Groups and Biases: The Role of Social Identity in the Musical Career Path Aspirations of Adolescent Musicians

Abstract

According to social identity theory, individuals self-categorize into groups and then differentiate between groups based on stereotypical norms to create a perceived hierarchy to benefit their self-esteem. The purpose of this study was to explore the presence of social identities among adolescent musicians related to the career paths of music performance and music education and to determine whether self-categorization and differentiation regarding these career paths were a feature of these social identities. Participants were 821 adolescent musicians of varying experience and backgrounds. Results indicated that participants self-categorized and differentiated in favor of the music performance career path but allocated hypothetical resources in favor of the music education career path. Age, family income, performance setting, and intention to major in music were significant predictors of self-categorization, differentiation, and resource allocation. These findings indicate that participants who were older, had greater financial means, identified as soloists, or intended to major in music were more likely to be aligned with a music performance social identity.

Keywords

social identity theory adolescence music education music performance bias

High school and undergraduate students pursuing a career in music have indicated that performance-based experiences during adolescence were impactful to that choice (Jones & Parkes, 2010; Parkes & Jones, 2011; Rickels et al., 2019). Because performance-based offerings are far more available to adolescents than nonperformance music offerings, such as courses in music history and appreciation (Haning, 2016), and large performing ensembles dominate secondary music curricula (Matthews & Koner, 2017), it is logical to conclude that performing is central in the lives of adolescent musicians. This centrality of performance continues beyond adolescence, as evident in music teacher socialization—a body of work that addresses the negotiation of this initial performer identity with an emerging teacher identity among undergraduate music education students (Draves, 2012; Isbell, 2008, 2015; Lesniak, 2005; Roberts, 1991; Woodford, 2002). The negotiation of teacher and performer identities is complicated by negative bias directed toward music education students as a group, which often pertains to perceptions of their performance abilities (Ellis, 1999; Sieger, 2012), nonperformance-based curricular responsibilities (Conway et al., 2010), and placements in ensembles and private studios (Albert, 2016; Ryan, 2010).

According to social identity theory (Tajfel & Turner, 1979), bias is created to improve or preserve the self-esteem of group members by increasing the differentiation between groups in a perceived hierarchy. Central to the theory is the broad definition of a group; as few as two people may be considered a group as long as they consider themselves and each other members of the same group, and individuals may self-categorize as a member of a group upon becoming aware of its existence and the typical characteristics of its members. Although individuals may self-categorize as members of several groups simultaneously (e.g., sexual orientation, gender expression, hair color, political affiliation, career path), social identity and membership associated with any group “need not depend on the frequency of intermember interaction, systems of role relationships, or interdependent goals” (Tajfel & Turner, 1979, p. 40) and represent “those aspects of an individual’s self-image that derive from the social categories to which he perceives himself as belonging” (Tajfel & Turner, 1979, p. 41). According to social identity theory, once membership in these groups is established, bias toward other groups ensues and serves to increase the differentiation between groups. In order to study this bias, Tajfel created a “minimal group paradigm” (Hogg, 2016, p. 5), in which the allocation of resources was studied between groups formed using arbitrary criteria or even random assignment. Regardless of the level of group identification or stakes associated with the resource allocation, Tajfel and Turner (1979) found bias to be a consistent feature in the relationships between groups. The work of Tajfel was continued by Turner, who researched the act of self-categorization. Turner discovered that social identity and group membership do not exist in a binary state of in or out but that “variations in the salience of social categorizations can have marked effects on attitudes and behavior” (Oakes & Turner, 1986, p. 326). Salience is a combination of accessibility, which is the extent that a social identity was prominent in a person’s life, and fit, the extent to which that person observes similarities between themselves and the stereotypical image of that social identity. These two aspects of salience explain how multiple or conflicting group memberships and associated social identities can be held by an individual and exist along a continuum independent of external validation of membership.

