Social Science Research 39 (2010) 296–309

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Social Science Research

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Opportunities to participate: Extracurricular activities’ distribution acrossand academic correlates in high schools

Elizabeth Stearns *, Elizabeth J. GlennieUniversity of North Carolina at Charlotte, Charlotte, NC, United StatesRTI International, United States

a r t i c l e i n f o a b s t r a c t

Article history:Available online 6 August 2009

Keywords:Extracurricular activitiesHigh school resources

0049-089X/$ - see front matter � 2009 Elsevier Incdoi:10.1016/j.ssresearch.2009.08.001

* Corresponding author. Address: UNC-Charlotte,704 687 3091.

E-mail address: elizabeth.stearns@uncc.edu (E. S1 Higher functioning students are more likely to

whether the beneficial effects of such participation arsponsored extracurricular activities gain some benefi

Studies suggest that students who participate in extracurricular activities benefit in a num-ber of ways. However, schools provide different opportunities to participate in these activ-ities. Using information from high school yearbooks and administrative data on studentsand schools in North Carolina, we examine whether school characteristics influence thenumbers and types of extracurricular activities available, whether schools providing moreand diverse activities have higher participation rates, and whether these schools have bet-ter academic outcomes. We find that school size and poverty levels significantly influencethe number and types of activities available, with larger schools and those schools withmore affluent student bodies offering more activities. In addition, schools with more activ-ities available tend to have higher participation rates. Opportunities to participate are asso-ciated with positive academic outcomes for the school, even when controlling for schoolresources. For some—but not all—activities, student participation rates mediate the rela-tionship between activity availability and the school’s academic profile. For benefits tobe present, schools must provide these resources, and students must invest in them.

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1. Introduction

Extracurricular activities are an integral part of high school for many students. Yet given funding challenges and pressuresto increase test scores in today’s educational climate, many schools are considering cutting the number of activities they offeror reducing students’ opportunities to participate by cutting transportation or other types of financial support (Gutierrez,2004; Starr, 2000). Those who support activities argue they provide many benefits for students, including an opportunityto develop prosocial peer groups and a sense of belonging, a ‘‘hook” into school that may help to keep students enrolled,and increased academic achievement (Cooper et al., 1999; Davalos et al., 1999; Johnson et al., 1998; Mahoney and Cairns,1997; Mahoney, 2000; Marsh 1992; Quiroz et al., 1996). Others point to the political socialization function that extracurric-ular activities serve, paving the way for adolescent participants to become politically active adults (Burns et al., 2001; Ecclesand Barber, 1999; McFarland and Thomas, 2006; McNeal, 1995; Putnam, 2000; Verba et al., 1995). Thus, extracurricular activ-ities are seen both to supplement existing academic curricula and to allow students the opportunity to build non-academic,civic, and political skills such as teamwork.1

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Department of Sociology, 9201 University City Boulevard, Charlotte, NC 28223, United States. Fax: +1

tearns).choose to participate in extracurricular activities, and existing research has not indicated conclusivelye the result of selection. However, the body of research suggests that students who participate in school-t from doing so.

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Yet, different types of schools may provide different opportunities to participate in such activities. While existing researchhas examined important individual-level influences on participation, such as socioeconomic status, it has largely neglectedthe possible existence of structural inequalities in opportunities to participate and whether any structural inequalities mightpertain to all types of activities (e.g., Eitle and Eitle, 2002; McNeal, 1998). The literature also lacks an examination of whethergreater opportunity is associated with greater participation. That is, in schools with more available spaces on different typesof activities, do more people participate? Finally, to our knowledge, there has been little examination of whether the distri-bution of extracurricular activities matters for student academic outcomes. In other words, few have investigated whetherthe presence of activities in and of themselves is associated with academic outcomes, or whether student participation medi-ates this link. In conceptualizing the link between activities, participation, and outcomes, we draw heavily on recent researchon opportunity structure theory, which distinguishes between structurally-based resources, the investments people make inresources (within the constraint of resource availability), and their influence on various outcomes (Charles et al., 2007; Rosc-igno et al., 2006).

Our work speaks directly to the core issues in stratification research that ask where resources are located and whetherbenefits are associated with the structural location of and individual investment in these resources. We conceptualize extra-curricular activities as resources that schools provide and students’ electing to spend their time and energy in these activitiesas their investment in these resources. Combining data from school yearbooks about the extracurricular activities they offerwith reports from students about their investments in these activities permits us to address a series of questions. First, weask how school characteristics influence the numbers and types of extracurricular activities available in schools. Rather thanrelying on school size as the only predictor of activity availability (Schoggen and Schoggen, 1988), we examine other impor-tant school characteristics, including student body composition and school location. Second, we ask whether schools thatprovide more activities to their students also have higher participation rates. This question allows us to examine the extentto which students’ participation is linked to activity availability. Last, drawing on opportunity structure theory, we ask ifschools that provide many resources in the form of a large number of extracurricular activities also see higher academic per-formance and lower dropout rates among their students. If such a link exists, it is important to establish whether mecha-nisms such as participation rates—the investments that people make in those resources—mediate the link.

2. Distribution of activities

Schools offering many different activities provide resources that could help students in a variety of ways. As such, it isimportant to examine where and in what types of schools these activities are located. While we acknowledge that someclubs may be generated and maintained primarily by student interest,2 we argue that most extracurricular activities and clubsexist, if not at the school’s initiative, then at least with the school’s endorsement. In other words, schools place a constraint onthe extent to which students can invest in extracurricular activity participation in the form of activity availability.

Many schools support clubs in various ways—by encouraging teachers to act as club advisors, donating space for clubs tomeet, publicizing club events, supplying materials such as uniforms, costumes, or some laboratory equipment, or even byproviding transportation to and from certain events. Additionally, schools and club advisors may set formal and informalcriteria to control both the numbers of activities available and the extent to which students can choose to participate in thoseactivities (Quiroz et al., 1996). They may limit the number of activities or the number of students who can participate in anyclub. In the absence of other research regarding the distribution of these activities, we draw on research regarding othertypes of resources that schools provide in order to form our hypotheses with respect to the types of schools in which clubswill be located. Broadly, we hypothesize that schools with more resources will have more activities than schools with fewerresources.

