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Abstract

This study re-examines volunteering through Pierre Bourdieu’s theoretical framework, arguing that in Germany and other western countries, volunteering functions as a means of accumulating symbolic capital (i.e. social recognition and status). Individuals from higher social classes are increasingly investing in this field, thereby restricting access for those from lower classes. Using data from the German Socio-Economic Panel Study (1992–2017) and the German Survey on Volunteering (2014), I examine class-based differences in overall volunteering and specific activities linked to varying levels of symbolic capital. Panel analyses indicate that higher social classes have intensified their engagement in volunteering over the past decades, widening the gap with lower social classes. Furthermore, individuals from higher social classes prefer prestigious volunteering activities that facilitate symbolic capital accumulation. This trend has contributed to a long-term increase in class disparities in volunteering, reinforcing social inequalities and limiting opportunities for lower-class participation.

Keywords

Germany occupational classes panel analysis social inequality symbolic capital volunteering

Introduction

In western societies, an average of 25% of the population volunteers, and in affluent western societies, the percentage can exceed 40% (Baert and Vujić, 2018). Volunteering is not only highly popular but also widely regarded in a positive light. The media often features stories of individuals assisting the elderly, volunteering at food banks or working for the fire brigade. Volunteering is perceived not only as a way to compensate for shortcomings in community services but also as a means of fostering social cohesion. Accordingly, a high level of civic engagement is seen as the foundation of strong community cohesion and a generally satisfied citizenry (i.e. Putnam, 2000, but see Kleiner, 2021). This narrative has led to the voluntary sector being treated with kid gloves compared with many other social phenomena (Dean, 2020; Hustinx and Lammertyn, 2003: 168; Shachar et al., 2019: 245f.). As a result, significant social inequality within volunteering has received little attention. Research shows that higher social classes volunteer significantly more often than lower social classes (Dean, 2016; Hirschle, 2015; Meyer and Rameder, 2021; Rameder, 2015). This is crucial, as disparities in volunteering contribute to the unequal representation of social groups and their opportunities for cultural and political influence and integration. Systematic exclusion from these opportunities can contribute to feelings of deprivation, dissatisfaction or even alienation from the community, thereby negatively impacting social cohesion (Kleiner, 2021; Kleiner and Kühn, 2024).

This article posits that volunteerism has emerged as a mechanism for signalling and securing social status – a role once fulfilled by art and cultural taste, as elucidated by Pierre Bourdieu (1977). In the current social landscape, the ‘altruistic act’ seems to function as a marker of prestige. This dynamic perpetuates social stratification, not only by influencing access to volunteer opportunities but also by inadvertently weakening social cohesion through the exacerbation of representational imbalances in cultural and political spheres of influence.

Explanations for inequality in volunteering have been formulated by other perspectives, but doubts remain about their plausibility. For instance, the prevailing explanation suggests that actors from the higher social strata dominate the third sector due to the specific skills necessary to carry out volunteering activities (Einolf and Chambré, 2011). According to resource theory, individuals in higher social strata are more likely to volunteer due to their greater availability of resources, while those in lower classes may lack such resources. But why do so many people, particularly those from higher social classes, choose to volunteer, and why do many of them invest such enormous effort into it? Is it because people from the higher classes often see themselves as altruistic and want to help others without expecting anything in return, as has been stated (Wilson et al., 2020: 223)? Although such a subjective self-image may be widespread among the upper classes, it cannot convincingly explain why over 40% of the population in western affluent societies, such as Norway or Switzerland, do voluntary work (Lindsey and Mohan, 2019; Simonson et al., 2021: 112) despite the competition from a well-developed leisure industry (Hirschle, 2011). Would it not be more rational to donate money and allocate one’s valuable time to career advancement, personal leisure or family life?

According to Meyer and Rameder (2021) and Rameder (2015), the resource model fails to provide a satisfactory explanation for the high number of volunteers in post-industrial societies and the tendency for volunteers in these countries to come from the middle or upper classes. I agree.

From a sociological perspective, it is unrealistic to assume that people engage in volunteering solely out of altruism or enjoyment of the activity (Lindsey and Mohan, 2019; Simonson et al., 2021: 112). Given individuals’ scarce time resources, especially those from higher classes and the absence of direct material gain, other factors must be at play (Hustinx et al., 2022; Smith and Wang, 2016: 635).

It is a common misconception that volunteers merely give without receiving anything of value in return. Instead, I argue that volunteers can indeed receive something valuable in return. The literature shows that contributing to the community, especially by supporting and helping the powerless and vulnerable without receiving anything material in return, is highly respected and valued by fellow citizens in virtually every society (see Andreoni, 1990; Becker, 1974; Dean, 2020; Schwartz, 2007). Thus, by volunteering, an individual can gain a valuable asset: symbolic capital, which refers to status and appreciation.