Social identity theory has been used to understand the role participation in music plays in adolescents’ identity development. North and Hargreaves (1999) indicated that music serves as an implicit “‘badge’ which conveys information about the person who expresses a particular preference” (p. 77) for a genre of music. Hoffman (2008) found that middle school band students had an understanding of how their social standing was negatively impacted by their membership, and in some instances, this perceived impact led to a decision to not enroll in band for the next year. Similarly, adolescents have been shown to be aware of a range of external perceptions about their involvement in music, and those perceptions have impacted the value they placed on their experiences (Marra, 2019). Parker (2014, 2018, 2020) found that musical involvement had positive impacts on the social identity of adolescents but also documented tension and biases among groups of adolescent musicians.

These tensions and biases have also been documented between groups of undergraduate musicians. For example, music education majors have reported feeling excluded by other music majors (Conway et al., 2010) and that despite their performance abilities, their major “carried a negative stigma” (Conway et al., 2010, p. 269). Some felt they were less valued by performance faculty due to their major (Albert, 2016). Ellis (1999) noted that this perception was reinforced when private lesson faculty encouraged performance majors to add a music education major only when they demonstrated a lower performance ability. Students enrolled in a double major of music performance and music education reported being treated as substandard musicians due to their music education major and viewed as condescending due to their performance major (Sieger, 2012).

Although bias among undergraduate musicians (Albert, 2016; Conway et al., 2010; Ellis, 1999; Sieger, 2012) and the impact of musical participation on the social identities of adolescents have been documented (Hoffman, 2008; Marra, 2019; Parker, 2014, 2018, 2020), the development of bias against and for musical career paths among adolescent musicians has not been explored. The purpose of this study was to investigate the presence of social identities among adolescent musicians related to the career paths of music performance and music education and to determine whether self-categorization and differentiation regarding these career paths are a feature of these social identities. We posed the following research questions: (1) To what degree do adolescent musicians self-categorize and differentiate according to a music educator or music performance social identity? and (2) What are the relationships between the self-categorization and differentiation of adolescent musicians and their demographic characteristics?

Method

We designed an online questionnaire to assess the social identity of adolescent musicians regarding the career paths of music education and music performance. Because private lessons, honor ensembles, and music camps have been shown to be common experiences among those pursuing careers in music (Jones & Parkes, 2010; Parkes & Jones, 2011; Rickels et al., 2013), we began the sampling process by identifying 76 institutions and organizations that provide such opportunities to adolescent musicians. These institutions and organizations included community music schools, youth orchestras, music camps, competitions, state-sponsored honor festivals, and both public and private music-focused high schools. One state-sponsored honor festival and one music camp provided email addresses for 1,577 participants in their programs, allowing for direct delivery of the questionnaire, resulting in 222 of the completed responses (a response rate of 14.1%). An additional 599 complete responses came from 28 organizations whose gatekeepers agreed to forward the questionnaire to students on our behalf. It was not possible to determine a response rate for this indirect channel of data collection because not all organizations provided an estimate of how many students received the link and would have been eligible to participate. In total, 1,381 adolescents began the questionnaire, and 821 (59.5%) completed all questions.

Questionnaire

The first page of the online questionnaire consisted of assent text, an explanation of the study, length of time to complete the questionnaire, contact information, confidentiality procedures, and a link to proceed to the study that also served as an agreement to participate in the study. In the first section of the questionnaire, we asked participants to indicate their gender, grade, primary instrument, number of years of private study, type of ensemble in which they typically perform, zip code, high school’s name, and whether they intended to major in music. With the exception of zip code and high school name, these demographic characteristics were the same as those used by Henry (2015) in an exploration of career aspirations of high school musicians. We utilized the 2014 to 2018 American Community Survey (Missouri Census Data Center, 2021) to estimate median family income percentile for each participant’s zip code. We then cross-referenced participants’ public high schools with the Common Core of Data (National Center for Education Statistics, 2021) and examined online school profiles of private schools to obtain student-to-teacher ratios for each participant’s school.

