Musical work and its tempi. Some thoughts from the Belgian case

Pierre Bataille, University of Lausanne
Louise de Brabandère, Université Libre de Bruxelles

Eliezer Pedroso, Allegro,, CC

From political discourses to scientific journals, the “gig economy” is everywhere. This buzzword is most of the time used to present the degradation of working and employment conditions within contemporary capitalist economies in a “positive” perspective  (Cloonan and Williamson, 2017), i.e as an opportunity for workers to experiment more freedom in their work relations, like musicians jumping from one project to another would do. Mainly motivated by ideology, such analogy comes from a misleading representation of what working as an independent musician really means. It does not take into account how far musical activity is shaped by institutional contexts and framed by social inequalities. Using the case of Belgian musicians, we would like to contribute to building a more accurate understanding of the working conditions of musicians in contemporary capitalist societies [1]. More precisely, since the fragmented nature of the activity seems to be one of the common points between musicians and workers in the era of “platform capitalism”, we present an in-depth analysis of the musical activity pace. By providing better knowledge of the concrete organization of musical work, we aim to suggest some insights to better understand the contemporary work and employment conditions in the era of the advanced de-regularization of many labor markets.

Thanks to the Smart cooperative, we had access to fine-grained data on the musical activity in 2016 of a large Belgium-based musicians’ sample (N= 2794). With more than 85 000 members, the Smart cooperative is one of the main companies that take charge of administrative work for freelance/atypical workers in Belgium [2]. It was founded in 1998 by individuals involved in artistic employment management in order to facilitate dealing with specific issues of artistic work (fragmentation of the activity, undetermined relationships with employers…). Presently, the cooperative admits members who work as freelancers in a large range of sectors such as journalism, catering, and healthcare.

Three main questions will underpin our contribution. Is musical professional activity fragmented to the same extent for all musicians? How much does the pace (or tempi) of musical work vary among musicians? How do these variations reflect the inequalities that shape the musical workplace?

A fragmented and unevenly remunerative activity

The highly fragmented nature of artistic activity is well known. Among the three main performing arts (theatre, dance, music), the activity of musicians without a stable work contract is perhaps the most discontinuous. Indeed, since rehearsals are almost never paid – except in cases of collaboration with theatre or dance -, the duration of the employment is generally limited to that of the performance. It rarely exceeds the day. Figure 1 points out this extremely fragmented nature of musical work in Belgium.

Figure 1: Dispersion (%) of the daily duration of work contract declared via Smart by musicians in 2016

The working time per contract does not exceed one day in more than 75% of the musical services. It must be noted that here we only have access to official statements. It is likely that for many of the Smart members concerned, the benefits coded here as one day’s work represent, in fact, different rewards of a few hours groups together, in order to satisfy legal forms of work declaration.

With Smart data, the employer activity sector can be identified for almost 50% of the work declarations. We can thus analyze whether non-musical activities are located in the field of culture or not. This distinction is fundamental. For musicians who work in the cultural field – those who are in a situation of “pluriactivity” (Bureau, Perrenoud and Shapiro 2009) – their implication in nearby professional spheres allows the transfer of resources such as social network and cultural capital from their core activity to their secondary ones. Whereas musicians who work outside the cultural field – those practicing “multi-activity” – such transfers are less likely. As such, non-musical activities may represent an obstacle to a full commitment in the musical career, rather than the musicians being able to exploit resources accumulated through musical activity in a different professional space and vice versa.

For non-musical services in the cultural sector, work declarations of musician members of Smart last most frequently two or three days, but are rarely longer than five days (only 10%). The lengths of contracts for non-musical and non-cultural work follow the same trend as non-musical services in the cultural field. The large dispersion of incomes within the artistic sphere is a well-known phenomenon. In this winner-take-all economy (Menger 1999), the income pyramid is bottom-heavy and only a very small group of workers can make their way to the top. Figure 2 gives an idea of the large dispersion of incomes, even within musician members of Smart. It also points out the impact of gender on the income generated by members’ activities.