2.1. Financial resources

Financial resources play a substantial role in influencing the quality of education offered to students. A large body of re-search, both popular and scholarly, has demonstrated some of the repercussions of inequalities in school funding. For exam-ple, Kozol (1991, 2005) has extensively shown how widely the quality of education varies, sometimes even among schools inthe same districts, according to their levels of funding. Higher levels of funding are frequently translated into more tangibleand intangible resources for students, such as lower class sizes, better technology, and more qualified teachers. Most schoolexpenses come from state and local sources, and districts with predominately high-SES residents have more economic re-sources than those with low-SES residents. Nationally, the average disparity in per pupil spending between high incomeand low income districts is $1348 (Carey, 2004). Per-student expenditures reflect financial resources that can enhance theavailability of extracurricular activities. Indeed, school districts facing budget cuts often propose cutting extracurricularactivities in an effort to save money (Gutierrez, 2004; Starr, 2000). Thus, we hypothesize that schools with higher per-stu-dent expenditures will also provide more activities than schools with lower per-student expenditures. We believe that thisresult will be consistent across different types of extracurricular activities.

2 This issue is minimized in our study by the fact that we use participation data from ninth graders, who have recently entered high school and found astructure of available opportunities.

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In addition, a significant body of research (Lichter et al., 1993; Roscigno et al., 2006; Tickamyer and Duncan, 1990)has established that rural schools have historically provided fewer resources for their students than urban and suburbanschools. In fact, in North Carolina, where this study is based, some rural schools have challenged the state educationsystem’s funding formula, arguing that it places a burden on local governments because their districts lack the necessaryresources to provide fundamental educational opportunities for their children (North Carolina Administrative Office ofthe Courts, 1997). We suspect that those schools that provide fewer academic resources for their students may also pro-vide relatively few extracurricular resources and that rural and urban schools will offer fewer activities than suburbanschools.

Although little work has been done on the effect of locale on extracurricular activity participation, we expect that thisfactor will influence such involvement. As schools are embedded in communities, they will probably offer activities thatreflect those valued by adults in that community. Using the National Endowment for the Arts’ online analysis software(National Endowment for the Arts, 2003), we find that rural adults are significantly less likely to participate in a wide varietyof arts activities than are urban adults. They are also less likely to participate in sports activities than adults in metropolitanareas. Thus, we expect to find that locale will influence the availability of different types of activities. In particular, suburbanand urban schools will offer more arts and sports activities than rural schools.

In addition to geographically-based differences in resources, inequalities are associated with the student body compo-sition, with schools with high percentages of poor students providing a lower quality education for their students. Histor-ically, these types of schools have lower per-student expenditure, larger class sizes, and fewer well-qualified andexperienced teachers than schools with more affluent students (Clotfelter et al., 2005; Kozol, 2005, 1991; Roscignoet al., 2006).

The repercussions of the socioeconomic composition of the student body go beyond the resources that the school pro-vides, however. The percentage of students on free/reduced lunch indicates the financial and human resources that par-ents and students can bring to their participation in activities. Children of lower-SES parents are less likely to participatein activities than children from higher-SES parents are, partly because of the direct costs of activities and partly due to theopportunity costs associated with them, such as the fact that a teenager participating in these activities is not available towork or care for siblings (see e.g., Antshel and Anderman, 2000). In addition, higher-SES parents are frequently more in-volved in their children’s education than are lower-SES parents (e.g., Lareau, 2002; Lareau and Horvat, 1999). They may bemore encouraging and supportive of their children’s participation in extracurricular activities and more likely to contributeto the schools’ efforts to provide those activities. Their support might take forms such as volunteering to work the con-cession stand at a football game, helping chaperone a trip to a chorale competition, or selling popcorn or wrapping paperto raise funds for the activity. Therefore, we expect to find a negative relationship between the percentage of students onfree/reduced lunch and the numbers of activities of various types available, results that we suspect will be consistentacross types of activities.

The racial composition of the school may also influence the number and types of activities available. Schools with rela-tively larger minority populations frequently have outcomes analogous to those of high poverty schools, not coincidentallybecause they are frequently also high poverty schools (Orfield and Lee, 2006). In addition, others have found that White stu-dents are more likely to participate in extracurricular activities than racial minorities, so perhaps schools with large minoritystudent populations offer fewer activities (Mahoney and Cairns, 1997; McNeal, 1998). It is not clear whether racial minoritiesare more likely to attend schools with fewer activities available or whether they are less interested in joining the types ofactivities that are available. We hypothesize that schools with more ethnic minority students would also have fewer activ-ities of most types available than schools with fewer ethnic minority students. At the same time, others have found thatminority students, specifically African-American students, are more likely to participate in sports than White students (Eitleand Eitle, 2002; Mahoney and Cairns, 1997, but see Ingels et al., 2005 and Davalos et al., 1999 for an alternative viewpoint).Thus, we expect to find that schools with heavily minority populations offer more sports activities than schools with propor-tionately larger White populations, net of other factors.

2.2. Human resources

In addition to financial resources, extracurricular activities also frequently require human resources, or skills and knowl-edge. Frequently, these human resources appear in the form of teacher participation. In many cases, teachers coach sportsteams or advise clubs. Those teachers who are already taxed with responsibilities for many students may be less willing tospend their time in this way, while teachers with responsibilities for fewer students in the classroom may have time andenergy to advise a club or coach a sports team. Therefore, we expect to find that schools with higher student/teacher ratioswill have fewer extracurricular activities than schools with lower student/teacher ratios. We expect these findings to be con-sistent across activity type.

In contrast to the research regarding these other school characteristics, the link between school size and activity avail-ability is somewhat more established (Barker and Gump, 1964; Schoggen and Schoggen, 1988). Small schools may not haveenough students, teachers, or facilities to support as many activities and thus larger schools have been found to offer moreactivities than smaller schools. We expect our analyses will show that larger schools will offer more activities as well. Wealso expect that the effect of school size will be particularly apparent for ‘‘hobby clubs” such as recreational sports, givenresearch that links the availability of ‘‘slots” in these clubs and school size.

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3. Activity availability and participation

We have hypothesized that greater levels of various resources are associated with more extracurricular offerings. Follow-ing the logic of the argument established by Roscigno et al. (2006), which distinguishes between the structural availability ofresources and individuals’ decisions whether to invest in those resources, the next question is whether people make greaterinvestments in extracurricular activity participation when there are more resources available. In other words, are greaternumbers of activities associated with higher participation rates when controlling for other school characteristics? Althoughwe cannot examine individual participation decisions, this study of participation rates demonstrates the outcome of multipleindividuals’ decisions about whether to participate in activities.

It is tempting to argue that the problem of participation is one of supply and demand. Students cannot participate inactivities if the activities are not available, and activities may not be available because there is no demand for them, eitherbecause students prefer other types of activities or because they do not want to participate in any activities. Extant researchis mixed on this question. Some research has shown that large numbers of activities, or ‘‘slots” in those activities, are notnecessarily associated with higher student participation rates (Schoggen and Schoggen, 1988). Specifically, while largeschools have more activities, students in smaller schools participate more often and in more types of activities than thosein larger schools (McNeal, 1999; Schoggen and Schoggen, 1988). Consider that activities such as sports teams and school gov-ernments have fixed numbers of positions. In larger schools, students may compete for those slots, but small schools recruitstudents to join because they must have a certain number of students to fill the slots. Thus, participation rates are higher insmaller schools than larger schools.

