For decades, the sports policy mission statement “Sport for All” has been aimed in particular at addressing and attracting women to sports activities, as well as to voluntary work in the sports sector (especially in sports clubs) in Germany. “Frauen an die Spitze” (“Women to the top”) was, for example, an initiative of the German Sports Confederation (DSB) and the Federal Ministry for Family Affairs, Senior Citizens, Women and Youth (BMFSFJ) in the early 2000s, and was intended to contribute to the equal participation of women and men in voluntary leadership positions in sports organized by clubs and associations (BMFSFJ, 2004). For a number of years, mentoring programs in sport have been supported by both the German Olympic Sports Confederations (DOSB) and by some member organizations as an instrument of personnel development. The aim is to support qualified young professionals who want a career in organized sport. There is also an expectation, above all, that mentoring programs will increase the proportion of female managers in sports. In 2012, for example, the DOSB launched the mentoring project “To the top with a mixed double!” with the aim of recruiting former female athletes for voluntary or full-time leadership positions in organized sport (DOSB, 2013). A gender quota has been enshrined in the DOSB statutes since 2014. The target quota for individual elections and for members of the DOSB Executive Board is for women and men to each comprise at least 30% of all DOSB bodies (DOSB, 2017; for an overview see Hartmann-Tews, 2019).

Such programs and initiatives to promote women in sport and voluntary work can also be found in other countries and international organizations (Adriaanse, 2017). An example of this is the “Balance in Sports Project” from 2016, which led to the development of tools to implement gender equality or the project “All in: Towards gender balance in sport” from 2018 to 2019 (Council of Europe, n. d.). At the international level, the United Nations Entity for Gender Equality and the Empowerment of Women (UN Women) “invites members of the sport ecosystem to join the Sports for Generation Equality Initiative to accelerate progress on a set of common principles and aligned objectives that will harness the power of sport in making gender equality a reality in and through sport” (UN Women, 2020, p. 1). The extent to which this can increase the proportion of women volunteering apparently depends on regional, national and organizational acceptance and is still debated (Evans and Pfister, 2021). Baxter et al. (2021) summarize that while women's participation in sport has increased worldwide over the last two decades, the number of women volunteers (e.g., referees, judges) has not increased to the same extent. This also applies in particular to the representation of women in top positions in sports organizations (Kvande, 2007). In Germany, the status is as follows: Only two out of the 16 state sports federations are currently led by a woman. In five out of 58 national sport associations, the voluntary leader is female, and in six associations there is a female/male tandem leadership. A positive development can be seen in the proportion of women in the presidia and executive boards of the state sports federations, seven of which reach the quota of 30%. Just under a quarter of the 58 participating national sport associations have at least 30% women on their voluntary boards. However, there are also 13 associations without women on the executive committee. The average proportion of women is 18% (DOSB, 2021). In 2021, according to the organization's own data, 11 out of 87 member organizations have established a mentoring program. Over the last five years, 17 associations had their own mentoring program (DOSB, 2021). In view of these numbers, it can already be seen as a success that women make up 44.4% of the German Olympic Sports Confederation's Executive Board, presumably due to the gender quota mentioned above (DOSB, 2021).

The sports development report 2017/2018 is based on feedback from clubs and its results show that in 2017 the share of women on sports clubs' boards was 30.7%, which is still substantially below the average female membership per association of 35.9%. Women are most often engaged as secretaries (46.3%) and youth leaders (37.4%), but least often as chairpersons (16.0%) (Breuer and Feiler, 2020).

The underrepresentation of women in volunteer and especially in leadership positions in club sports is not unique to Germany (for an overview see Burton and Leberman, 2017; Elling et al., 2019). The proportion of women on the boards of national sport federations in European Union countries is 14% (Wicker et al., 2020 based on Data from European Institute for Gender Equality). A similar trend was found by Adriaanse (2016) and Tranter et al. (2016). Van der Roest et al. (2017) report that in all ten countries they studied, men are overrepresented relative to women as members and volunteers in community sports clubs. Gender equality is most likely to be found in the Scandinavian countries, while studies from Spain and Poland tend to indicate significantly higher proportions of men (Burton and Leberman, 2017; Lamprecht et al., 2017; Sisjord et al., 2017; Evans and Pfister, 2021).