Figure 2: Dispersion (%) of the daily amounts of work contracts declared via Smart by musicians in 2016

In Figure 2.A, the concentration of work engagement partly or totally outside the cultural sector in the lower income class is striking. Just over 40% of these services do not generate more than fifty euros (taxable) per day. For most of the musical performances, the daily amount is around 100 euros. A small number of services (10%) are paid more than 200 euros a day. Performances in the cultural but not necessarily musical field follow more or less the same distribution.

These initial findings call for two main observations. First, the low income generated by services in the non-cultural sectors suggests that these activities that supplement artistic work and incomes are relatively degraded or not very prestigious – and thus potentially represent a source of tension and disillusionment for those in a multi-activity situation. Nevertheless, since we only have information on the services reported via Smart, a large part of the members’ potential activity stays out of our sight. Thus, the scope of the comparison between the different types of services analyzed here is necessarily very modest.

Looking at the dispersion of the daily income regarding the employer’s sector and the sex of the members (Figure 2.B), we see that the median taxable income per day is 80 euros for men’s musical performances and 93 euros for women. This slight advantage for women – which is also noticeable in non-musical cultural labor – reflects a greater asymmetry in the distribution of women’s income and, ultimately, greater inequalities among women than among men. This difference is partly explained, as we will see later, by the fact that the few women who stand in the musical professional career path often play music in professional spaces combining several types of artistic disciplines such as dance and theater. What is more, such spaces are more often (and better) subsidized than the institutions that strictly broadcast non-classical music.

Two activity peaks

Going further in these general observations on the fragmented nature of musicians’ professional activity, we can consider, on a one-year scale (in 2016), the distribution of Smart’s musicians’ performances (Figure 3).

Figure 3: Rhythm of musical performances declared via Smart in 2016

Considering both musical and cultural work declarations, we notice a peak of activity in May and September. Almost a quarter of the year’s performances are billed during these two months. For both types of engagements, there is also a low point during the summer period. It remains difficult to determine whether the variations identified reflect variations in the intensity of musical and artistic activity or if they are an artifact reflecting the reporting strategies and practices of Smart members. More than an increase of musical activity at the beginning of the school year, we could assume that the September peak shows the accumulation of work declarations for services during the summer period – when administrations are operating at a slower pace.

Nevertheless, it can be argued that the drop of activity in summer reflects the dependence of Smart’s musicians’ activity on the opening seasons of the regular venues, which have a break in their program over the summer period. This, as opposed to festivals, for instance, most of which have their activities highly concentrated in June, July and August. The variations observed here suggest that summer festivals, although numerous and quite popular as shown by the analysis of interviews with Belgian musicians (de Brabandère, 2018), are far from being the main source of remuneration for most musicians. Rather, these variations point out that, consistent with what is observed in other countries  (Titan Group 2015; Webster and al. 2018), it is the preservation of a network of sustainable venues, where live music can be heard once or several times a week, that provides the best job security for ordinary musicians – i.e  the ones, neither rich or famous, who live or try to live from their musical activity (Perrenoud 2007).

Three main patterns of musical activity

While Figure 3 provides a useful overview of the changes of intensity in Smart musicians’ activity throughout the year, it disregards the significant inter-individual variations that exist within this population. Thus, it should be recalled that nearly 30% of the members whose services we are analyzing here declared only between 1 and 5 work contracts in 2016. On the other hand, 30% of them have declared more than twenty contracts. For a more detailed view of these variations of musical work pace, we analyzed the intensity of activity per month in 2016 for each member identified as a musician. Using sequence analysis tools (MacIndoe and Abbott 2006), these individual sequences can be assembled into different groups (clusters) based on their relative similarity/dissimilarity. Figure 4 shows these different sequence clusters. Maintaining eight groups is the most efficient approach from a statistical point of view and the most meaningful from a descriptive point of view.