From this perspective, social inequality in volunteering is not seen as a secondary effect of differences in ability or moralism, but as a direct result of people’s striving for symbolic capital. Actors from higher classes are more successful because they have more and better resources to acquire symbolic capital, a mechanism that has been described for a number of other social domains, such as the arts, leisure or sport (Bourdieu, 2010; Friedman and Reeves, 2020; Veblen, 2007).

Building on Pierre Bourdieu’s concept, I argue that volunteering in post-industrial societies has become a social field in which individuals compete for symbolic capital (Bourdieu, 1977: 179; Hayes, 2020: 21). In this field, individuals from higher social classes, due to their better access to economic, social and cultural resources, dominate the volunteering sector and claim most of the achievable symbolic value (Bourdieu, 2010; Dean, 2016).

The remainder of this article is structured as follows: first, I present my argument and derive testable hypotheses (section 2). I then test these hypotheses using longitudinal regression analyses based on data from the German Socio-Economic Panel (1992–2017) and data from the German Survey on Volunteering (2014). I use the EGP (Erikson, Goldthorpe and Portocarero) class scheme (Erikson and Goldthorpe, 1992) to illustrate the significant rise in social inequality in volunteering in recent decades (section 3). The findings also reveal that higher-class individuals are more likely to engage in prestigious activities (section 4). Finally, the article concludes with a discussion of the results and their implications (section 5).

Theoretical Background and Hypotheses

Volunteering and Symbolic Capital

Research has often overlooked or underestimated social inequality in volunteering (Hustinx et al., 2022). Rather than investigating the causes of inequality in engagement and analysing how differences in education, income or occupation contribute to the reproduction of social disparities in other areas, these variations have often been ascribed to functional requirements or resource availability (Hackl et al., 2012: 466; Musick et al., 2000; Wilson and Musick, 1997). For example, Wilson and Musick (1997: 694) argue that volunteer work requires human, social and cultural capital: ‘volunteer work is (1) productive work that requires human capital, (2) collective behaviour that requires social capital, and (3) ethically guided work that requires cultural capital’. Therefore, inequalities in the volunteering sector are primarily a demand-side consequence. Higher social classes volunteer more often due to their skill sets, while those from lower socio-economic backgrounds are implicitly excluded from such opportunities. This model, however, presents a twofold problem:

Surprisingly, the increasing opportunity costs of volunteering for individuals with greater resources are not considered. For instance, time is a scarce resource, and volunteering offers no significant advantages for higher social classes, who can acquire status, economic capital or other rewards through other activities (Carlson et al., 2011; Murnighan et al., 1993). According to human capital theory, as cited by Wilson and Musick, higher social classes are predicted to donate more money but commit less time to volunteering (Iannaccone, 1990: 309). However, empirical evidence does not support this prediction.

Furthermore, and more problematically, proponents of resource theory have often overlooked the rewards obtained through volunteering. In public discourse, volunteering is usually interpreted as an altruistic, pro-social helping behaviour that is beyond purely economic motives (Andreoni, 1990; Dean, 2020: 3; Rifkin, 2000; van Dyk, 2021). The value of an activity that consists of helping others, especially those in need, without expecting anything in return is not only hardly doubted, but also publicly acknowledged (Andreoni, 1990; Becker, 1974). Under certain circumstances it is even accompanied by a ‘glow of goodness [. . .] energised by those [. . .] who know you did the good deed’ (Dean, 2020: 156). Thus, it is incorrect to claim that volunteers receive nothing in return. On the contrary, volunteering provides a highly valued good in society: symbolic capital; that is, recognition, reputation, status or even moral superiority (Dean, 2020: 12).

If we acknowledge that volunteering can serve as a means of acquiring symbolic capital, we can apply Pierre Bourdieu’s practice theory – alongside the interrelated concepts of capital, habitus, social space and fields – to propose an alternative explanation for the observed inequalities in the third sector.

Meyer and Rameder (2021) interpret Bourdieu’s social field as a playground or battlefield with specific rules that act as laws within the universe of the social field in question. Each field has its own logic of practice, determining which types or combinations of capital yield benefits or symbolic capital (Meyer and Rameder, 2021: 20).

The voluntary sector can be conceptualized as such a contested field with unique codes, languages and understandings (Hayes, 2020: 21; Macmillan, 2011). Meyer and Rameder (2021) identify common mechanisms in the field of volunteering:

The dominant illusio assumes that engaged individuals are primarily driven by humanitarian concerns and altruistic motives. Reputational gains from volunteering occur only when the economic nature of transactions remains hidden (Meyer and Rameder, 2021: 20).

