Future Positive − Mean Future Negative). A positive (Utopian) score reflects more negative than positive characteristics in the past and more positive than negative characteristics in the future. Dystopianism is indicated by a negative score.

An Expansion index was computed using all items: (Mean All Future − Mean All Past). A positive score reflects Expansion (all characteristics across all dimensions more typical in the future than the past). A negative score represents Contraction.

Across the three samples, these three indices were highly correlated with their corresponding participant component loadings (all rs > .81) and were not strongly correlated with each other (all rs < .20). Thus, these indices capture the distinct FTSC, Utopianism, and Expansion narratives of societal change from the three-mode analysis in a more replicable way. The appendix contains the mean scores and intercorrelations of these indices for each country, along with their correlations with beliefs about economic/technological development.

To further understand these narratives of societal change, each index was regressed onto country, economic/technological development beliefs, and basic demographics (age, gender). To assess country and gender effects, effect coding was used to minimize multicollinearity (with Chinese and females as reference categories). Age and Development were mean-centered, with interaction terms created by multiplying centered indices with the effect-coded variables. Multicollinearity was within an acceptable range (all Variance Inflation Factors < 2.5).

Regressions are shown in Table 2. The betas reported for each variable relate to “average” effects across the whole sample, with the interaction terms denoting deviations from the average effect. Endorsement of FTSC was stronger for those who believed in greater economic and technological development in society over time, and this relationship was not significantly different across countries. Furthermore, after accounting for development beliefs, the country differences in FTSC endorsement (see Table 1) were no longer significant.³

Table 2.

Regressions of Social Change Indices on Background Variables.

	FTSC	Utopianism/Dystopianism	Expansion/Contraction
R ²	.25***	.14***	.17***
		β
Australian (effect-coded)	−.09	−.05	.11
Japanese (effect-coded)	.04	−.22**	−.33***
Development (centered)	.42***	.02	.18***
Australian × Development	−.09	.04	.02
Japanese × Development	.06	−.06	−.08
Age (centered)	−.02	.10	.09
Australian × Age	.01	−.18*	.02
Japanese × Age	.08	.14*	−.01
Gender (−1 = female, 1 = male)	.04	.03	−.01
Australian × Gender	−.04	.17*	−.06
Japanese × Gender	−.06	−.14*	.04

Note. FTSC = folk theory of social change index, which was calculated without the divergent items.

p < . 05. **p < .01.***p < .005.

Endorsement of Utopianism did not vary with Development, but did vary with age and gender across countries. Relationships with age were relatively stronger for Japanese, resulting in a significant positive relationship (younger Japanese endorsed Utopianism less strongly) and relatively weaker for Australians (resulting in a non-significant negative relationship). In addition, Australian women were more utopian than men, but in Japan, this relationship was significantly weaker (negative but non-significant). However, Japanese were still more dystopian than other countries after controlling for age, gender, and development.

Endorsement of Expansion was positively associated with Development. However, even after accounting for other variables, Japanese still showed lower Expansion beliefs.

Discussion

A three-mode principal component analysis has shown for the first time that people hold not one but three narratives about societal change. At the most general level, we found that people see the trajectory from the past to the future in a unidimensional way, with the distant future and past seen just as more extreme versions of the proximal future and past.

The first, and dominant, narrative of societal change is that there is a trade-off in warmth/morality and competence in society, with people becoming more competent over time but at the expense of warmth and morality. This narrative confirmed Kashima et al.’s (2009, 2011) “FTSC.” This was common across all countries, but especially pronounced in China. One way to interpret this narrative is that people are expected to become more “machine-like” over time, in that they are expected to become more competent in performing tasks but also more interpersonally cold and remote (Haslam, 2006).

This FTSC narrative was strongly related to perceptions of economic/technological development, which could be interpreted as a belief that people are expected to become more machine-like because they are becoming more immersed in, and reliant on, machines and technology. Development fully accounted for country differences in endorsement of FTSC, indicating that these country differences arose from differing experiences of development. China’s recent past of rapid economic and technological development contrasts with Japan’s economic stagnation (with Australia in-between), mirroring their differing endorsement of FTSC. However, one implication is that endorsement of this narrative may change with a country’s economic fortunes. Parallels have been drawn between China now and Japan during its economic boom (Ueda, 2011), suggesting that when China’s growth slows, it may also weaken the perception of a competence—warmth/morality trade-off in society.

The second narrative of societal change, Utopianism/Dystopianism, reflects the view that a nation’s warmth, morality, and competence are becoming better (or declining) over time. Endorsement of utopianism was strongest in China, whereas Japanese typically endorsed a more pessimistic dystopian narrative. Unlike FTSC, Utopianism/Dystopianism was not related to perceptions of development but did vary with gender and age in country-specific ways, with older Japanese and Australian women being more utopian. These country-specific effects suggest the need for a deeper investigation into the cultural and individual factors that contribute to optimistic or pessimistic views about societal change.