Other research based on a case-study of an inner-city school has found that similar processes exist with respect to clubsthat have no pre-determined number of ‘‘slots” (Quiroz et al., 1996). Both formal and informal mechanisms can limit stu-dents’ access to the extracurricular opportunity structure. The formal criteria include such things as performance thresholdslike GPA or skill-level requirements or class attendance. Informally, activity membership may be limited by sponsors’ puttingcaps on the membership in their clubs and teachers’ and students’ actively recruiting or discouraging students fromparticipating.

In contrast to Quiroz et al., we hypothesize that schools with larger numbers of extracurricular activities may also havehigher participation rates, net of school size. However, we do not anticipate that there will be a linear one-to-one increasein participation rates associated with increases in activities. In other words, we anticipate that the greater resource avail-ability will be associated with students’ greater investments in those resources, but we do not anticipate that there will bea perfect correlation between resources and investments. As Roscigno et al. (2006) and Charles et al. (2007) find, people donot always make investments even when resources are available. Although their findings focus on other educational out-comes, we argue here that the same may hold true for students’ participation in extracurricular activities. In order for lar-ger numbers of activities to be associated with higher participation rates, students must find activities that are attractiveto them, find available slots in those activities, and receive support (or at least a lack of discouragement) from parents andpeers to participate.

Several factors may explain a positive relationship between activity availability and participation. First, those schoolswith many types of activities will offer a range of opportunities that appeal to many different tastes, thus encouraging great-er participation. A second possibility is that schools with many activities will offer many similar types of activities, but have agreater number of slots available in those activities, so that more students can participate. Third, greater participation ratesmay reflect an overall higher level of commitment to or attachment to the school. In any case, we ask whether resourceavailability and participation rates may make a difference for school-level academic outcomes, including dropping outand academic achievement.

4. Activities, participation, and outcomes: applying resource investment theory

4.1. Number of activities and academic outcomes

Finally, we turn to the question of whether the distribution of activities matters for academic outcomes. More specifically,is the number of activities available directly associated with the positive academic outcomes, or do participation rates inthese activities mediate the relationship between activity availability and academic outcomes? In many respects, this isthe key question of this study, as it directly addresses the issue of whether inequalities of resources have an impact on mea-surable academic outcomes, thereby indicating one way in which inequalities in education perpetuate and generate laterinequality.

Our argument parallels that made by Roscigno et al. (2006) and Charles et al. (2007) in distinguishing between the pres-ence of resources (extracurricular activities) and the investments that individuals and/or institutions make in using thoseresources (participating in activities). For instance, Roscigno et al. (2006) find that both parental income (resource) andthe extent to which they have invested in educational items predict student achievement. In addition, the investments thatparents make mediate between the presence of resources and educational outcomes. In our case, activity participation rates,or the investments that individuals make in using the resources, might mediate between the number of activities (resources)and the academic outcomes.

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Why might participation rates mediate between the numbers of activities available and academic outcomes? A large bodyof literature has found a positive relationship between student participation in extracurricular activities and academicachievement (Broh, 2002; Eccles and Barber, 1999; Fejgin, 2001; Hanson and Kraus, 1998; Mahoney and Cairns, 1997;Marsh, 1992; Marsh and Kleitman, 2003; McNeal, 1998). In addition, students who participate in extracurricular activitiesmay be less likely to drop out of high school (Davalos et al., 1999; Mahoney, 2000; Mahoney and Cairns, 1997; Melnicket al., 1992a,b; Quiroz et al., 1996; Zill et al., 1995). On the whole, students who participate in extracurricular activities havehigher achievement and lower dropout rates than those students who do not.3 This research leads us to believe that the pres-ence of the resource in the form of extracurricular activities may not be associated with academic outcomes if relatively fewstudents elect to invest in these activities through participation.

However, the number of activities may influence academic outcomes independently of participation rates. Activity avail-ability may measure some intangible aspect of the school environment that is not captured by our other measures of schoolcharacteristics. For instance, given the resources that are necessary to run extracurricular activities, the number of activitiescould proxy for the amount of emphasis that the school and/or community places on producing well-rounded adolescents orthe amount of social support from concerned adults available for students. As Stevens (2007) notes, high schools are differ-entiated by intangible characteristics, characteristics with which savvy parents and college admissions officers are wellfamiliar. In this case, we might expect to find that the participation rates do not entirely mediate any relationship thatwe find between activity availability and academic outcomes.

To summarize our hypotheses, we consider extracurricular activities to be a type of resource that schools offer to theirstudents, and we expect that schools with more financial and human resources will offer more activities. We expect thatmore students will participate in these activities when they have more opportunities to do so. When students invest in theseopportunities, we expect to find that schools will also see some academic benefit. These higher levels of participation willmediate the relationship between activity availability and academic outcomes. In other words, we hypothesize that schoolswith more activities available and higher extracurricular activity participation rates will have both higher achievement ratesand lower dropout rates. Student participation will mediate the relationship between activity availability and studentachievement.

5. Data

Our sample includes all of the regular high schools in the state of North Carolina. We exclude alternative and charterschools, as well as high schools with a grade span other than grades 9–12.4 Our data originate from several different sources.First, information on some school-level variables, such as student/teacher ratio, percent of ethnic minority students, percenton free/reduced lunch, school size, and school location—rural, urban, or suburban—come from the Common Core of Data(CCD). The CCD is a federally-sponsored dataset that collects information from all schools in the country.

Other variables come from datasets collected by the North Carolina Department of Public Instruction (DPI) and madeavailable to researchers through the North Carolina Education Research Data Center at Duke University. These data includeinformation regarding the per pupil expenditure, the extracurricular activity participation rate, the percentage of the studentbody performing at grade level and the dropout rate.

Participation rates are for ninth graders in the spring of 2001. We use the End of Course English 1 exam at the end of 9thgrade English to establish a population of students in North Carolina schools. After the ninth grade, the course taking of manystudents diverges, but almost every ninth grader (86.3%) takes English 1.5 Although in North Carolina, all students in grades 3–8 take End of Grade exams, students in high school take End of Course exams whenever they complete the courses with suchexams. For example, students in all high school grades might take Biology. English 1 is the only high school exam that is takenby students in the same grade, specifically ninth grade. Because the students responding to the survey about extracurricularactivities are all in the same grade, using this source of information controls for the students’ stage in high school.