Individuals with good jobs signal possession of skills and social relationships demanded from volunteers, making them more likely to be recruited (for responsible positions) (Meyer and Rameder, 2021: 19).

Volunteer recruitment often follows the law of homophily, selecting individuals with characteristics already overrepresented among existing volunteer associations (McPerson et al., 2001).

Consequently, access to the field – especially to prestigious activities – is implicitly or explicitly regulated (Dean, 2016). Actors with more resources are better equipped to dominate the sector and acquire symbolic capital through volunteering.¹ These mechanisms lead to uneven accumulation of opportunities for field access and symbolic capital, widening the gap between high- and low-status groups, and potentially infusing the already resourceful with more resources and benefits (Matthew effect), while the less resourceful are blocked from such benefits.

As a result, privileged individuals who may not need the benefits of volunteering are most likely to access civil society organizations and attain influential positions. This further reinforces their competencies, reputation or prestige (Eimhjellen, 2023: 655; Meyer and Rameder, 2021). The voluntary sector thus becomes an arena for reproducing social inequality from other social fields.

The Rise of Volunteering as a Symbolic Marker

In addition to the notion that volunteering can be used to acquire symbolic capital, I argue that public perceptions of volunteering and its symbolic value have increased over the last few decades. This is owing to two interconnected developments:

First, the general transition to post-material inclusive universalist and emancipatory values in post-industrial societies: ‘While industrialization was linked with an emphasis on economic growth at almost any price, the publics of affluent societies placed increasing emphasis on quality-of-life, environmental protection, [. . .] self-expression’, and ‘well-being’ (Inglehart and Baker, 2000: 21, 49).

Second, the vocal criticism of the exploitative industrial and neoliberal economic system has become more widespread in recent decades (Boltanski and Chiapello, 2007; Chiapello, 2013; Helleiner, 2003). The process of environmental value change and the rise of environmental and climate movements (e.g. Fridays for Future, Extinction Rebellion) or movements against social inequality (e.g. Occupy Wall Street, We are the 99 Percent) is well documented (Helleiner, 2003: 694; Leiserowitz, 2021).

While providing support to the poor, weak or vulnerable without seeking profit is valued in nearly all societies (Schwartz, 2007: 711), this behaviour becomes even more valuable under circumstances where post-material values dominate and profit maximization is perceived as detrimental to the environment and the social fabric of society.

Jeremy Rifkin (2000: 239) argues that volunteering is ‘the realm in which fiduciary arrangements give way to community bonds, and where the giving of one’s time to others takes the place of artificially imposed market relationships’. And the post-materialist view claims ‘that the best of human satisfactions come not just from material possessions but from the experience of life’s social, cultural and natural wonders’ (Booth, 2018: 83).

Ron Henderson (2019), on the other hand, argues that in western societies, education, wealth and professional success are no longer enough to achieve true social status. Rather, status today is linked to the ‘right’ beliefs; the new elite must present themselves as morally upright and virtuous to gain prestige.

Volunteering and shining in the ‘warm glow’ of doing good (Andreoni, 1990: 464; Dean, 2020, 3) serves as a means of both embodying and showcasing postmodern values, thereby earning social recognition (Booth, 2018: 94). Moreover, since most thriving actors in western societies are still part of the conventional economy by means of gainful employment, volunteering can be used to add a moral touch to their life. If individuals use volunteering as a status marker and medium for gaining symbolic capital, this should, therefore, not be understood as merely coincidental. Rather, it is intimated by the zeitgeist.

Hypotheses

Assuming that volunteering in western societies has acquired a distinctive symbolic value and that altruistic motives are equally distributed among individuals from different strata, I argue that those in higher strata are better positioned for acquiring symbolic capital through volunteering due to their economic, cultural and social capital resources.

My first hypothesis states that upper social classes volunteer more frequently than middle social classes, who in turn volunteer more often than lower classes.

As shown above, I assume that the symbolic value gained through voluntary engagement has incrementally increased over the last few decades. Higher class members are better equipped to acquire symbolic capital through volunteering. My second hypothesis, accordingly, is that class differences increase over time.

Apart from differences in overall engagement, I am interested in the specific types of activity in which individuals from different class backgrounds engage. Volunteering encompasses a wide variety of domains with distinct activity profiles (Gray et al., 2012; Simonson et al., 2021). Thus, the symbolic value of an activity varies greatly across different profiles and their hierarchical and representational status. Consequently, I expect that members of different class strata will engage in distinct activities based on the symbolic value associated with these activities.