To collect data regarding adolescent musicians’ self-categorization, we modified the identity-specific text prompts of a measure employed by Brown et al. (1986) to align with our study. The revised measure consisted of a subset of five statements about the music education career path and a subset of five statements about the music performance career path. These 10 positively worded statements formed the Self-Categorization Measure (SM). To collect data regarding adolescent musicians’ differentiation, we modified the identity-specific text prompts utilized by Tanti et al. (2011) to measure “evaluative bias” (p. 560) so that they aligned with our study. The revised measure consisted of a subset of five stereotypical statements about the music education career path and a subset of five stereotypical statements about the music performance career path. As in Tanti et al., the stereotypical statements about each group were culled from existing research on this topic. These 10 positively worded statements formed the Differentiation Measure (DM). Participants responded to the statements in the SM and DM using a 7-point Likert-type scale ranging from strongly disagree (1) to strongly agree (7).

The music performance and music education subsets of the SM and DM resulted in scores with a potential range of 5 to 35. Consistent with Tanti et al. (2011) and Brown et al. (1986), we computed a composite SM score and a composite DM score for each participant by subtracting the values given for the music performance subset from the values given for the music education subset. The resulting composite scores had a potential range of −30 to +30. A negative composite score indicated a social identity more strongly associated with music performance, and a positive score indicated a social identity more strongly associated with music education. A score of zero indicated a balanced social identity between these two career path groups.

We used a minimal group design adapted from Hennessey and West (1999) to assess resource allocation—an additional indicator of differentiation. Such designs involve asking participants to make decisions based on hypothetical group membership. In this study, we presented participants with a $100,000 budget to be allocated to a music educator and music performer. We told participants that the music educator and performer engaged in the same amount of work and directed them to divide the total sum into two salaries as they saw fit. We computed a composite Resource Measure (RM) score for each participant by subtracting the hypothetical salary allocation for the music performer from that of the music educator. Salaries were allocated in units of $1,000, resulting in a possible range of −100 to +100. As with the SM and DM, a RM score of zero indicated a balanced allocation of resources between the two music career paths. A negative score indicated a social identity more strongly associated with music performance, and a positive score indicated a social identity more strongly associated with music education.

We conducted a pilot study involving 25 adolescent musicians to ensure proper operation of the online survey and assess the appropriateness of reading level and length of time to complete. Participant feedback led to the inclusion of additional demographic characteristic choices but otherwise confirmed the clarity of the instrument. To validate the content of the survey instrument, we consulted with a social psychologist with expertise in social identity theory. They recommended expanding the Likert scale from 6 points to 7 but otherwise endorsed each measure as appropriate for the assessment of social identity.

Because participants’ allocation of resources to the music performer were the inverse of the allocation of resources to the music educator, typical measures of internal consistency did not apply to the RM. The SM had a high level of internal consistency (α = .87), similar to what was reported by Brown et al. (1986; α = .71). The DM also had a high level of internal consistency (α = .81), as did the measure used by Tanti et al. (2011; α = .71). Based on these reliability results, we deemed that the data from the SM, DM, and RM were suitable for further analysis.

Analysis

To address Research Question 1 (To what degree do adolescent musicians self-categorize and differentiate according to a music educator or music performance social identity?), we calculated descriptive statistics and performed a multivariate analysis of variance (MANOVA) on SM and DM scores. We treated the social identity related to career paths in music as an independent variable with two categories (music education and music performance) and the subset scores on each measure as dependent variables. Regarding the RM, we performed an analysis of variance (ANOVA) that treated the amounts allocated as the dependent variables and used the social identity associated with career paths in music education and music performance as the independent variable.