When taking this test, students complete a brief survey that includes the yes–no questions ‘‘In which of the followingextracurricular activities do you participate afterschool? Mark ALL that apply.” Response options were the following:

3 Explanations for the benefits vary. Participation in clubs gives students the opportunity to build social capital through interaction with both other studentsand teachers. Some of the academic benefits of activities might lie in the increased attention from concerned adults, who may be more proactive in seekingacademic help for students who are in danger of failing, particularly if the students are participating in activities that have a minimum GPA requirement. Clubsalso facilitate getting to know adults within a non-classroom, non-familial setting. Adolescents interact with the club advisors more informally than they mightin class and then potentially have more adults to talk to if they had a problem (Quiroz et al., 1996). These activities may also expand a student’s peer group,allowing him or her to meet and befriend others from different social classes, neighborhoods, and ethnic groups. Such diversity has been shown to haveacademic benefits among college students (Antonio, 2004; Chang, 1999; Chang et al., 2006) and may very well do so among high school students as well. Inaddition, organized activities may also help adolescents by giving some structure to their discretionary time. Teens spending time in structured activities haveless unsupervised time to engage in deviant behavior and more time to interact with motivated and similarly interested peers and perhaps adhere to moreprosocial behavioral norms (Eccles and Barber, 1999; Mahoney and Cairns, 1997). Any of these types of social capital might be resources on which studentscould draw, resources that might facilitate achievement or keep students enrolled in school.4 In contrast to many other states, North Carolina has relatively few charter and alternative schools. During the 1999–2000 school year, for example, there wereonly six charter high schools operating in the state. Given that one of these charter schools had just opened that year and that their average size was 84 students(with a maximum of 136 students) vs. an average school size of 1056 for non-charter schools, we decided to exclude these schools from the sample.

5 Those exempt from taking English 1 include limited English proficient students, exceptional students, and those who had recently transferred to a NorthCarolina public school.

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athletics and supporting activities, (e.g., athletic teams, cheerleading, pep club); academic subject matter clubs or debate;fine arts (e.g., band, orchestra, chorus, dance and drama); vocational education clubs (e.g., future homemakers, teachers,farmers and business); service clubs (e.g., Civitans, Key Club); other activities; and ‘‘I do not participate in any extracurricularactivities.” We aggregated these responses to calculate the ninth grade participation rate in the school for the following: (1)any activity participation; (2) academic activity; (3) arts activity; (4) ‘‘other” activity; (5) service activity; (6) sports; and (7)vocational activity participation.

The data on extracurricular activities come from yearbooks that we collected from North Carolina high schools during thespring of 2003. Using data from the North Carolina Education Research Data Center, we generated a list of 302 traditional(non-charter) 9–12 high schools in North Carolina that had been open during the 1999–2000 school year. These 302 schoolsrepresent 95.3% of the schools enrolling high school-aged students in North Carolina. We were able to obtain informationabout school-based extracurricular activities for 264 (87.4%) of these high schools. The majority of these schools providedinformation for the 1999�2000 school year.

We contacted each school via telephone and eventually received yearbooks from 203 schools.6 For those schools that didnot provide a yearbook, we asked yearbook advisors to e-mail list of activities in their schools (five did so) or obtained data fromthe school’s website (56 schools). Comparisons of the data source indicate that there are no significant differences on our inde-pendent variables between schools that provided us with information via yearbooks and those with other sources of informa-tion.7 Thus, we are left with missing data for only 38 schools.8

Once we had collected yearbooks, we coded the activities that were available in each school. We then agreed on a codingscheme that collapses the various activities into a set of 12 categories: academic; arts; ethnic identity/advancement; govern-ment/leadership; honors; media; music; recreational sports; religious; service; varsity and junior varsity sports; and voca-tional. Academic activities include things such as foreign language clubs and Quiz Bowl. Arts activities include Art Club andPerforming Arts Club, while ethnic identity/advancement clubs include such organizations as the NAACP and Latino Clubs.Examples of government/leadership clubs include student government and Students Against Drunk Driving. Honors clubsinclude various national honor societies and media clubs include journalism clubs and the newspaper, among others. Variouschoirs are examples of music clubs and recreational sports include clubs like skiing, scuba, and surfing clubs. We distinguishhere between interscholastic varsity and junior varsity sports that have a limited number of slots for participants and involvecompetition against teams from other schools, and recreational sports that do not involve such competition.9 Religious activ-ities are primarily Christian-based activities such as ‘‘Christian and Proud” and the ‘‘Cross Club,” but some schools had JewishClubs and Muslim Student Associations. Service clubs included organizations such as the Civitans and Habitat for Humanity,while vocational clubs included Future Farmers of America and Future Business Leaders of America. A more complete listingof clubs is available from the authors.10 Descriptive information for all of our independent and dependent variables is shownin Table 1.11

Our school-level academic outcomes are the percentage of students performing at grade level on End-of-Course examsand the percentage of students who drop out of school. The North Carolina Department of Public Instruction calculatesthe school-level percentage of students performing at grade level on End-of-Course exams each year as part of its account-ability program. North Carolina follows the federal event count method of reporting dropouts (North Carolina Department ofPublic Instruction, 2000). A dropout is someone who began school in the previous school year and either dropped out duringthat school year or did not return to school following the summer break (transfers are not drop outs). Each October, schoolsreport dropouts from the previous year. The dropout rate is the number of dropouts divided by the total membership of theschool (multiplied by 100).

6 The other 99 schools either did not have an extra yearbook available, were unwilling to send one to us, or said that they would send us a yearbook and thendid not do so. Several schools also had yearbook advisors who were ‘‘unreachable”: we abandoned efforts to reach the advisors after six phone calls. We codedthe extracurricular data from the yearbooks that were sent to us. In five cases, we supplemented the yearbook data with data from the school’s website becausethe yearbook did not include spring sports.

7 The means for some of the types of activities were significantly higher in schools that provided yearbooks than they were in schools that providedinformation via the Internet. We are unable to tell whether these differences are the result of data-gathering techniques, or whether they reflect actualdifferences in activity availability. On the whole, the differences were small (on the order of approximately one activity) and our substantive results held upwith the introduction of a series of dummy variables designed to measure the source of the data.

8 These 38 schools tended to be high-poverty, high-minority schools located in rural areas of the state. They had significantly fewer students performing atgrade level, but there was no significant difference between these 38 schools and the sample schools in terms of the student-reported extracurricularparticipation rate.

9 Many of these recreational sports are specific to various parts of the state. For example, scuba and surfing clubs are found in coastal high schools, while skiteams characterize high schools in the mountains. Others, such as bowling, are bound less by geography.