My third hypothesis is that members of the higher classes will be more likely than those of the middle classes, and the middle classes will be more likely than those of the lower classes, to engage in voluntary activities that provide distinctive symbolic value.

I test these hypotheses using two different sets of data. The following empirical part is therefore organized in two separate sections. The first section (Study 1) focuses on testing hypotheses 1 and 2 using survey data from the German Socio-Economic Panel (1992–2017). The second section (Study 2) uses data from the German Survey on Volunteering (2014) to examine hypothesis 3.

Study 1

Data and Operationalization

To test hypotheses 1 and 2, I use survey data from the German Socio-Economic Panel from 1992–2017 (SOEP, 2021). The SOEP is a representative panel survey that has been conducted at annual intervals since 1984 among approximately 30,000 individuals per year aged 17 and older in about 15,000 randomly selected private households in Germany.

The SOEP measures voluntary engagement not in its full range, but rather focuses on the classic ‘honorary office’. A characteristic feature of this type of volunteering is the institutional link to civil society organizations (clubs, associations or social services).

Volunteering is surveyed every two years and measured on a four-point scale. Since I am primarily interested in whether a person engages or not, I use a dichotomized version of the variable (individuals who volunteer every week, every month or less often receive a value of 1, respondents who never volunteer are coded to 0).

To measure occupational class positions, I use the EGP class scheme (Erikson and Goldthorpe, 1992). It is theoretically inspired by Max Weber (1978) and primarily expresses the objective characteristics of occupational activity and the productive and contractual framework in which the employed are embedded. Class position does not imply class consciousness in the sense of Karl Marx. Nevertheless, similar interests can of course result from such class situations, insofar as the members of a class likely have similar educational biographies, work under similar employment conditions and are subject to certain common opportunities and risks (such as fixed-term, temporary, precarious employment) (Chan and Goldthorpe, 2007: 514). I acknowledge that the EGP class scheme is not ideal for testing a Bourdieu-inspired theory with strong Marxist elements. However, the SOEP does not provide an alternative method for class operationalization. Nonetheless, the Weber-inspired EGP scheme captures two central divisions in the working population that are relevant for a Bourdieusian/Marxian-inspired study: the distinction between manual workers (EGP VI and VII) and the service class/self-employed, as well as the division within the service class and the self-employed between jobs requiring higher education, creative tasks and/or personnel responsibility (EGP I, II) versus all other jobs (Erikson and Goldthorpe, 1992: 36). In fact, the EGP scheme differentiates between 13 occupational classes (Erikson and Goldthorpe, 1992: 36), of which I use only six to focus on those classes that, in my view, are most likely to differ in lifestyle (see Table 1).²

Table 1.

EGP occupational classes (German SOEP).

Labels	Description according to Erikson and Goldthorpe (1992)
Managers (higher grade) (14.1%)	I Higher-grade professionals, administrators and officials; managers in large industrial establishments; large proprietors
Managers (lower grade) (26.7%)	II Lower-grade professionals, administrators and officials, higher-grade technicians; managers in small industrial establishments; supervisors of non-manual employees
Routine non-manuals (13.6%)	IIIa Routine non-manual employees, higher grade (administration and commerce)
Sales and service (13.6%)	IIIb Routine non-manual employees, lower grade (sales and services)
Skilled workers (14.4%)	V Manual supervisors VI Skilled manual workers
Unskilled workers (17.7%)	VIIa Non-skilled manual workers VIIb Agricultural labour

Notes: percentages correspond to the distribution in the sample of employed persons in 2017 (weighted). Non-employed persons as well as persons under 17 and over 65 years of age were excluded from the calculations.

SOEP: socio-economic panel.

Regarding the systematics of the EGP scheme, some occupational classes have a hierarchical relationship due to differences in qualifications and authority, typically accompanied by income differences. Other groups are more horizontally structured (Chan and Goldthorpe, 2007: 514). At the top of this hierarchy are higher-grade managers, followed by lower-grade managers, including various types of managers, department heads, senior and mid-level civil servants, as well as business managers and owners. Below them in the hierarchy are members of the ‘Routine non-manual’ class. Although they are not always clearly distinguishable from lower-grade managers (Evans and Mills, 2000), they generally have less authority. Typical examples of this class are commercial employees, who, despite different employment contracts, are hierarchically on the same level as skilled workers.

In contrast, the lower segment of the class scheme includes lower routine employees and unskilled and semi-skilled workers. Lower routine employees (in sales and service) typically require low qualifications and are mainly involved in personal services (e.g. selling goods in supermarkets and boutiques, delivering packages, cleaning buildings and working as service staff in restaurants and cafes). Semi-skilled and unskilled workers, on the other hand, generally perform simple tasks in the manufacturing sector.