SM, DM, and RM data met the ANOVA assumption of independence, and we determined that the assumption of normality was met based on histograms and P-P plots. Given the dichotomous nature of the independent variable (music education and music performance being the only two conditions of the data), the assumption of sphericity was met. Regarding the additional associations for MANOVA, an examination of histograms and P-P plots showed no outliers, and scatterplot matrices demonstrated a linear relationship between dependent variables. We determined the absence of multicollinearity by examining the correlation among the dependent variables of the music education and music performance subset scores, which were found to be only moderately related; however, Box’s M test showed significant differences between covariance matrices of the SM and DM data. In response to this, we chose Pillai’s trace as the test statistic (V) for these measures because it is a conservative statistic that is robust to violations of homogeneity of covariance (Bray & Maxwell, 1985).

To address Research Question 2 (What are the relationships between the self-categorization and differentiation of adolescent musicians and their personal characteristics?), we employed multiple regression analyses treating each measure (SM, DM, and RM) as a dependent variable and using personal characteristics (gender, grade, school type, primary instrument, number of years of private study, type of ensemble in which participants typically perform, intention to major in music, median household income, and student-to-teacher ratio) as predictors. We created dummy variables to allow categorical participant characteristics to be included in the regression model. We then binned responses to the number of years studied, gender, instrument, ensemble type, and school type into groups of more comparable size. We checked linearity and homoscedasticity through an examination of scatterplots and P-P plots and found no violations to these assumptions. Because all variance inflation factor (VIF) values were below 10 and the average VIF was close to 1, we determined that the assumption of multicollinearity was met (Bowerman & O’Connell, 1990).

Results

Demographic characteristics of the total sample can be found in Table 1. All U.S. regions were represented, with the exception of West Virginia, Montana, and Wyoming. A majority of participants attended public schools (78.6%, n = 645), 14.9% (n = 122) attended private schools, 5.8% (n = 48) were homeschooled, and 0.7% (n = 6) were enrolled in online schools. Of those enrolled in public schools, 35.7% (n = 230) attended Title I-eligible schools. The average student-to-teacher ratio was 17.82:1 for participants who attended public schools and 8.76:1 for those who attended private schools. The average median family income percentile across participants’ zip codes was 78% (SD = 23.63%). In terms of the number of years of private study, the modal response (reported by 20% of participants) was more than 10 years, and the median response was 6 years.

Table 1.

Demographic Characteristics.

	n	%
Gender identity
Female	493	60.0
Male	300	36.5
Nonbinary/third gender	17	2.1
Prefer not to say	8	1.0
Prefer to self-describe	3	0.4
Grade
12th	259	31.5
11th	277	33.7
10th	185	22.5
9th	100	12.2
Primary instrument
String	274	33.3
Woodwinds	154	18.8
Voice	146	17.8
Piano/keyboard/organ/harp	133	16.2
Brass	85	10.4
Percussion/drumset	17	2.1
Guitar/electric bass/other	12	1.5
Primary performance setting
Orchestra	296	36.1
Soloist	246	30.0
Wind ensemble	158	19.2
Choir	100	12.2
Jazz ensemble	16	1.9
Popular music ensemble	5	0.6
Intention to major in music
Yes	409	49.8
No	163	19.9
Unsure	249	30.3

Note. N = 821. Self-descriptions of gender included “genderqueer” (2) and “two-spirit” (1).

Research Question 1

The mean of the combined data from the five music performance prompts on the Self-Categorization Measure was 26.75 (SD = 6.83), and the mean of the combined data from the five music education prompts was 22.80 (SD = 6.85), resulting in a mean difference of −3.95 (SD = 7.51). This difference in subset scores was statistically significant, V = 0.256, F(5, 816) = 56.11, p < .001, ɳ² = .256, in favor of the music performance career path. Post hoc tests revealed that four of the five pairs of prompts produced statistically significant results (Table 2).

Table 2.

Summary of Scores and Univariate Results.