The consistent and global underrepresentation of women in volunteering within sport organizations and especially on boards could be an indicator of gender inequality. However, one-dimensional gender analyses fall short of adequately describing forms of discrimination, power relations, subject positions and social inequalities in voluntary engagement and leadership positions in sport. Moreover, the focus is often on sports associations and on leadership positions (Shaw, 2006; Claringbould and Knoppers, 2008; Terjesen et al., 2009; Adriaanse and Schofield, 2013; Gaston et al., 2020) and less on (grassroots) sports clubs and volunteering. This is where our own study comes in. Based on a quantitative population survey on volunteering in Germany, we look for factors and interactions that can predict women's volunteering and leadership in sport. The following questions are guiding:

RQ1: What gender differences can be identified in access to volunteering in sport and in taking on leadership positions in Germany? What trends are emerging?

RQ2: Which variables predict (a) women's volunteering and (b) women's likelihood of taking on a leadership position and to what extent do differences with men emerge?

RQ3: What differences in (a) volunteering and (b) leadership positions can be identified in subgroups of women (as opposed to men)?

In order to be able to analyze the unequal access to volunteering and leadership positions in sport, reference is made to inequality theory and intersectional approaches. The process model of Solga et al. (2009), with four structural levels of social inequality, can be used to theoretically discuss the unequal access to volunteering by women in sport and the resulting consequences (e.g., on opportunities for social and societal participation or on the generation of social capital). It provides a structuring scheme for the state of research and enables the disclosure of existing research gaps. On the input side, there are the so-called (1) determinants of social inequality, which lead to social inequality in different (2) dimensions through (3) mechanisms on the output side that need to be defined in more detail, which in turn are associated with certain (4) consequences (see Figure 1).

In our contribution, volunteering is considered to be a dimension of social inequality. At the same time, sports clubs as organizations provide a context for the genesis and reproduction of social inequality (Rameder, 2015).¹ The unequal access to voluntary work for women and men and gender-specific forms of voluntary engagement are examples of horizontal gender segregation. Gender differences in leadership positions in sports clubs are an example of vertical gender segregation. The empirical finding that men are more likely to volunteer than women is initially only evidence of heterogeneity. Attention must also be directed to the consequences of unequal access in order to identify social inequality. Positive consequences of volunteering could be the generation of social capital (Putnam, 2000; Braun, 2007), the acquisition of skills (Heckman et al., 2006; Ruiter and De Graaf, 2009) or an increase in subjective wellbeing (Wicker and Downward, 2019).

Gender, class, immigration status, age and family status, among others, are conceived as determinants of social inequality. Belonging to these social groups is the basis for advantages and disadvantages in certain conditions of action and life (Solga et al., 2009). Gender differences in volunteering have already been reported. Class or access to various socio-economic and cultural resources such as paid employment, income and education are discussed as determinants of access to volunteering. There is relatively consistent evidence of a middle-class bias in volunteering (Rameder, 2015; Meusel, 2016; Simonson et al., 2022a). Moreover, previous findings suggest that immigrants are less likely to volunteer than non-immigrants (Rameder, 2015; Simonson et al., 2022a). Age differences in volunteering are also empirically documented. People between the ages of 30 and 49 are the most likely to volunteer (Simonson et al., 2022a).