Over and above demographic factors, Japanese were still relatively more dystopian. As Utopianism/Dystopianism involves rosy/dark views of societal change, they may be related to optimism and pessimism, which are respectively linked to extraversion and neuroticism personality traits (Marshall, Wortman, Kusulas, Hervig, & Vickers, 1992). The relative strength of Utopianism across countries (in descending order, China, Australia, Japan) is consistent with the relative strength of neuroticism (inversely), but not with extraversion (McCrae, Terracciano, & 79 Members of the Personality Profiles of Cultures Project, 2005; see their Figure 2), suggesting that country levels of neuroticism/pessimism may help explain these findings.

The third narrative of social change involved believing people in society will polarize, so that society overall will exhibit more of both positive and negative traits in the future than in the past (Expansion). Chinese and Australians endorsed the Expansion narrative more, such that society would show greater levels of competence warmth, and morality than in the past, but also greater levels of incompetence, coldness, and immorality. The converse narrative that human character was shrinking over time (Contraction), showing lesser warmth, morality, and competence, but also lesser coldness, immorality, and incompetence, tended to be held more by Japanese.

This ambivalent narrative about societal change was related to perceptions of economic and technological development. We propose that people see technology and economic development as “enablers,” providing the means to achieve our social goals whether these are benevolent (moral and warm) or malevolent (immoral and uncaring). Social media fit this pattern, as they enable positive social connections but also facilitate online trolling. For competence, it is uncontroversial that technology can be seen to enhance competence in society, but the link with greater incompetence is less obvious. We surmise that it reflects a fear that people are becoming over-reliant on technology, and thus becoming less capable of doing things themselves (making them more incompetent).

Country differences in Expansion/Contraction remained after controlling for development and demographics, with Japanese still endorsing a more contractionist view of societal change. We surmise that Expansion implies a more ambivalent, ambiguous, and uncertain future (with potential for more extreme good and bad things to happen) than for Contraction where society is expected to exhibit fewer extremes and surprises in the future than in the past. Thus, endorsing Expansion/Contraction may be related to avoidance of uncertainty, a value that is much stronger in Japan than in China, with Australians in-between (Hofstede, Hofstede, & Minkov, 2010), consistent with country differences for this narrative.

We proposed a fourth dimension (Endless Cycle), but despite its historical significance (Gray, 2004; Hardin, 1993), analyses revealed that that people see human character changing in linear rather than cyclic or other more complex ways. However, it is possible that the current time frame of 200 years was too short to capture a cyclic pattern, or that examining only 20- and 100-year increments was not able to identify shorter cycles in people’s beliefs about change. It is also possible that endless cycles are not seen in judgments about character, but may be observed in projections about more sociological features of society such as violence and crime (Bain et al., 2013) that might be more easily understood as exhibiting cyclic change (e.g., “crime waves”). This suggests the value of examining societal narratives of change beyond auto-stereotypes, including to values and social issues (Bain et al., 2013), to examine the consistency of beliefs about societal change across constructs.

Kashima et al.’s (2011) original analysis showed that Chinese did not show the typical FTSC pattern, in that they saw an increase in competence over time, but no decline in warmth and a halt in decline for morality in the future. The current analyses help to understand this finding. Chinese did hold the FTSC strongly—indeed more strongly than Japanese and Australians. However, at least some Chinese also held a more utopian view of the future than other cultures, where competence, warmth, and morality were expected to be higher in the future. Thus, Utopianism would inflate mean ratings of warmth, morality, and competence for future time points, accounting for Kashima et al.’s discrepant Chinese findings. That is, these seemingly anomalous findings appear to be due to two distinct cultural narratives (FTSC and Utopianism) that are both relatively strong in China. This illustrates a benefit of a three-mode analysis as a tool to “dig deeper” to understand cultural phenomena.

These analyses also have implications for understanding stereotype content across cultures. Relations between stereotype dimensions vary across personal and group contexts (e.g., Judd et al., 2005), and these findings show that these dimensions also vary across cultures and time. Moreover, the Expansion/Contraction narrative shows that the established dimensions of warmth, competence, and morality are not consistently applied to groups over time, as some people associate the future of the group with both greater and lesser warmth, morality, and competence. In this light, it is notable that some measures of stereotype content use positive traits only (Cheng et al., 2010; Cuddy et al., 2009; Fiske et al., 2002), as negative traits do not consistently fit the model (Fiske et al., 2002). The Expansion/Contraction narrative suggests that there may be systematic reasons for the failure of negative traits to correspond to stereotype dimensions, not just noise. This could deepen our understanding of stereotypes, so we recommend including both positive and negative traits in future research.