10 Factor analysis indicates that there are multiple groupings with eigen values >1 for many of the activity types. We identified those activities that loadweakly on the first component for each of the activity groupings and reran the analyses using both attempts at quantifying these activity groupings. Thenumbers of each type of club were fairly small, and changing the way in which the activity types were coded did not alter the results presented in this paper.

11 The N is smaller for the analyses of dropout rate than it is for the other analyses. There was one school that did not provide information on the dropout rate,but did provide information on all other measures. We decided to include that school in the other analyses where possible.

Table 1Descriptive information for all independent and dependent variables: study of extracurricular activities in North Carolina public high schools.

Mean Standard deviation Range

Low High

Student outcomes% At grade level 64.30 10.55 24.70 87.30Dropout rate 5.89 2.16 1.52 13.70

School characteristics% Ethnic minority 33.39 23.07 1.04 98.71% Free lunch 25.19 15.77 3.33 98.94School enrollment (logged) 6.91 0.43 174 2649Urban 0.21Suburban 0.34Per-student exp./100 $62.65 5.70 $53.68 $82.02Pupil/teacher ratio 14.82 2.23 8.40 23.80

Activity availabilityAcademic 3.90 2.46 0 14Honors 2.03 1.36 0 9Arts 1.35 1.00 0 6Music 2.51 2.07 0 12Ethnic identity/advancement 0.47 0.79 0 4Recreational sports 1.42 1.35 0 6Service 2.30 1.71 0 8Vocational 5.03 2.04 0 11Government & leadership 2.09 1.07 0 6Religious 1.04 0.77 0 4Media-related 0.67 0.80 0 3Sports 21.51 5.26 5 32Total activities 44.31 12.24 11 83

Activity participation ratesTotal participation 77.86 5.23 61.60 90.88Academic participation 6.79 3.85 0.00 41.60Arts participation 25.74 7.36 0.00 56.00Other participation 27.74 6.00 12.25 49.60Service participation 8.45 5.34 0.00 34.40Sports participation 47.70 6.47 24.61 66.67Vocational participation 8.33 6.64 0.00 50.35

N = 258 for all measures, except for dropout rate where N = 257.

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6. Analytic strategy

This paper examines three research questions: (1) how do school financial and human resources affect the availability ofextracurricular activities; (2) how are the availability of activities and student participation rates related; and (3) how areactivity availability and participation in these extracurricular activities associated with school academic outcomes? Toaddress the first research question, we run regression models with each of the 12 types of activities that we found schoolsto offer as the dependent variable. Some of the activity types merit the use of ordinary least squares (OLS) regression becauseof their continuous nature, while others require the use of Poisson or negative binomial models because of their skewed dis-tributions and over-dispersion. We analyze both the total number of activities available, as well as the individual types ofactivities, given research on the differing nature of participation in various activity types (Eccles and Barber, 1999; McFar-land and Thomas, 2006; McNeal, 1995). Independent variables include measures of school characteristics—school location,student body composition, school size, student/teacher ratio, and per-student expenditure.

Then, to address our second research question, we calculate ninth grade activity participation rates for each of the grade9–12 high schools in North Carolina and use the activity participation rates as dependent variables, with the activity avail-ability variables as the key independent variables of interest. Several features of our analysis minimize the concern that stu-dent participation and activity availability is a problem of supply and demand. We are analyzing the participation rates ofninth graders, who have recently moved into high school and have had little time to initiate new activities on their own. Wemay reasonably regard these students as facing an established structure of opportunity. In addition, given differential drop-out rates in North Carolina schools (Stearns and Glennie, 2006), the ninth grade data are least biased by dropout rates.

Furthermore, the work of Quiroz et al. (1996) suggests that the number of activities is relatively stable from year to yearand does not change radically in response to student participation. In fact, the structure of activity availability generates stu-dent participation, which is then largely self-sustaining as students recruit others into existing activities. Finally, participa-tion in one type of activity does not usually preclude participation in other types of activities. Recall that we measure activityparticipation over the course of the entire school year, not at one point in the year. Thus we include activities that meet

E. Stearns, E.J. Glennie / Social Science Research 39 (2010) 296–309 303

during school hours and afterschool as well as activities such as sports that occur only during specific seasons of the year.Therefore, participation in a club that met during the school day would not preclude joining an afterschool activity, and play-ing on a fall sport would not prevent playing a spring sport. Our data show that participation rates in most types of activities(except vocational activities) are strongly and positively correlated, suggesting that students participate in more than onetype of activity during the year.

For the third research question, we use the variables measuring activity availability as independent variables predictingacademic outcomes, and then enter the participation rates to discover whether they mediate the impact of activity availabil-ity. We also present unstandardized coefficients throughout the tables, allowing for interpretation of mediating effects. Stan-dardized coefficients that compare effect sizes are available from the authors.

7. Results

7.1. School characteristics and activity availability

The results in Table 2 address our first research question: to what extent are extracurricular activities—both the totalnumber of activities and each type of activities—available in schools with different resources? First, the model for total activ-ities shows a number of significant predictors for the number of activities in the high school. Contrary to our hypotheses,suburban and urban schools do not offer more activities than rural schools do, net of other factors. Further testing (notshown) indicates that urban and suburban schools do not differ significantly from each other in the availability of activities.As we hypothesized, there is a significant and positive relationship between school size and the number of activities. At thesame time, higher percentages of poor adolescents in high school are associated with lower numbers of total activities. Theadjusted R2 value for this model is relatively high (0.39), indicating that school socioeconomic status and school size areexplaining a good deal of the variance in the number of total activities available. However, we did not find evidence in thisfirst model that ethnic composition of the student body or the student/teacher ratio was significantly associated with thetotal number of activities offered in the school.12

Turning to the availability of individual types of activities, we find that some school characteristics have a fairly consistentimpact on the types of activities available.13 Consistent with our hypotheses, school size is positively associated with the num-ber of academic, ethnic, media, music, recreational sports, service, sports, and vocational activities. Honors activities are the onlytype of activity not associated with school size. Indeed, the influence of school size on the number of sports available is largest,which perhaps makes sense given the limited number of slots available on most sports teams. Schools facing greater studentinterest in a guitar club, for example, could simply increase the number of slots available in that club, but schools facing a great-er interest in sports activities would need to increase the number of sports activities to capitalize on student interest. Further-more, urban schools also show more academic and service activities than rural schools, but they do have significantly fewervocational activities than rural schools. We find no significant differences between rural and suburban schools on any activitytype. Furthermore, while the percent on free/reduced lunch is negatively associated with the total number of activities, it alsohas a negative association with the number of honors, service, and sports activities in the school. As noted above, per pupilexpenditures were not associated with the total number of activities, but expenditures are significantly associated with thenumber of ethnic and recreational sports activities in the school and the relationship is in the expected direction: schools withgreater per-student expenditures also have more ethnic and recreational sports activities than schools with lower per-studentexpenditures.