Figure 4: Typology of individual sequences of musical activity

Three principles that structure the tempi of Smart members’ annual musical activity emerge here:

  1. The most salient is that of continuity of musical activity throughout the year, which opposes clusters 1, 2 and 3 (where activity takes place in almost every month of the year) with clusters 4 and 5 (where musical activity is very occasional) and, to a lesser extent, with clusters 6, 7 and 8 (where musical activity is concentrated only at certain times of the year).
  2. The intensity of musical activity is the second principle of differentiation. It distinguishes cluster 1 from all others, as the members of these very rarely report more than 5 days of monthly activity.
  3. The seasonality of musical activity is the third and last principle. It opposes clusters 6, 7 and 8 to each other, depending on whether musical activity is concentrated during the summer period (cluster 6), spring (cluster 7) or autumn (cluster 8).

We can thus distinguish three main types of profiles here:

  1. The full-time musicians (clusters 1, 2 and 3), who represent 28% of the Smart members we have identified as having a musical activity. Nevertheless, within this first type, a small group (cluster 1, 6.9%) stands out for the intensity of its musical activity, and regularly declaring 10 or more days of musical work per month.
  2. The occasional musicians (clusters 4 and 5), who report musical activity via Smart only occasionally and who represent 40.8% of our target population. However, even if the quantity of declared activities is sometimes very low, as in cluster 5, it would nevertheless be sufficient for renewing one’s “status” consisting of adjustments to unemployment benefits for artists in Belgium for those who have already had this recognition previously. Therefore, musicians with little or no experience are mixed here with experienced but not very active musicians during the year under study.
  3. The seasonal musicians (clusters 6, 7 and 8), who have their activity concentrated in a specific period of the year and who represent 31.1% of Smart’s musicians.

When the activities tempi reveal the social structure of the musical professional space

To further refine the analysis of these different profiles, let’s have a look at how the non-musical performances of musicians are distributed as regards to the cluster to which they belong (Figure 5).

Figure 5: Dynamics of non-musical performances in 2016 by cluster

First of all, it appears that cluster 1, comprised of full-time musicians, is also the cluster where members have the least declared days of engagements in non-musical sectors. For both the clusters representing occasional and seasonal musicians, the proportion of people regularly reporting work days of non-musical performances is somewhat higher – especially among cluster 5 members. This proportion slightly varies over the year, which can be partly linked to variations in musical work intensity.  However, it rarely exceeds 10% in all cases. This suggests that, especially for members in clusters 4 and 5, the benefits declared via Smart are not their only means of living. They probably have other occupations – more regular work such as a day job – or declare their artistic activities through other channels. The physiognomy of the cluster 4 members’ activity suggests a “music festival” effect, which constitutes – for instrumentalists who are less active or inactive the rest of the year – an opportunity to perform on stage without necessarily professionalizing their musical practice.

To specify the professional and social profiles of the different work paces, for each cluster we can focus on the sectors of the labor market in which musicians evolve and on the distribution by age and by sex within them (Figure 6).

Figure 6: Sequences typology and member profiles

First, Figure 6.A points out a polarization within the group of full-time musicians (clusters 1, 2 and 3). The cluster 1 musicians, the most active in terms of the number of days worked per month, are also those whose activity is mainly part of the artistic and cultural pole, as nearly 60% of their employers are located in this sector. When they declare a non-musical performance, it is, in more than half of the cases, in the cultural sector. Teaching is their second source of non-musical income, although it should be noted that the number of non-musical services reported by the people in this cluster is very low. It is in this particular cluster that musicians who only practice music in the cultural sector are concentrated. Among musicians in clusters 2 and (especially) 3, one can also count many work engagements within the cultural sector, but it is in these two groups that the proportion of employers with a foot in the entertainment sector is higher, compared with the cluster 1 musicians. Musicians of these two clusters are closest to bearing the profile of musicians playing on demand: “functional musicians” (Umney 2017) or ones seen as “craftsmen” (Perrenoud and Bataille 2017).

