The Five “A”s of Meaning Maintenance: Finding Meaning in the Theories of Sense-Making

ion Compensatory affirmation is not the only way in which we can fluidly compensate for a meaning violation—sometimes we will find meaning when unrelated understandings are threatened. If we are looking to our environment to identify something—anything—that can be rendered familiar, the kinds of expected associations that we will draw or abstract may push the limits of fluid compensation even further. In much the same way as compensatory affirmation efforts, initial examples of compensatory abstraction appeared to involve pulling patterns out of the environment that could be construed as sharing content with the expected associations that were violated. For example, Whitson and Galinsky (2008) demonstrated that violations of control would enhance the motivation to see patterns within events that are not inherently related—ranging from simple causal attributions to grand conspiracy theories. Within the domain of personal control, it could be reasonably argued that these fluid compensation efforts were relatively distal attempts at regaining a sense of predictability and control in other domains. However, other research has suggested that different meaning violations will both motivate and enhance efforts to see “signals in the noise”—where these signals share no content with the violated meaning framework. For example, an unpublished study cited by Dechesne and Kruglanski (2004) suggests that reminders of one’s mortality can improve the implicit learning of complex patterns in (seemingly) random letter strings. In our own research (Proulx & Heine, 2009), we have built upon these earlier findings to demonstrate enhanced pattern abstraction following a variety of meaning violations—both implicit and explicit, trivial or self-relevant. Across these different experiments, we have used the same dependent measure—a variation of Reber’s (1967) original implicit associative learning task. During the “learning” phase of this task, participants are asked to copy out series of letter strings verbatim (e.g., XVTTRM) without being told why they are doing so. During the subsequent “test” phase, participants are told that the previous letter strings contained a complex pattern and are asked to guess which of a newly presented series of strings appears to follow the same pattern. Even though participants feel as though they are guessing at random, they are not, as they pick out the pattern-congruent strings at a frequency that is above chance—a remarkable feat, given that they have abstracted these patterns at an entirely unconscious level, without making an explicit effort to learn anything, or even an awareness that they were indeed learning. Following from our own meaning maintenance perspective, we expected something perhaps more remarkable—an enhanced ability to abstract the hidden patterns following unrelated meaning violations. As it turns out, the ability to implicitly abstract these complex probabilities is significantly enhanced following meaning violations, whether they follow from a threat to one’s identity, or a Franz Kafka short story. More recently, we demonstrated enhanced implicit pattern learning following a meaning violation that is itself entirely implicit—the subliminal presentation of anomalous word pairs (e.g., quickly blueberry; Randles et al., 2011) –where this violation also evokes the same compensatory affirmation efforts as mortality reminders or secretly switched experimenters (Proulx & Heine, 2008). Taken together, these studies demonstrate fluid compensation in a manner that is perhaps more radically content general than compensatory affirmation efforts—the enhanced implicit learning of statistical patterns following violations that share no common content, are implicit or explicitly perceived, and are self-relevant or entirely trivial. Ultimately, these effects can also be construed as meaning lost–meaning restored, where meaning is reduced to its most essential form: expected relations.