Other variables have a less consistent influence on the number of activities in the school and support our hypotheses lessconsistently. We had expected to find that the percent ethnic minority in the school would be negatively related to the num-ber of activities, but it is significantly negatively related only to the number of media activities and positively related to thenumber of ethnic activities. In addition, the student–teacher ratio is not significantly related to activity availability of anytype.

7.2. Activity availability and participation

Our second research question regards the relationship between availability of activities and student participation rates.Table 3 reports results from an analysis predicting student reports of participation from the availability of the activities atschool, net of the school characteristics. The reader will recall that students are asked about participation in six differenttypes of activities—academic, arts, ‘‘other,” service, sports, and vocational. Model 1 reports total participation based onthe number of activities. Each subsequent model takes each type of activity in turn and examines the relationship betweenthe availability of that particular activity and its participation rates. Only models with statistically significant results foractivity type are presented here. Thus, models for academic activity participation are not included because none of the types

12 We also considered the possibility that teacher experience would be related to activity availability, instead of student–teacher ratio. To this end, we createda variable measuring the percent of teachers in the school who had fewer than three years of teaching experience. Results were consistent with those presentedfor student–teacher ratio.

13 There were no significant predictors for arts or governmental activities and the R2 values for these models were all under 0.05. Thus, in the interest ofparsimony in the tables, we do not present the results from the models with these dependent variables.

Table 2Results from multivariate OLS or negative binomial regressions of activity availability: North Carolina public high schools.

Totalactivities

Academicactivities

Ethnicactivities

Honorsactivities

Mediaactivities

Musicactivities

Rec sportsactivities

Serviceactivities

Sportsactivities

Vocationalactivities

Urban 2.87 0.22* -0.23 0.16 0.37 0.03 0.27 0.35** 0.04 �0.29***

(1.99) (.11) (.27) (.14) (.24) (.16) (.17) (.13) (.04) (.10)Suburban 0.74 0.09 �0.33 �0.04 0.23 0.01 0.07 0.17 0.04 �0.09

(1.43) (.08) (.24) (.11) (.19) (.12) (.14) (.10) (.03) (.07)% Minority �0.02 0.00 0.02* 0.00 �0.01* 0.00 �0.01 0.00 0.00 0.00

(.05) (.00) (.01) (.00) (.01) (.00) (.00) (.00) (.00) (.00)% Free lunch �0.16* �0.01 0.00 �0.01* 0.01 0.00 �0.01 �0.01* �0.001** 0.00

(.07) (.00) (.01) (.01) (.01) (.01) (.01) (.01) (.002) (.00)School size

(logged)14.26*** 0.42** 1.28*** 0.08 0.75** 0.41* 0.74*** 0.42** 0.29*** 0.32**

(2.13) (.12) (.33) (.16) (.28) (.17) (.20) (.15) (.05) (.10)PPETotal/100 0.17 0.01 0.04* 0.01 0.01 0.02 0.03* 0.00 0.00 �0.01

(.11) (.01) (.02) (.01) (.01) (.01) (.01) (.01) (.00) (.01)Student/teacher

ratio�0.25 0.02 �0.02 0.02 �0.05 �0.01 �0.05 0.01 �0.01 �0.03

(.36) (.02) (.05) (.03) (.05) (.03) (.03) (.02) (.01) (.02)Constant �57.41*** �2.16* �12.57*** �0.88 �5.66** �2.72* �5.42*** �2.25* 1.29*** 0.28

(15.28) (.87) (2.34) (1.13) (1.97) (1.25) (1.39) (1.06) (.35) (.71)

Type ofregression

OLS Neg. binomial Poisson Poisson Poisson Neg. binomial Neg. binomial Neg. binomial Poisson Poisson

Adjusted R2 0.39F-Stat 24.73***

Likelihoodratio v2

74.49*** 60.19*** 26.58*** 19.60** 15.63* 51.90*** 71.63*** 161.36*** 19.84**

Log likelihood �541.50 �211.63 �409.41 �267.07 �504.99 �380.75 �448.51 �728.57 �541.88N 258 258 258 258 258 258 258 258 258 258

* p < .05.** p < .01

*** p < .001.

304 E. Stearns, E.J. Glennie / Social Science Research 39 (2010) 296–309

of activities predicted academic club participation, and two models for ‘‘Other” activities are included because two differenttypes of activities are associated with this type of participation.

For all of the participation rates except for academic activity participation, the participation rate was significantly asso-ciated with the availability of activities in the school. These results emerged in bivariate regressions (not shown) and, for themost part, held up with the introduction of control variables, as shown in Table 3. For example, participation in all kinds of

Table 3Results from OLS regressions of activity participation on activity availability: North Carolina public high schools.

Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7

Total Arts Other Other Service Sports Vocational

Activity availabilityTotal activities 0.09** (.03)Academic activities 0.43** (.16)Media activities 1.21* (.57) 1.03*(.44)Service activities 0.66** (.21)Sports activities 0.32** (.09)Vocational Activities 0.79*** (.18)

School characteristicsUrban 3.80*** (.96) 4.74** (1.46) 1.94 (1.14) 2.13 (1.14) 3.07** (1.05) 4.13*** (1.12) �2.28 (1.23)Suburban 0.55 (.68) 2.71* (1.04) 0.29 (.81) 0.24 (.81) 1.30 (.75) 1.80* (.80) �1.55 (.86)% Ethnic minority �0.10*** (.02) �0.06 (.04) �0.08** (.03) �0.06* (.03) �0.03 (.02) �0.08** (.03) �0.03 (.03)% Free/reduced lunch 0.00 (.04) �0.04 (.05) �0.02 (.04) �0.04 (.04) �0.03 (.04) �0.07 (.04) 0.04 (.04)School size (logged) �2.27* (1.10) �1.07 (1.58) 1.91 (1.23) 2.08 (1.23) �0.50 (1.12) �5.54*** (1.30) �4.833*** (1.32)Per-student expenditure 0.17** (.05) 0.13 (.08) 0.14* (.06) 0.15* (.06) 0.13* (.06) 0.35*** (.06) �0.09 (.07)Pupil/teacher ratio 0.08 (.17) 0.17 (.26) 0.00 (.20) 0.06 (.20) 0.05 (.18) 0.38 (.20) �0.06 (.22)Constant 80.11*** (7.47) 22.94* (11.26) 6.49 (8.81) 4.87 (8.78) 2.30 (8.02) 54.96*** (8.69) 45.48*** (9.21)Adjusted R2 0.25 0.11 0.19 0.18 0.14 0.32 0.25F-Stat 11.58*** 4.81*** 8.50*** 8.20*** 6.18*** 16.11*** 11.84***

N 258 258 258 258 258 258 258

* p < .05.** p < .01.