Rameder (2015) suggests statistical disadvantage, the principle of homophily and the “Matthew effect” as examples of inequality-generating mechanisms. Statistical disadvantage occurs when decisions about individuals are made on the basis of behavioral assumptions regarding entire social groups (Solga et al., 2009). For example, association officials may believe that women are less flexible than men in terms of time due to household and childcare responsibilities. The principle of homophily can be defined as the tendency of people to seek out or be attracted to others who are similar to them. In this respect, contact between similar people occurs more frequently than between dissimilar people (McPherson et al., 2001). A distinction is also made between status homophily and values homophily. For example, it might be much more difficult for women of color to volunteer in a sports club that is strongly dominated by white men. The Matthew Effect or cumulative (dis)advantage is a general mechanism for inequality in any temporal process, such as in the life course, where a favorable relative position becomes a resource that generates further relative gains (DiPrete and Eirich, 2006). For example, men may accumulate more advantages than women. Flexible careers and part-time employment of women due to child-rearing and unpaid domestic care could lead to further disadvantages, e.g., in the pension system or also in filling voluntary positions. The causes or concrete mechanisms of social inequality must be specified and named in the respective empirical study (Solga et al., 2009).

Volunteering is defined as engagement that is (1) voluntary and (2) not aimed at material gain. The commitment (3) is oriented toward the common good, (4) takes place in the public sphere and (5) is usually carried out on a joint/cooperative basis (Enquete Commission, 2002). However, volunteering is also a specific form of work, since goods or services are produced in connection with an organization outside the household (e.g., in a sports club). While gainful employment is paid, voluntary work is unpaid. Volunteers may receive a small expense allowance (Meusel, 2016; Kelle et al., 2021).

The explanatory variables used in the analyses are the respective indicators for the ascribed features of gender, age and immigration status, as well as for the acquired features of level of education, employment, income and family status (Table 1).

Given the complexity of volunteering in modern societies, the inequality theory approach is only one possible approach. Different theories should thus ideally be linked (e.g., Einolf and Chambré, 2011). We therefore integrate further context variables and personality features into our investigation, which have proven to be relevant in previous studies on volunteering in sports (Schlesinger and Nagel, 2013; Hallmann, 2015; Wicker, 2017) and on volunteering in general (Clary et al., 1998; Musick and Wilson, 2008; Hustinx et al., 2010). Region, years of residence, voluntary work in other areas, level of neighborhood cohesion, support from others and health status of respondents are included as control variables in all analyses. In order to predict leadership positions in sport, motives, information about impulse givers and necessary skills are additionally used as control variables (Table 1). The latter were only asked of volunteers.

At the end of the 1990s, the German government had a survey-based information system implemented that was intended to provide a representative empirical picture of volunteering in Germany over time. The goal of this system was to (further) develop a social strategy for promoting civil society on the basis of comprehensive data. A broad-based population survey was designed, which began in 1999 and has since been conducted five times. On the basis of the German Survey on Volunteering, it is possible to examine the scope and structure of voluntary engagement in the sports sector—in sports clubs as well as in self-organized projects and initiatives—on a cross-sectional basis, to map changes on a longitudinal basis and to discuss challenges faced by sports clubs with regard to human resources in the provision of services. The corresponding survey results have become an important tool for policy advice, especially in the field of “engagement policy”.

A large number of application-related problems played a relevant role in the conception of the German Survey on Volunteering and the construction of the corresponding survey instruments. Theoretical conceptualizations are therefore rather marginal. The process model of Solga et al. (2009) is intended to contribute in a pragmatic way to structuring and classifying the topics and variables of the German Volunteer Survey, to integrating existing findings and to guiding one's own empirical analyses. At this point, the limitations of the survey should be pointed out. For example, no information was collected on the respective organization (e.g., size of the club, sports offered, club goals and culture, socio-structural composition of the members). Nevertheless, the socio-structural characteristics of the respondents were asked in detail so that socio-structural analyses could be carried out.

Due to some fundamental methodological changes (Simonson et al., 2022b), our paper mainly analyses the results for volunteering in sport from the 2014 and 2019 waves. Older data are only used to describe long-term trends toward gender equality. The datasets are considered representative of the population of the Federal Republic of Germany regarding the characteristics of age from 14 years, gender, federal state and municipality size, class and education. The sample allows analyzing individual fields of action (e.g., the area of sport) and individual population groups (e.g., women and men).