Methods of Analysis

To test whether the occupational class is related to the probability of volunteering, I use logistic regressions. Volunteering (binary variable) is employed as the dependent variable and EGP class position (factor variable) as the independent variable. I also account for factors that may influence the relationship between occupational class and volunteering, such as type of employment (full-time, part-time, other forms of employment (e.g. marginal employment, part-time for older workers or training), gender, age, migration background, church attendance, survey region (East/West Germany) and whether the respondent lives in a rural or urban area.³

Our study is focused on the employed population. Accordingly, I restrict my sample to employed respondents between 17 and 65 years of age. Since voluntary engagement was not surveyed annually, I cannot draw on all waves, but on a total of 18 waves out of 26. This results to 169,891 observations between the years 1992 and 2017 based on a sample of 44,044 respondents.

To test hypothesis 1, I conduct two separate logistic regressions for 1992 and 2017 (the beginning and end of the observation window). To test hypothesis 2, I use the complete dataset from 1992 to 2017, adding the interview year as a variable and an interaction term between year and EGP class position to examine the development of each class over time. Since the SOEP is a panel study in which most respondents were interviewed in several waves in a row (3.9 waves on average), I treat variances between individuals (between variances) and variances of the same individuals between different points in time (within-variances) separately by means of random-effects panel regression analyses (Wooldridge, 2002: 257f).

As the coefficients of logistic regressions are not intuitively interpretable beyond direction and significance, in addition to the results of the regression analyses (Table A1, Online Appendix), I present predicted margins for the different class locations that map the probabilities of being a volunteer as a function of class location, or class location and year, while controlling for all other variables.

Results

Figure 1 presents results from logistic regressions for 1992 and 2017, with volunteering as the dependent variable and EGP classes as the central independent factor variable. The grey squares represent predicted probabilities of volunteering for different occupational classes in 1992, the black circles the predicted margins for 2017. The bases for these calculations, the results from regression analyses, can be found in the Online Appendix (Table A1).

Figure 1.

Probability of volunteering in 1992 and 2017.

Looking at the values for 1992 reveals a gradation between occupational classes in the expected direction: the higher the class position, the higher the probability of volunteering. However, most of the differences are not statistically significant. Only differences between the working class on the one hand (skilled and unskilled workers combined) and the salariat (including routine non-manual workers) are statistically significant. Differences are thus particularly apparent between white-collar and blue-collar workers.

In comparison, the results from 2017 reveal a different picture. First, virtually all classes – with the exception of the service and sales class – have significantly higher probabilities to volunteer in 2017 than in 1992. Second, the differences between the classes are much more pronounced. For example, higher-grade managers are the most likely to volunteer and significantly more likely to volunteer than lower-grade managers, who rank second overall. The differences between lower-grade managers and routine non-manual workers are also statistically significant.

Apart from these subtle differences, in 2017 a clear divergence of two class camps becomes apparent: the salariat with probabilities above 37% to volunteer on the one hand (managers and routine non-manual workers) and the blue-collar workers and service and sales class with a probability of 32% or less on the other.

The extent of the differences becomes clear when comparing the various groups. For example, the probability of volunteering in 2017 is less than 25% for unskilled workers but over 45% for higher-grade managers. Between routine non-manual workers and the service and sales class – two contiguous occupational groups – differences still amount to 9 percentage points (38% versus 29%), and therefore point to distinctive practices in the sense of Bourdieu (middle vs. lower classes) (Bourdieu, 2010: 321f).

Overall, we can conclude that the results confirm hypothesis 1. It should be noted, however, that the differences are not only graded according to internal occupational hierarchy (qualification, authority to issue directives), but are also visible between the service and working classes. This is particularly evident when comparing routine non-manual workers (38%) and skilled workers (31%), who differ in the EGP scheme mainly with regard to employment contract, but are located at the same hierarchical level.

Figure 2 presents results from random-effects regression analyses with all available waves of the SOEP data processed. The figure shows the developments of the EGP classes over time, calculated using the EGP factor variable, the survey year and an interaction between EGP and year.

Figure 2.

Volunteering and occupational class.

Even a cursory glance at the markers and their values in Figure 2 reveals the drifting apart of two class camps. On the one hand, there are the managers and professionals (higher and lower grade) and the routine non-manual workers; on the other hand, there are the workers (skilled and unskilled) and the sales and service class. While both class camps were still close at the beginning of the observation window in 1992, by the end in 2017 they are separated by a gap of 6 percentage points or more.