*** p < .001.

E. Stearns, E.J. Glennie / Social Science Research 39 (2010) 296–309 305

activities is significantly higher in schools that provide more activities. Furthermore, participation in service activities is sig-nificantly higher in schools that provide more service activities. Likewise, ninth grade students report participating in sportsmore frequently when they attend schools with more sports activities available. Interestingly, the provision of recreationalsports does not have a significant relationship to sports participation rates, net of other variables, but the provision of inter-mural sports does. Students also report higher participation rates in vocational activities in schools with more of these typesof activities. In addition, schools that provide greater numbers of media and academic activities also have higher percentagesof students reporting that they participate in ‘‘other” activities, net of other variables.

The results in Table 3 are a bit less clear for the relationship between arts activities and arts participation. In bivariaterelationships, arts, music, and media activities are all significantly associated with the arts participation rate. Yet art and mu-sic activities are not significantly associated with the arts participation rate, net of other school characteristics. While thenumber of arts activities is not significantly associated with the arts participation rate, it is possible that students considerparticipation in some of our other types of activities to be ‘‘arts” participation. For instance, the number of media activities ina school is significantly associated with the arts participation rate, net of other school characteristics.

Interestingly enough, once activity availability is accounted for, we do not find a significant relationship between school sizeand participation rates for all types of activities, an association that has been widely reported in the literature (e.g., McNeal,

Table 4Results from multivariate OLS regressions of school % at grade level on activity availability and ninth graders’ extracurricular activity participation: NorthCarolina public high schools.

Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Model 8Totalactivities

Academicactivities

Serviceactivities

Sports Totalactivities

Academicactivities

Serviceactivities

Sports

Constant 40.37***

(10.74)40.86***

(10.53)37.17***

(10.59)39.63***

(10.58)32.88**

(11.54)33.47**

(11.26)29.05*

(11.26)33.21**

(11.39)

Activity availabilityTotal activities 0.11*

(.04)0.07(.04)

Academic activities 0.66**

(.19)0.46*

(.18)Service activities 0.61*

(.27)0.21(.27)

Sports activities 0.32**

(.11)0.21*

(.10)

Activity participationAcademic

participation rate�0.19(.13)

�0.21(.13)

�0.18(.13)

�0.20(.13)

Arts participation rate �0.01(.06)

�0.02(.06)

�0.01(.06)

�0.01(.06)

Other participationrate

0.20*

(.08)0.19*

(.08)0.20*

(.08)0.21**

(.08)Service participation

rate0.36***

(.10)0.36***

(.10)0.35***

(.10)0.36***

(.10)Sports participation

rate0.17*

(.08)0.19*

(.08)0.18*

(.08)0.16*

(.08)Vocational

participation rate�0.06(.07)

�0.06(.07)

�0.06(.07)

�0.06(.07)

School characteristicsUrban 3.40*

(1.37)3.04*

(1.36)3.17*

(1.39)3.45*

(1.36)1.15(1.35)

0.94(1.35)

1.10(1.36)

1.21(1.35)

Suburban 1.73(.98)

1.64(.97)

1.61(.98)

1.54(.98)

0.75(.94)

0.71(.93)

0.71(.94)

0.65(.94)

% Ethnic minority �0.32***

(.03)�0.33***

(.03)�0.32***

(.03)�0.31***

(.03)�0.28***

(.03)�0.29***

(.03)�0.28***

(.03)�0.28***

(.03)% Free/reduced lunch �0.06

(.05)�0.06(.05)

�0.07(.05)

�0.05(.05)

�0.02(.05)

�0.02(.05)

�0.03(.05)

�0.02(.05)

School size (logged) 2.47(1.58)

3.04*

(1.47)3.50*

(1.48)2.15(1.59)

2.66(1.58)

2.94*

(1.47)3.48*

(1.47)2.25(1.60)

Per-studentexpenditure

0.23**

(.08)0.23**

(.08)0.24**

(.08)0.25**

(.08)0.13(.08)

0.13(.08)

0.13(.08)

0.14(.08)

Student/teacher ratio �0.13(.24)

�0.21(.24)

�0.18(.24)

�0.13(.24)

�0.20(.23)

�0.25(.23)

�0.23(.23)

�0.19(.23)

Adjusted R2 0.62 0.63 0.62 0.62 0.67 0.68 0.67 0.67F-Stat 52.96*** 54.72*** 52.35*** 53.62*** 38.17*** 39.05*** 37.74*** 38.54***

N 258 258 258 258 258 258 258 258

* p < .05.** p < .01.

*** p < .001.

Table 5Results from multivariate OLS regressions of school dropout rate on activity availability and ninth graders’ extracurricular activity participation: North Carolinapublic high schools.

Model 1 Model 2 Model 3 Model 4Total activities Academic activities Total activities Academic activities

Constant 11.57*** (3.22) 11.71*** (3.19) 18.07*** (3.59) 18.29*** (3.53)

Activity availabilityTotal activities �0.03* (.01) �0.02 (.01)Academic activities �0.13* (.06) �0.08 (.06)

Activity participationAcademic participation rate 0.00 (.04) 0.01 (.04)Arts participation rate �0.01 (.02) �0.01 (.02)Other participation rate �0.03 (.03) �0.02 (.03)Service participation rate �0.02 (.03) �0.02 (.03)Sports participation rate �0.06* (.03) �0.06* (.02)Vocational participation rate �0.07** (.02) �0.07** (.02)

School characteristicsUrban �0.67 (.41) �0.61 (.41) �0.50 (.42) �0.46 (.42)Suburban 0.41 (.29) 0.42 (.29) 0.46 (.29) 0.47 (.29)% Ethnic minority 0.02 (.01) 0.02* (.01) 0.01* (.01) 0.01 (.01)% Free/reduced lunch 0.02 (.02) 0.02 (.02) 0.02 (.02) 0.02 (.02)School size (logged) 0.15 (.48) �0.02 (.45) �0.34 (.50) �0.46 (.46)Per-student expenditure �0.08** (.02) �0.08** (.02) �0.06* (.03) �0.06* (.02)Student/teacher ratio �0.13 (.07) �0.11 (.07) �0.12 (.07) �0.11 (.07)Adjusted R2 0.18 0.18 0.24 0.24F-Stat 7.86*** 8.01*** 6.63*** 6.68***

N 258 258 258 258

* p < .05** p < .01.