	Music Performance ScoreM (SD)	Music Education ScoreM (SD)	F (1, 820)	p	η²
Self-Categorization Measure
I am a person who:
considers those in this career path important	6.3 (1.1)	6.3 (1.2)	0.72	.3978	.001
identifies with other people who pursue this career path	5.3 (1.7)	4.5 (1.7)	156.29	<.0001	.160
feels strong ties with this career path	5.2 (1.7)	4.2 (1.8)	220.73	<.0001	.212
is glad to belong to this career path	5.2 (1.7)	4.3 (2.0)	153.97	<.0001	.158
sees myself as belonging to this career path	4.7 (1.9)	3.6 (1.9)	236.98	<.0001	.224
Composite results	26.75 (6.83)	22.80 (6.85)	56.11	<.0001	.256
Differentiation Measure
Members of this group are excellent musicians	6.3 (1.0)	5.5 (1.2)	298.60	<.0001	.267
Members of this group intend to perform (teach) because:
they love sharing music with others	6.3. (0.9)	6.3 (1.0)	0.09	.7672	.000
they enjoy practicing alone (working in front of others)	4.9 (1.3)	5.6 (1.1)	188.95	<.0001	.146
they love performing for their community or audience (teaching their students)	6.1 (1.1)	5.8 (1.2)	35.96	<.0001	.050
members of this group continue to grow artistically throughout their career	6.7 (0.8)	6.0 (1.3)	174.97	<.0001	.229
Composite results	30.26 (3.39)	29.19 (4.24)	138.35	<.0001	.459
Resource Measure	$48,640 ($9,270)	$51,360 ($9,270)	17.39	<.0001	.021

Note. N = 821. Scores were gathered using a Likert scale in which 1 = strongly disagree and 7 = strongly agree.

The mean of the combined data from the five music performance prompts on the DM was 30.26 (SD = 3.39), and the mean of the data from the five music education prompts was 29.19 (SD = 4.24), resulting in a mean difference of −1.07 (SD = 3.85). This difference in subset scores was statistically significant, V = 0.459, F(5, 816) = 138.35, p < .001, ɳ² = .459, in favor of the music performance career path. Post hoc tests revealed that four of the five pairs of prompts produced statistically significant results (Table 2).

The mean amount allocated to the music performer in the RM was $48,640 (SD = $9,270), and the mean amount allocated to the music educator was $51,360 (SD = 9,270), resulting in a mean difference of $2,730 (SD = $18,730), in favor of the music education career path. This difference in allocation of resources was statistically significant, V = 0.021, F(1, 821) = 17.39, p < .001, ɳ² = .021 (Table 2).

Research Question 2

The regression model in which participant characteristics served as predictors of the SM scores was statistically significant, F(24, 796) = 3.51, p < .001, R = .31, explaining 9.6% of the variance in the SM scores. Nine of the predictor variables were significant in the model (see Supplemental Table S1 included with the online version of this document for full regression results).¹ Participants who identified their main performance setting as choir were predicted to score 2.73 points higher on the SM than those who identified their main performance setting as soloist (p = .030). Those who did not intend to study music were predicted to score 2.88 points higher on the SM than participants who did intend to study music (p < .001). Participants in ninth grade were predicted to score 2.18 points higher on the SM than 12th-grade participants (p = .017). Those with less than 1 to 3 years of private study were predicted to score 2.06 points higher on the SM compared to participants with 10+ years of private study (p = .016). Participants who indicated they were unsure about their intention to major in music were predicted to score 2.14 points higher on the SM than those who intended to major in music (p = .001). Those who played woodwinds were predicted to score 1.94 points lower on the SM than participants who played string instruments (p = .046), and singers were predicted to score 4.05 points lower on the SM than participants who played string instruments (p = .002). Participants who identified themselves as male were predicted to score 1.12 points lower on the SM than those who identified themselves as female (p = .047). Finally, an increase in median family income percentile by 1 unit resulted in a reduction of 0.02 in the predicted SM score (p = .045).