Overall, therefore, the expected trend outlined in hypothesis 2 is provisionally verified. Not in line with the hypothesis is only the rather weakly pronounced difference between routine non-manual workers and lower-grade managers that, moreover, becomes completely blurred over time. This finding may also be the result of the fuzzy boundaries in the EGP scheme between grades II and IIIa (Evans and Mills, 2000: 657).

Apart from this outlier, the expected differences in voluntary engagement are not only evident in the rough divergences between occupational camps (higher vs. lower classes) but also, as expected, in nuanced distinctions between adjacent class strata. While at the beginning of the time window in 1992 differences between skilled workers and unskilled workers, between routine non-manual workers and members of the sales and service class and, not least, in the top segment between higher-grade and lower-grade managers are still small and insignificant, they are much more pronounced at the end of the period and substantial in all these cases (see also Figure 1).

Study 2

Data and Operationalization

I use data from the Freiwilligensurvey (German Survey on Volunteering, FWS) to examine differences between occupational classes with respect to specific activities in the third sector (hypothesis 3). The FWS (2014) is a representative survey for the German population and contains a total of 28,690 interviews. The focus in the FWS is on surveying voluntary engagement. Beyond volunteering levels, detailed information on the area of volunteering and the type of activity is collected (Hameister et al., 2019).

The purpose is to address hypothesis 3 and to test whether the higher classes are more likely to engage in voluntary activities that facilitate the acquisition of symbolic capital through volunteering. In this respect, two factors seem decisive: first, representative activities have the advantage of being visible to a broader audience, thereby creating status as a mere consequence of doing the ‘job’. Second, and similar to the labour market, activities are explicitly or implicitly ranked in terms of status, where ‘occupations that require working with symbols and perhaps people, and especially professional occupations, confer the highest status, while those that require working directly with material things confer the lowest status’ (Chan and Goldthorpe, 2007: 515).

In the FWS, voluntary engagement is surveyed more broadly than in the German SOEP. The questionnaire includes not only organizational activities, but all types of volunteering, including those that take place outside clubs, associations or organizations. The overall rates are correspondingly higher – in the SOEP they amount to 34.3% for 2015, in the FWS to 39.5% in 2014.

To examine differences in voluntary job descriptions, I focus on respondents who volunteer, focusing on class differences in specific activities rather than overall engagement rates.

However, the variety of activities carried out in the different domains can only be studied schematically. For many critical activities, it is hardly possible to determine the average symbolic value assigned to their exercise. Therefore, I only distinguish activities that can be roughly interpreted in terms of their hierarchical position (in relation to other activities) and/or their representative character. To achieve this, the answers to two open-ended questions about the respondents’ voluntary activities were encoded step by step. First, keyword lists (e.g. soccer, handball) were used as the basis for an automated classification into different areas of involvement (sport). The keyword lists used for automatic categorization were compiled by reviewing the open-ended responses. Second, all the data were subjected to a follow-up check. The remaining cases in the ‘other’ category were also categorized where possible. Incorrect categorizations were corrected. At the end of this process, 92 cases (0.8% of the total valid data) remained that either could not be categorized because there was no evaluable data or fell into an area for which no category existed. I distinguish between management and representational tasks (chairpersons, presidents, managing directors), associated with high status, organizational and administrative tasks (treasurer, public relations, organization of events), associated with average status, and manual auxiliary activities (cooking, cleaning, working on infrastructure, selling drinks at events), which are hardly associated with status beyond the mere association with the group.

In addition, I use a variable that expresses area-specific critical activities constituting the core tasks of a domain, such as caring for people in the social domain, coach in sports, firefighter in the fire brigade and so on. Since these domains and activities are heterogeneous, it is practically impossible to specify the associated symbolic value in each case. Therefore, I use this category only for control purposes and in the form of a cross-domain variable simply indicating whether or not a person performs such a task, without specifying the domain itself.

Owing to the fact that respondents may be active in more than one of these fields of activity, the four categories are available as binary variables where 1 indicates activity and 0 non-activity.

To operationalize for occupational classes, I cannot use the ready-made EGP classes in the FWS that are available to us in the SOEP. Instead, I reconstruct a simplified class variable from a categorical occupational question. Following the EGP schema, I distinguish between managers (I, II), routine non-manual workers (IIIa), sales and service (IIIb), skilled workers (V, VI) and unskilled workers (VII) based on qualification and authority. I exclude self-employed workers but, following the EGP scheme, categorize self-employed workers with more than 10 employees as managers.

Methods of Analysis

To test whether occupational class is related to the probability of engaging in volunteer activities associated with higher or lower symbolic value, I conduct four logistic regressions. The activity-specific (bivariate) variables serve as dependent variables, the class position (factor variable) as independent variable. I control for the same factors as in the analyses based on SOEP data (see Study 1, ‘Methods of Analysis’) with the exception of church attendance, which was not collected in the FWS.