These analyses also identified anomalies in trait patterns that are difficult to explain. People holding the Expansion/Contraction narrative believed insensitivity (negative warmth), liking (positive warmth), and disorganized (negative competence) would emerge most strongly in the future (for those endorsing Expansion), or decline most strongly in the future (for those endorsing Contraction). Accordingly, these traits did not correspond to their theoretical stereotype content dimensions. However, we do not know why these particular traits were only weakly linked with FTSC yet strongly linked with Expansion/Contraction. We are wary of drawing strong conclusions about these traits from this analysis without replication, but they do suggest caution in assuming that stereotype content dimensions items are theoretically consistent when making judgments across time.

In using three-mode analyses to uncover complex relationships, it is remarkable that a small set of narratives describes common perceptions of societal change across three cultures, despite their diverse cultural histories. Although China, Australia, and Japan did vary, this was mainly in the strength and direction of the narratives they held, rather than each country holding distinctive and non-overlapping narratives. Future research is needed to uncover when and why people hold each societal change narrative. Although economic/technological development was a strong correlate, other sociological perceptions may also be relevant. For example, Expansion may be positively associated with social factors such as multiculturalism (where immigrants bring both positive and negative possibilities to society), wealth inequality (where the rich can be more benevolent and more exploitative of the poor), or deregulation (where relaxing laws and constraints can promote entrepreneurship but also exploitation).

Finding that the FTSC was the dominant narrative of societal change does not mean the other narratives are unimportant. There may be other countries or situations where they are dominant, or they may be emerging narratives that will become more important over time. Accordingly, there is at least suggestive evidence that significant cultural events such as hosting the Olympics could lead to a nation adopting more Utopian beliefs (Cheng et al., 2010).

Another way that societal change narratives may become more salient and important is through political rhetoric. A political leader may portray a utopian future for society if he or she were to lead the country, whereas their opponent presents a dystopian view of this outcome. Although committed followers of each leader may come to endorse the corresponding Utopian/Dystopian narratives, for unaligned observers, such rhetoric may prime Expansion—society would become both better and worse in some ways. Thus, politics is an area where these beliefs about societal change may be highly consequential.

Knowing the structure of people’s societal change narratives is important because it can underlie people’s support for social change. It may help politicians identify areas of concern that need to be addressed through policymaking to try to meet people’s concerns and create positive social change. Kashima et al. (2009) found a link between FTSC and support for community building policies rather than economic development policies, and other narratives may also have social consequences. For example, a Utopian narrative may lead to more entrepreneurship due to optimism about society’s future. Understanding social change narratives within countries may also be enlightening, such as exploring the implications of age differences in Utopian beliefs in Australia, or comparing perceptions among ethnic groups within a country about how it is changing, to help understand differing reactions to social policies.

Our capacity to engage in mental time travel, to imagine the future and the past, is one of the distinguishing characteristics of humanity (Suddendorf, 2006; Suddendorf & Corballis, 2007). This research has shown that mental time travel about society takes at least three distinct forms, present to some degree across cultures. This research is a step along the path to a better future, as to achieve a future people want, it is crucial to know where they think society is going and to know whether their perception, or reality, needs to be changed.

Footnotes

Appendix

Means and correlations for indices used in regression analyses.

			Correlations
		M (SD)	1	2	3
China
1	FTSC	10.28 (7.79)	—
2	Utopianism	1.08 (3.51)	−.35***	—
3	Expansion	0.37 (1.20)	−.12	−.26***	—
4	Development	6.14 (1.94)	.40***	.03	.20*
Australia
1	FTSC	7.13 (5.08)	—
2	Utopianism	0.01 (2.69)	−.10	—
3	Expansion	0.04 (0.84)	−.10	−.17	—
4	Development	4.97 (1.67)	.34***	.11	.16
Japan
1	FTSC	6.39 (6.81)	—
2	Utopianism	−1.60 (3.31)	−.31***	—
3	Expansion	−0.54 (0.78)	.08	−.06	—
4	Development	4.18 (1.96)	.49***	−.05	.10

Note. FTSC = folk theory of social change index, which was calculated without the divergent items.

p < .05. ***p < .005.

Acknowledgements

We thank Stephen C. Wright and the Center for Research in Social Psychology at the University of Queensland for valuable feedback.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by Australian Research Council Grants to the first author (DP0984678) and to the third author (DP1095323, DP130102229). The second author’s visit to Australia was supported by an Ethel Raybould Visiting Fellowship of the School of Mathematics and Physics, University of Queensland.

Notes

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