The regression model in which participant characteristics served as predictors of the DM scores was also statistically significant, F(24, 796) = 2.90, p < .001, R = .28, explaining 8.0% of the variance in the DM scores. Five of the predictor variables were significant in this model (see Supplemental Table S2 included with the online version of this article for full regression results). Participants who identified their main performance setting as choir were predicted to score 2.12 points higher (p < .001) on the DM than those who identified their main performance setting as soloist. Those who identified their main performance setting as a jazz or popular ensemble were predicted to score 2.92 points higher (p = .004) on the DM than participants who identified their main performance setting as soloist. Participants in ninth grade were predicted to score 1.34 points higher on the DM than 12th-grade participants (p = .005). Participants who attended a public school not eligible for Title I funding were predicted to score 0.65 points higher on the DM than those who did attend a public school eligible for Title I funding (p = .048). Finally, an increase in median family income percentile by 1 unit resulted in a reduction of 0.02 in the predicted DM score (p = .007).

The regression model in which participant characteristics served as predictors of the RM scores was also statistically significant, F(24, 796) = 2.42, p < .001, R = .26, explaining 6.8% of the variance in the RM scores. Four of the predictor variables were significant in the model (see Supplemental Table S3 included with the online version of this article for full regression results). Participants in ninth grade were predicted to score 5.35 points higher on the RM than 12th-grade participants (p = .021). Those who did not intend to study music were predicted to score 3.63 points higher on the SM than participants who did intend to study music (p = .041). An increase in median family income percentile by 1 unit resulted in a reduction of 0.07 in the predicted RM score (p = .022). Finally, participants in 10th grade were predicted to score 4.47 points lower on the RM than 12th-grade participants (p = .014).

In summary, participants self-categorized and differentiated in favor of the music performance career path but allocated resources in favor of the music education career path. Age, family income, performance setting, and intention to major in music were significant predictors of the outcome variables. This indicates that participants who were older, had greater financial means, identified as soloists, or intended to major in music were more likely to be aligned with a music performance social identity.

Discussion

We gathered a total of 821 questionnaire responses from adolescent musicians that addressed the social identities associated with musical career paths in music performance and music education. The results of this study suggest that adolescent musicians are aware of the social identity groups associated with career paths in music performance and music education and self-categorize into those groups. According to SM scores, adolescents perceive both of these social identities as salient enough to self-categorize despite having not yet formalized their membership in any of these groups through the declaration of a major or another external validation of group membership. Tajfel and Turner (1979) indicated that with self-categorization comes the creation of bias, both in favor of one’s own group and against other groups, although not necessarily formed with malicious intent. The finding that adolescent musicians expressed biases in favor of and against these social identities is notable given that researchers have documented such biases only among postsecondary students (Bouij, 2004; Conway et al., 2010; Ellis, 1999; Gavin, 2012; Ryan, 2010; Scheib, 2006; Sieger, 2012; Woodford, 2002). Furthermore, it may conflict with the notion that the climate or culture of a university or conservatory music program creates such biases (Nettl, 1995; Scheib, 2006).

One possible explanation for participants’ self-categorization and the presence of these biases during adolescence may be the aforementioned centrality of performance or an increase in performance-based offerings in music as students progress through a preK–12 curriculum (Haning, 2016; Matthews & Koner, 2017). As Reimer (2012) suggested, “at the secondary level, we have put practically all our eggs in the basket of performing music in large ensembles” (p. 25). There is concern that the centrality of performance negatively impacts the quality of and access to musical experiences in schools (Koza, 2009; Radocy, 2003). According to Tajfel and Turner (1979), in-group favoritism and bias are “a remarkably omnipresent feature of intergroup relations” (p. 38) and require only the awareness or perception of an out-group to form. Individuals differentiate between their in-group and perceived out-groups by increasing the distance between the stereotypical profiles of members of each group. This centrality may also have the unintended consequence of fostering in-group favoritism and bias toward the music education career path among adolescent musicians aligned with the music performance career path.