In 2014 and 2019, computer-assisted telephone interviews (CATI) took place both via landline and mobile phone. In the landline interviews, the target person was selected from the household using the last-birthday method. In the cell phone interviews, the person who primarily uses the phone was interviewed (Simonson et al., 2017, 2022c). In 2014, the proportion of people contacted (N = 148,668) who took part in the interview was 21.3% (N = 31,600) or 19.3% (N = 28,690) based on the fully realized and analyzable interviews (Simonson et al., 2017). In 2019, 21.1% (N = 31,454) took part and 18.6% (N = 27,762) of 149,053 contacts resulted in analyzable data (Schiel et al., 2020). The response rate is similarly low as in other telephone surveys (Engel et al., 2012). In both waves, the main reasons for drop-out were refusal to participate on principle, lack of interest in the topic of the study or interviews in general and the length of the interview (Schiel et al., 2020). Distorting factors in the composition of the sample (e.g., a disproportionate sampling according to region) and unequal participation probabilities (e.g., according to age) were compensated by weighting. Weighting was based on the characteristics of federal state, community size class depending on the number of inhabitants and the population and job density (Behrens et al., 2019), gender, age group and school education (Simonson et al., 2022c). Data collection, data checking and weighting were the responsibility of the Institute for Applied Social Science (infas). The empirical analyses are based on the adult sample (18 years and older) because the study examines the roles of employment and the presence of children in the household as possible determinants of social inequality. Due to the age-related case selection, the sample size differs between the unweighted and the weighted sample (Table 2).

The following analyses focus on the one hand on the overall sample (Table 2) and on the other hand on the subsample sport (Table 3). The subsample consists firstly of the women and men who volunteer in the field of sport and physical activity. Secondly, we will look at the subgroup that spends the majority of their total volunteer time on sports-related activity and holds leadership positions there.

The data were processed and analyzed in the statistical software IBM SPSS 25.0. In a first step, descriptive characteristics are calculated and statistical tests are conducted to identify gender differences. The analysis was carried out depending on the measurement level of the variables, in the case of categorical variables using contingency tables (cross-tabulations) and Chi²-Tests or in the case of metric variables t-tests. The longer trends (1999–2019) in terms of changes in the proportions of women and men volunteering or taking up leadership positions in sport (RQ1) are only presented descriptively due to the reported methodological problems. The changes between 2014 and 2019 are examined in the regression analyses.

To be able to answer the second question on the prediction of access to volunteering in sport and taking up leadership positions, binary-logistic regression models are calculated with the determinants of social inequality as predictors, controlling for contextual and personality features. To examine how gender and other variables jointly affect volunteering and the distribution of leadership positions, interaction effects were included. Appropriate prerequisites were previously tested and multicollinearity analyses were conducted. Ignoring the interactions, all of the correlations between the predictors are less than the threshold of r = 0.80, which is often used in regression analysis (Urban and Mayerl, 2018).

In 2019, 11.5% of women and 15% of men volunteered in sports. Women and men volunteer primarily because it is fun, they want to get together with other people, they want to help other people and influence society. Power and influence, as well as earning extra money, play a much smaller role. Women differ from men in their respective approval ratings. They agree more strongly with the former reasons, while they agree with the latter reasons less often than men (Table 4). Differences between survey dates are marginal.

In about 43% of cases, the initiative to take on the voluntary work came from the volunteers themselves (women: 42.3%; men: 43.9%). Just over half of the respondents indicate that the impetus came from leaders within the club or group and in just as many cases the impulse came from family members, friends or acquaintances who were already active there. Family experiences—and as a tendency this applies also to family members, friends or acquaintances—are indicated more often from women as impetus, whereas voluntary service and the employer were more important for men (Figure 2).