Results

In Study 1, I examined the relationship between class and the likelihood of volunteering. I now take a closer look at different activities that volunteers engage in. I thereby restrict the sample to respondents who volunteer.

Before turning to these analyses, I take a brief look at the relationship between social class and overall engagement in the FWS data in order to audit for possible differences compared with data from the German SOEP. Table 2 provides these values for the five occupational classes in the FWS (2014) and for the six classes in the SOEP (2015), respectively.

Table 2.

Volunteers by occupational class in FWS (2014) and German SOEP (2015) in comparison.

FWS 2014			SOEP 2015
	Col %	N		Col %	N
			Managers (higher grade)	43.6	1309
Managers	50.7	3494	Managers (lower grade)	41.5	2156
Routine non-manuals	43.8	3960	Routine non-manuals	37.3	1035
Sales and service	29.0	661	Sales and service	29.2	872
Skilled workers	35.4	841	Skilled workers	27.5	763
Unskilled workers	20.6	397	Unskilled workers	23.1	796
Total	39.5	9353	Total	34.3	6931

Note: FWS 2014 and SOEP 2015, weighted percentages.

SOEP: socio-economic panel.

It becomes obvious that both surveys lead to similar results. Both in the SOEP and the FWS, managers have the highest activity rates, followed by routine non-manual and skilled workers. Engagement is lowest among unskilled workers. Differences emerge, however, with respect to the overall level of voluntary engagement (+5 percentage points in the FWS). This is, as outlined in the operationalization section, a result of different measurement instruments used in the SOEP and the FWS. While it is theoretically possible that our results are influenced by the exclusion of non-institutionalized forms of volunteering in Study 1, this is not the case; higher occupational groups are more likely to volunteer in both institutionalized and non-institutionalized settings (Table A2, Online Appendix). Additionally, Study 2 addresses this limitation by using data that broadly covers volunteering.

Hypothesis 3 claims that class position is correlated with specific activity profiles. I argue that higher classes perform activities that confer higher status, where the status of an activity depends on its content and whether it entails representative functions. This results in three types of practices: manual auxiliary activities confer low status, administrative/organizational activities confer medium status and managerial functions confer high status. Additionally, for the sake of completeness, I include cross-field critical activities that cannot be assigned a status or prestige due to their diverse profiles.

Figure 3 presents the results of the analyses. As above, I provide predictive margins calculated on the basis of the fitted logistic regressions (see Table A3, Online Appendix).

Figure 3.

Probability to engage in certain activities.

Results indicate significant differences between the occupational classes for all three status-indicative activity profiles. As expected, managers are least likely to engage in low status auxiliary activities, followed by routine non-manual workers (difference significant). While differences between members of the sales and service class and workers are negligible and insignificant, they are substantially more likely to engage in auxiliary activities than managers and routine non-manual workers.

As in relation to administrative activities, significant and substantial differences can only be found between managers and routine non-manual workers on the one hand, and (blue-collar) workers and the sales and service class on the other, with the latter groups performing these activities far less likely than the former. While the direction of the correlations is therefore consistent with hypothesis 3, the expected subtle differences within members of the service classes are not revealed.

The same is true for representative tasks (chairperson, managers, presidents). As expected, managers and routine non-manual workers are more likely, while workers and members of the sales and service class are less likely to engage in these activities.⁴

A brief look at the critical tasks reveals no significant distinctions between occupational classes. That is unsurprising, given that these activities can confer very different levels of social recognition depending on the domain and the opportunity to represent (e.g. political office, parental representation, sport coach, caring for elderly people, firefighter, etc.; see Kleiner, 2022a).

Discussion and Conclusion

The empirical analyses reveal substantial variations in volunteering across occupational classes. Upper strata (senior managers) volunteer the most, followed by middle strata (lower managers and routine non-manual workers), with lower strata (unskilled workers, service and sales) volunteering the least. Notably, professionals – who belong to the middle strata – volunteer less than expected, possibly due to the declining status of manual labour in a service-driven economy (Chan and Goldthorpe, 2007: 515; Florida, 2002).

Longitudinal analyses indicate a clear evolution in class disparities over time. While all classes volunteer more in 2017 than in 1992, the increase is steepest for higher-grade managers and least for unskilled workers.

I also observe significant class differences in the types of volunteer activities. Higher occupational classes tend to engage more in high-status, representational roles, avoiding simple manual tasks. These differences are particularly pronounced between upper and lower classes, but finer distinctions within the upper and middle classes are not evident.