Unlike the results of the SM and DM that favored the music performance career path, the results of the RM favored the music education career path. This was surprising, given that Tajfel (1986) found consistent results across all measures of differentiation, including resource allocation. It is possible that the allocation of resources in this study may have been influenced by the emerging nature of these identities among participants. Tajfel and Turner (1979) noted that discriminatory group behavior is more likely to occur between groups with impermeable boundaries. Given the consistency of impactful experiences and high level of influence attributed to music teachers among adolescent musicians (Jones & Parkes, 2010; Parkes & Jones, 2011; Rickels et al., 2019), the boundaries between the social identities associated with the music performance and music education career paths may not be firm enough during adolescence to allocate resources in alignment with their self-categorization and differentiation. Such a lack of boundaries between career paths and the emerging nature of these identities may also contribute to a wide variety of salience associated with these career paths among adolescents, reflected in the greater variability of SM scores than those of the DM (as indicated by the standard deviations of individual items and composite score), and subsequently a smaller effect size for the mean difference of the SM (V = 0.256) than the DM (V = 0.459). According to Abrams and Hogg (2010), the salience of group membership relies on two factors: accessibility and fit. Accessibility is the amount of presence a group has in an individual’s life, and fit is the extent to which an individual’s behavior aligns with stereotypical behaviors of group members. Although the performance-based nature of most adolescent musicians’ experiences may have allowed participants to achieve high levels of fit with these career paths, entrance to college, graduation, and additional education all stand between adolescents and these career paths and may result in a low degree of accessibility. Alternatively, adolescent musicians may view these career paths as accessible due to the influential presence of music educators in their lives but experience less fit with the career paths out of respect for the professionalism of those same individuals.

Regardless, this lack of salience may represent an opportunity for music educators to address adolescent musicians’ bias against the music education career path. Secondary music educators might apply strategies that have been found to be effective in encouraging music teacher socialization among postsecondary students. Strategies might include taking steps to bring adolescents’ attention to pedagogical practices, implementing teaching opportunities for students (Madsen & Kelly, 2002; Rickels et al., 2013, 2019; Thornton & Bergee, 2008), introducing peer mentorship experiences (Goodrich, 2022), or inviting music teacher educators to discuss the music education career path earlier in adolescents’ high school years, offer guidance regarding application and audition processes, and advocate for financial support. Such steps on the part of music educators and music teacher educators may help counter the biases associated with musical career paths that were revealed in this study and encourage a more balanced musical identity for young musicians.

Perhaps due to the large number of demographic characteristics included and the categorical nature of most of these variables, regression analysis of each measure indicated a small amount of variance. Several variables significantly contributed to the model, including some that were consistently significant across measures and reflected trends found in extant research. Gender, performance setting, age, family income, and intention to major in music were significant predictors of participants’ alignment with the identities associated with the musical career paths included in the study. An adolescent who most favors the music performance career path is a male, 12th-grade vocal soloist, with 10 or more years of private study, who comes from a wealthy family and intends to major in music. In contrast, the profile of an adolescent who most favors the music education career path is a female, ninth-grade string player, with 3 or fewer years of private study, who also sings in a choir, comes from a family of modest means, and does not want to major in music. In terms of gender, these results align with the female majority found in demographic research of individuals in preK–12 music teaching positions (Gardner, 2010) and investigations of gendered representation of music educators in music journals (Kruse et al., 2015). Although there is less research regarding gender distribution within the music performance career path, the results of this study do align with the male majority found across multiple genres of music performance (Sergeant & Himonides, 2023).

