COVID-19 and careers: On the futility of generational explanations.

It is common to broadly group people of different ages into "generations" and to speak of distinctions between such groups in terms of "generational differences." The problem with this practice, is that there exists no credible scientific evidence that (a) generations exist, (b) that people can be reliably classified into generational groups, and (c) that there are demonstrable differences between such groups. We have already noted an emerging generationalized rhetoric that has characterized how people of different ages have been affected by and reacted to the COVID-19 pandemic. These narratives have been especially present in discussions of how work and careers will be affected by this crisis. In this essay, we outline problems with applying the concept of generations, especially for researchers seeking explanations for how COVID-19 will affect careers and career development. We urge researchers to eschew the notion of generations and generational differences and consider alternative lifespan development theoretical frameworks that better capture age-graded processes.

Humans naturally seek simplified explanations for their own and others' behavior through a process of sensemaking, especially during “uncertain times” (Kramer, 1999). This process is enacted through numerous means, including the construction and adoption of stereotypes (Hogg, 2000). To this end, there is a tendency to broadly classify people into distinct groups based on demographic characteristics, such as age and gender, and to make generalized assumptions about the “typical” attitudes, values, and behaviors of all members in a given group that distinguish them from members of other groups. In particular, we often see sentiments that members of one generational group are markedly different in various ways from members of another generation. Such differences are noted across domains, for example, members of certain generations are often chided for “killing” various industries (e.g., napkins, Koncius, 2016; cereal, Severson, 2016; fabric softener, Terlep, 2016). Generational explanations for behavior can likewise be seen across domains of study in the organizational sciences (see Costanza, Badger, Fraser, Severt, & Gade, 2012; Zabel, Biermeier-Hanson, Baltes, Early, & Shepard, 2017 for meta-analyses), including vocational behavior (e.g., Holtschlag, Masuda, Reiche, & Morales, 2020).

Clearly, COVID-19 is presenting us with “uncertain times,” and the influence of this pandemic has already represented a career “shock” to many people (e.g., Cox, 2020a, Cox, 2020b). As a way of making sense of this crisis, researchers and practitioners may be tempted to seek out generational explanations to understand the impacts of COVID-19 for workers, and especially their careers and career development. Despite this, we strongly caution against the application of “generationalized” explanations for COVID-19, especially to understand careers and career development (see related arguments offered by Rudolph & Zacher, 2020). Generationalized explanations are those the rest upon the assumptions that (1) distinct generations exist, (2) there are demonstrable differences between generations, and (3) these differences can be empirically studied. Unfortunately, each of these assumptions represents a “myth” about generations that does not hold up to logical or empirical scrutiny. The assumptions that support generationalized explanations are dependent on one-another, forming a logical “house of cards,” wherein falsifying any single assumption invalidates the entire idea of generations and generational differences. In our previous work, we have outlined these issues in some detail, so we only allude to them briefly here (see Rudolph, 2015; Rudolph and Zacher, 2015, Rudolph and Zacher, 2017; Zacher, 2015).

First, the idea that generations and assumed differences between them actually exist is highly doubtful in light of their socially constructed nature (see Rudolph & Zacher, 2015, for an introduction and overview of this perspective). Simply put, generations exist because we think that they do; we will them into being. Generations provide a convenient way for us to describe otherwise complex phenomena associated with human aging into simpler, if not consequently reductive and deterministic terms (Walker, 1993). Generations and assumed differences between them are socially constructed through numerous mechanisms, for example, these ideas are born from and reinforced by the media, often through sensationalized headlines (e.g., Glazer, 2020). Moreover, some scientists and organizational consultants financially benefit from promoting the idea that, despite weak or non-existent empirical evidence, generational differences exist (e.g., by selling popular press books, by conducting trainings and workshops). As suggested by Rudolph and Zacher (2020), we are already seeing a generationalized rhetoric of COVID-19 emerging (see also Ayalon et al., 2020).

Second, research that has attempted to study generational differences generally finds small differences between members of (assumed) generational groups (e.g., Costanza et al., 2012; Zabel et al., 2017). That said, the understanding of the “demonstrable differences” assumption is qualified by the third assumption. Namely, third, there exists no methodology or statistical/analytic framework that can unambiguously separate out “generations” (i.e., birth cohort effects) from two other time-varying influences: chronological age and contemporaneous period effects. These methodological and statistical/analytic issues matter, as suggested by Rudolph and Zacher (2018), because “… it could be argued that there has never actually been an empirical study of generational differences” (p. 4).

In particular, in common research designs (i.e., cross-sectional, cross-temporal, longitudinal), age effects, period effects, and cohort effects are variously confounded with one-another. This issue is well understood and defined in the literature (e.g., Glenn, 1976; see also Rudolph, 2015; Rudolph, Costanza, Wright, & Zacher, 2019; Rudolph & Zacher, 2017, for critiques and empirical demonstrations of these and related issues). Of particular note, the conflation of cohort and period effects bears some consideration, especially to the extent that one is attributed to the other. Factors that occur contemporaneously and that are experienced broadly (e.g., economic conditions, global pandemics) manifest as period effects, not as cohort (i.e., generational) effects. COVID-19 has already affected hundreds of millions of people across the globe, either directly or indirectly; its influence will continue to be wide-sweeping, affecting everyone regardless of their birth year and their (assumed) membership in one generation, versus another.

Just as we would caution against the application of generations for studying any phenomenon related to work (e.g., leadership; Rudolph, Rauvola, & Zacher, 2018), so too would we offer that generations are not a reasonable framework for understanding vocational behavior topics. We fully recognize that generations are a convenient way of explaining colloquially the uncertainties associated with COVID-19. However, this convenience does not make for good science. At best, it represents a misguided effort. At worst, it opens up the possibilities of generationalism (Rauvola, Rudolph, & Zacher, 2019). To circumvent this issue, we strongly recommend that vocational behavior researchers adopt a lifespan development perspective for understanding the impacts of COVID-19 on workers of all ages, regardless of assumptions made about their generation (see Rudolph, 2016; Rudolph & Zacher, 2017). The lifespan development framework has a long history in vocational behavior research (e.g., Vondracek, Lerner, & Schulenberg, 1986), which makes it an ideal fit to the types of research and practice questions that would otherwise give rise to generationalized explanations. In following our advice to adopt a lifespan development perspective, vocational behavior researchers could attempt to understand how the effectiveness of individuals' personal and contextual resources (e.g., capacities for emotion regulation, social support) for coping with specific demands imposed by the pandemic (e.g., increased work demands, social isolation) change with age. Additionally, vocational behavior researchers could investigate various career and life management strategies (e.g., primary and secondary control striving; Heckhausen & Tomasik, 2002; selection, optimization, compensation; Wiese, Freund, & Baltes, 2000) that people use to successfully manage transitions from school to work, from employment to unemployment, from work to retirement, and vice-versa, during the COVID-19 pandemic.

In closing, we recognize that some problems require fast and simple explanations and solutions. However, other problems, like understanding the impacts of a global pandemic on work, and especially people's careers and career development, require more nuanced and complex explanations and solutions. Generations are a vastly oversimplified framework for understanding behavior in any context, and in particular in the workplace. We urge caution to researchers and practitioners to overcome the tendency to classify and divide people along generationalized lines, in favor of more comprehensive and rigorous theorizing and explanations for behaviors during these trying times.