Among the occasional musicians (clusters 4 and 5), we see that when individuals declare a non-musical performance, it is often for an employer within the film or television sector. It can thus be assumed that, in addition to musicians with very low intensity activity throughout the year, these two clusters also include people with activities in sectors where music is produced, but where on-stage performance is not the core trade.

Concerning musicians with a seasonal activity (clusters 6, 7 and 8), the majority of their musical performances are located within the cultural sector. Like the musicians of clusters 2 and 3, however, their employers also have activities in the teaching or entertainment sectors.

Nevertheless, the proportion of employers affiliated with entertainment never reaches the same proportions as for cluster 3. Furthermore, we can assume that these musicians – whose activity is seasonal – either do not have access to professional entertainment circuits, which could help them increase their activity, or partially select their work engagements in order to keep an in-between. That is, trying to collect enough fees to claim access to unemployment schemes, while avoiding as much as possible situations of work considered too alienated because too closely linked to the entertainment sector.

From a gender perspective, it is clear (Figure 6.B) that the clusters with the most “integrated” musicians (1, 2 and 3) are among the least feminized. Women are also few amongst musicians who are mainly active in the summer (cluster 6). This reflects a concentration of women musicians at the margins of the core of the professional group – a trend already underlined by many works on the gendered structure of the professional sector of popular music and its performers (Buscatto 2017; Reddington 2016).

Finally, an analysis of the configuration of these clusters according to age (Figure 6.C) shows that those where musicians are the most active (clusters 1, 2 and 3) are also those with a mean age of 35-40 years – a little higher than in the other clusters. For most of the other cases, the 30-35 age group is the most significant. These results confirm the hypothesis that the intensity of musical activity is closely linked to a long-term integration into dense professional networks, and is the result of a relatively long process of stabilization in the professional field (Coulangeon 2004). This could indeed explain why musicians aged 35-40 are over-represented in this first set of clusters. This intensity of musical activity declared via Smart among these slightly older musicians also points out that the longest and/or most regular contracts are first and foremost obtained by the most experienced musicians, with the youngest or newcomer musicians more often experiencing the most degraded forms of musical employment.


Thanks to a fine-grain analysis of musical activity tempi, we identify differences within musicians as regards to musical activity and work concentration. Our short vignette on Belgian musicians points out the variety of their working conditions. This heterogeneity provides arguments against the casual use of the “gig economy” metaphor and calls for a more fine-tuned analysis of work conditions across all sectors. Indeed, most of the musicians have a highly fragmented activity. Nevertheless, the matter and the tempi of this activity strongly vary according to the activity sector and the socio-professional profile of the musicians studied.

As in many other national cases (Umney 2016; Perrenoud and Bataille 2017; Silva 2017; Moyano 2017), our analyses point out that the professional activity of “ordinary”[3] musicians is caught between those who are rooted in the “cultural” sector – who are considered both by themselves and others as artists – and more “functional” activities in music  (Umney 2017), where musicians have to act as service providers, as craftsmen who “do the job” more than perform their artistic singularity (Perrenoud 2007).

The identification of these fragmentation lines within the musicians professional group highlights the ambivalence of music production within capitalist societies. In this, it also points out the difficulties of establishing common regulations, adapted to each of the different types of musical practice. But it is paradoxically by having the most accurate representation of these differences that collective action is possible. And let us dare imagine that the reflections initiated here and by many members of the WIM network will favor such a dynamic.


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[1] This is a translation from French of the following chapter by the authors in an edited book: Bataille, P., & de Brabandère, L. (2019) “La musique de Smart”, in C. Virone (ed.), Musicien‧ne : quelques réalités du métier, 21–40, Bruxelles: Smart.
[2] For more information, see
[3] For more on the concept of “ordinary” artists, see Perrenoud and Bois  (2017).

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