Regarding performance setting, the connection found in this study between those identifying primarily as soloists and the music performance career path was somewhat presumed. In contrast, the relationship between string players and the music education career path was surprising given long-held concerns regarding string teacher shortages (Hash, 2021). The effect of age and years of study are understandably linked because advancing years allow more opportunity for study and reinforce the importance of earlier engagement with the music education career path, as mentioned previously. The linkage between higher socioeconomic status and a music performance identity revealed in this study builds on earlier findings that those in the highest quartile of socioeconomic status are more likely to be involved in school music programs (Elpus & Abril, 2011). Efforts to reduce or remove the cost of instrument rentals, private lessons, or honor ensembles may improve access to the key preparatory experiences associated with a career path in music for a broader range of individuals. Finally, because more than 97% of participants in this study reported studying instruments and participating in ensembles traditionally linked to classical music, an increased diversity of offerings and inclusive range of musical genres might invite participation into both of these career paths for a broader range of individuals.

Limitations

We aimed to assess the social identity regarding musical career paths among adolescent musicians using an online questionnaire. One pair of prompts (“Members of this group intend to perform [teach] because they enjoy practicing alone [working in front of others]”) produced the only result of the 10 that favored the music education career path. This inconsistent result may point to a problem with the wording of the prompt and perhaps an oversimplification of the work involved in the two career paths. Future research might include a refined version of this prompt or additional prompts that explicate the types of work involved in each path.

Although the resource allocation by participants in this study may represent a lack of salience among adolescent musicians or the emerging nature of their social identities, the measure itself may require further development. Adolescent musicians may believe that financial instability is an inevitable part of the music performance career path (Lingo & Tepper, 2013). Social identity theory suggests that to retain a positive self-image and hierarchical status, a drawback such as the financial instability of a career path must be viewed as a positive (Tajfel & Turner, 1979). For example, an individual might welcome financial instability by embracing a historic archetype of the starving artist who values their art above monetary interests (Lingo & Tepper, 2013). In this study, participants who identified with the music performance career path in the SM and expressed bias against the music education career path in the DM may have acted in accordance with their social identity by embracing this archetype in their allocation of resources to the detriment of the music performance career path. Given that we did not query participants regarding their awareness of the financial realities of these career paths and considering that more than 20% of U.S. adolescents lack basic financial literacy (OECD, 2017), these results may not be sufficiently calibrated for accurate interpretation, a notion supported by the low effect size of the RM (V = 0.021) and a relatively high standard deviation of $18,730.

Suggestions for Further Research

The replication of this study among college students enrolled in the music performance and music education major could provide insight into the development of these identities, as would a longitudinal study beginning in adolescence. Responses from adolescent musicians involved in nonclassical musical activities and future music teacher organizations may also provide insight. Future studies using qualitative methods may further illuminate the presence of social identities associated with career paths in music. A better understanding of identity formation among individuals who may pursue a music education career could lead to effective recruitment and retention efforts within a performance-centric musical landscape. Social identity theory may serve as a useful lens to understand and assist musicians as they navigate these identities at all ages.

Supplemental Material

sj-docx-1-jrm-10.1177_00224294231211911 – Supplemental material for Groups and Biases: The Role of Social Identity in the Musical Career Path Aspirations of Adolescent Musicians

Supplemental material, sj-docx-1-jrm-10.1177_00224294231211911 for Groups and Biases: The Role of Social Identity in the Musical Career Path Aspirations of Adolescent Musicians by John A. Bragle and Diana R. Dansereau in Journal of Research in Music Education

Footnotes

Declaration of Conflicting Interests

The authors declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: Boston University-2021.

Funding

The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: Bragle, J. A. (2021). The role of social identity in the formation of biases toward career paths in music among adolescent musicians (Doctoral dissertation, Boston University).

ORCID iDs

John A. Bragle

Diana R. Dansereau

Supplemental Material

Tables S1 to S3 are available in the online version of the article at .

Notes

Author Biographies

John A. Bragle is director of community programs at the Wisconsin Conservatory of Music. His research interests include the social identity of musicians and early childhood music education.

Diana R. Dansereau is associate professor of music and music education at Boston University. Her research focuses on early childhood music education and music education research.

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