From a comparative gender perspective, the reasons people who are active in sports do not take on voluntary work are also interesting. Most respondents overall, and women a little more often than men, consider time reasons to be decisive, while professional reasons are frequently cited by both sexes. Moreover, women mention family reasons and health reasons more often than men and state more often that they do not want to take on any commitments (Figure 3).

With regard to the volunteers with the most time-consuming voluntary activity in sports, there are more similarities than differences between women and men in the content of their activities (Figure 4). Practical activities, the organization and implementation of (sporting) events and personal help are mentioned particularly frequently. Men state more frequently than women that they take care of fundraising and administrative activities and that they perform consulting services.

In 2019, women named families significantly more often than men as a special target group for their volunteer work. In 2014, this applied to families and also to older people, people with a handicap and people who need help or care. In 2014 and 2019, women were more involved with women and men more with men (Table 5).

In 2014 and 2019, 84.1% of the women and 87.6% of the men with the most time-consuming voluntary activity in sports are involved in (formal) sports clubs. Women spend an average of 3.0 h and men more than 4.2 h per week on their most time-consuming voluntary activity. Men have been doing this for an average of 12.1 years, women for 10.2 years.

Trend analyses of the German Survey on Volunteering show that women have caught up with men in terms of the proportion of people volunteering. Whereas, in 1999 6.4% of women were volunteering in sport, 20 years later the figure was 11.5%. The proportion of volunteers among men was 14.2% in 1999 and 15.0% in 2019, with major fluctuations in between (Figure 5). Some methodological changes were made to the Survey in 2014, so trends in volunteering before and since 2014 should be considered separately. However, the reduction in gender differences in 2019 is due to the lower proportion of engaged men.

Women continue to be underrepresented in volunteer leadership positions in sport. The gender gap was around 15 percentage points before 2014 and around 10 percentage points since 2014, to the disadvantage of women in leadership positions (Figure 6).

Table 6 shows the results of the regression analyses examining the predictors of volunteering. Almost all in Model 1 included variables—operationalized as determinants of social inequality—contribute significantly to the prediction of access to volunteering. Model 1 contains only the main effects. The proportion of explained variance is rather low at 14.2%.

To examine how gender and other variables jointly affect volunteering, interaction effects between the gender variable and the other variables were included in Model 2. The results show that part-time and marginal employment are more likely to be associated with volunteering among women than among men (Tables 6, 7). However, the likelihood of volunteering decreases more for women than for men when they are not employed at all. Moreover, higher income for women is less likely to be associated with voluntary work than it is for men, while volunteering in other areas is more likely to have positive effect on volunteering in sports for women than for men. Compared to Model 1 the proportion of explained variance increases only slightly to 14.5% by adding interaction effects. The odds ratios for the significant interaction effects are rather small.

In order to find out which variables (in addition to socio-structural characteristics) predict a volunteer leadership position in sports, motives, requirements and impetus for volunteering are used, among others (Table 8). For these analyses, only those who perform their most time-consuming voluntary activity in sports are included. Model 1 contains only the main effects. The proportion of explained variance is rather low at 13.6%.

Again, Model 2 contains interaction effects. When predicting leadership positions, considering interaction effects has a greater impact than when predicting volunteering. The increase of explained variance to 15.4% and the odds ratios for the significant interaction effects are higher. This suggests that gender differences as a function of other variables are larger for leadership positions than for volunteering. Here, the scope of employment seems to be of particular importance. Part-time and marginal employment increases the likelihood of having a leadership position to a greater extent for men than for women whereas it is the other way around for volunteering. In the context of leadership positions, men benefit more than women if there are no children in the household. Furthermore, women seem to be moving more into leadership positions, if they have the impression that specific training is necessary for voluntary work and that social skills can be acquired through voluntary work. Getting the impetus to do voluntary work from family or friends worsens the odds of occupying a leadership position more significantly for women than for men (Tables 8, 9).