The results align with Bourdieu’s theory of social fields, which posits that individuals leverage their economic, social, cultural and symbolic capital not only to participate in the voluntary sector but also to secure prestigious positions within it, thereby accumulating additional symbolic capital. Those endowed with such capital signal their potential contributions effectively, increasing their chances of recruitment. The law of homophily ensures that more individuals from higher classes are recruited, thus maintaining existing networks and resources within these upper echelons and further widening the gap between social strata.

Overall, the increasing social inequality in volunteering is striking. The growing dominance of the salariat in the third sector challenges the narrative of altruistic motivation. Instead, the third sector functions as a social field, as described by Bourdieu, where symbolic capital is at stake (Dean, 2020). This dominance is not incidental but rather indicative of a broader transformation in the mechanisms of social distinction. In Bourdieu’s terms, while art and cultural taste once served to demarcate social status, today, volunteering fulfils this role. Tomorrow, it may be something entirely different. This continuous reproduction of social inequality has profound consequences: it reinforces disparities in cultural and political influence, systematically excludes lower-status groups from participation and ultimately weakens social cohesion by fostering feelings of deprivation and alienation.

It is important to emphasize that the results do not imply that altruistic motives are absent in volunteering. However, it is implausible to assume that altruism is so unequally distributed across occupational classes that it could account for the class distinctions observed in volunteering. Altruism is not a virtue exclusive to the upper classes, nor is it likely that the degree of altruism has increased primarily among them over time. Furthermore, there is no evidence to suggest that the material situation of lower occupational classes in Germany has worsened over the past 20 to 30 years to the extent that it has reduced their capacity to volunteer (Grabka, 2021).

Although the findings are clear, I was unable to operationalize the true motives underlying voluntary engagement. Investigating these motives is a complex and difficult task (Lindsey and Mohan, 2019: 113). Indeed, fully disentangling these motives may be inherently challenging, as they often intersect with socially desirable narratives (Bourdieu, 1998: 113; Meyer and Rameder, 2021: 21). Moreover, the symbolic value attributed to different activities cannot be explicitly determined. There is also the possibility that the observed sharp increase in volunteering among the upper classes is primarily a methodological artefact – namely, an increase in the social desirability of volunteering (Hermansen, 2018; Lee and Sargeant, 2009). If the symbolic value of volunteering has advanced particularly among the higher classes, those in this stratum may feel more obliged to report volunteering in interviews, as it is considered socially desirable (Kleiner, 2022b).

Nevertheless, the thesis – that individuals can acquire symbolic capital through ‘conspicuous volunteering’ – and the argument that the symbolic value of volunteering has increased over time due to the rise of post-material values, provide a plausible explanation for both the observed class differences and the widening gap in volunteering rates between classes over time. To my knowledge, no competing theoretical approach can account for this. But I, of course, invite other researchers to provide alternative explanations.

I wish to make it unequivocally clear that my intention is not to discredit volunteering. On the contrary, my goal is to safeguard the voluntary sector, which, at its core, provides essential services through altruistically motivated individuals from all walks of life – benefiting not only fellow human beings but also the environment, animals and society as a whole. However, the colonization of volunteering as a space for the display of social status and moral superiority is likely to marginalize truly altruistic individuals performing critical tasks in favour of free riders engaging in purely symbolic activities to gain prestige.

Supplemental Material

sj-docx-1-soc-10.1177_00380385251343282 – Supplemental material for On Good Deeds and the Reproduction of Social Inequality: An Empirical Study on Social Class and Volunteering in Germany

Supplemental material, sj-docx-1-soc-10.1177_00380385251343282 for On Good Deeds and the Reproduction of Social Inequality: An Empirical Study on Social Class and Volunteering in Germany by Tuuli-Marja Kleiner in Sociology

Footnotes

Acknowledgements

I would like to thank all the reviewers and editors for their valuable comments and suggestions. I would also like to express my sincere gratitude to my beloved husband and best friend, who provided invaluable insights and recommendations to improve the quality of this article.

Funding

The author received no financial support for the research, authorship and/or publication of this article.

ORCID iD

Tuuli-Marja Kleiner

Supplemental material

Supplemental material for this article is available online.

Notes

Tuuli-Marja Kleiner is a senior researcher at the Thünen Institute for Rural Studies. Her research focuses on civic engagement, political culture and social cohesion, specifically volunteering, political trust and public opinion polarization, with publications in journals such as Swiss Political Science Review, European Journal of Political Research, European Political Science, Journal of Sociology and Journal of Contemporary European Studies. She has previously worked as a researcher and lecturer at various German universities, earned her PhD from the University of Hamburg and habilitated at Goethe University Frankfurt. In addition to research and teaching, she provides science-based policy advice to federal ministries.

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