*** p < .001.

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1999; Schoggen and Schoggen, 1988). It seems that activity availability mediates the relationship between school size andactivity participation for arts, other, and service participation. Even though school size was positively associated with numbersof sports and vocational activities (Table 2), it is negatively associated with sports and vocational participation.

7.3. Activity availability, participation, and academic outcomes

Our third research question concerns whether there is a link between the resources of activities, the investments of par-ticipation, and academic outcomes. In Tables 4 and 5, we investigate whether schools with larger numbers of activities willalso have higher academic achievement and lower dropout rates and whether participation mediates any association be-tween numbers of activities available and academic outcomes. Schools may provide activities for students, but the benefitsto those students may depend on whether they take advantage of the activities by participating in them. In these tables, wepresent unstandardized coefficients, as well as standard errors, the latter of which appear in parentheses. Only models withstatistically significant results for activity type are presented.

Table 4 examines the percentage of students performing at grade level, and Table 5 presents results for analysis ofthe dropout rate. For the academic achievement outcome, three out of the twelve different types of activities are sig-nificantly associated with the outcome, along with the total number of activities. For dropout rates, only one type ofactivity, along with the total number of activities, is significantly associated with the outcome. The results in Tables4 and 5 suggest that the availability of certain types of activities is positively associated with academic outcomesand that some of these relationships are mediated by higher participation rates. For example, in Table 4, Models1–4 show that the number of total activities, as well as academic, service, and sports activities, are all positivelyand significantly related to the percentage of students performing at grade level, net of other school characteristics.These results indicate that there is, in fact, a link between these types of resources and academic outcomes, net ofother school characteristics.

Models 5–8 indicate that participation in activities mediates some of the link between activity availability and participa-tion. Specifically, Models 5 and 7 show that extracurricular activity participation mediates the relationship for total activitiesand for service activities, such that the relationship between total activities and service activities and average academicachievement is no longer statistically significant. In Models 6 and 8, a significant association remains for the number of aca-demic and sports activities, but the magnitude of the coefficients has declined somewhat from Models 2 and 4. Those schoolsthat provide more of these types of activities have proportionately more students performing at grade level, net of structuralfactors and participation rates.

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The story for dropout rates is a bit more straightforward in Table 5. Here, only the availability of total activities and aca-demic activities are significantly associated with the dropout rate. They are associated in the predicted direction, as thoseschools with more activities have lower dropout rates. In the case of both of these measures, the relationship betweenthe activity availability and dropout rate is mediated by the percentage of students who participate in various types of activ-ities. For this outcome, it appears that the investments that students make in extracurricular activities, in the form of par-ticipation rates, mediate the relationship between the activities and academic outcomes. Specifically, participation in sportsand vocational activities appear to be the only two types of activity participation that have a significant effect on the dropoutrate: each of these is negatively associated with the dropout rate, indicating that those schools that have higher percentagesof students participating in sports and vocational activities also have lower dropout rates.

8. Conclusion

Extracurricular activities are a resource for students, an opportunity for them to learn both academic and non-academicskills and to establish relationships with other students and teachers. They provide a chance for students to develop intel-lectually and socially in a relatively informal setting. In deciding how many and which activities to offer, schools are influ-enced not only by student interest in activities, but also by external political and budgetary considerations. For instance,more socially conservative rural communities may be less likely to support a club like the Queer-Straight Alliance than EastChapel Hill High School, while urban schools are less likely than rural schools to sponsor a chapter of Future Farmers ofAmerica. We find surf clubs in high schools located near the beach and snow ski clubs in schools in the mountains. Further-more, in today’s political and budgetary climate, with schools struggling to meet the standards imposed by the No Child LeftBehind Act with little cushion in their budgets, extracurricular activities can be seen as an extravagance, and schools mayremove their financial support from them in an effort to cut their budgets.

In this paper, we extend the extant research not only by examining the distribution of various types of activities, but alsoby connecting the distribution of those activities to participation rates and to academic outcomes. Our results suggest thatthe availability of activities reflects inequality and may help to generate it, as those schools with more activities in them havebetter academic outcomes, including higher levels of achievement and lower dropout rates. Thus, we connect the presence ofstructural resources with individuals’ decisions to participate and with schools’ academic outcomes, contributing to anemerging literature that links structurally-based inequalities in resources to individuals’ investments in those resources.

As with so many other resources, extracurricular activities are not equally distributed across schools. Our findings, whilenot entirely consistent across activity type, indicate that the landscape of opportunity to participate varies by several struc-tural factors. Consistent with other studies, we find that students attending larger schools have a larger number of potentialactivities in which to participate than students attending smaller schools, although this is not true with respect to honorsactivities. The student poverty level is negatively associated with the number of activities available. Given that many activ-ities rely on parent financial support, either directly or by raising funds through selling goods, schools serving poorer chil-dren may not be able to afford as many activities. Ethnic clubs and recreational sports are influenced by per-studentexpenditure, but we did not find a consistent relationship between per-student expenditure and the total number of activ-ities. We suspect that this finding may be due to the rather limited range of per-student expenditure found in the schools in asingle state (see Table 1). Furthermore, we could not account for the cost of each activity; schools with lower per-studentexpenditures may provide a greater number of low-cost clubs. This distinction may be behind the lack of consistent findingsfor school location as well, although our results supported our hypotheses regarding school location and academic and ser-vice availability, with urban schools offering more of these clubs than rural schools do. In addition, we did not find consistentresults between the percent minority in the student body and the availability of activities. Here, we suspect that other schoolcharacteristics are superseding student body composition.

In providing activities, schools give students the opportunity to participate. Unless the students participate, however, thisis only an unrealized opportunity to gain the potential benefits associated with activity participation. Although school sizewas associated with the activities available, it is not consistently associated with participation rates once the numbers ofactivities are controlled. Thus, although larger schools can offer more activities, the patterns of participation for arts, other,and service activities are the same in large and small schools. Patterns of participation in sports and vocational activities dodiffer by school size, with students less likely to participate in larger schools. Studies of extracurricular activities need to ac-count for the opportunities available.

In general, our results show that availability of different kinds of activities predicts participation rates, net of other factors.To draw a parallel between our research and that of Roscigno et al. (2006) and Charles et al. (2007), our results suggest thatmore people are more likely to make investments—or to participate in extracurricular activities—when more resources—orextracurricular activities—are available. We did not find, as might be the case, that schools with more extracurricular activ-ities are inspiring greater participation from a limited number of people, but that schools with more activities have partic-ipation from more students than schools with limited numbers of activities, net of other factors. We find that this is trueacross activity type, with two exceptions. First, the availability of academic activities does not significantly predict the levelof reported academic activity participation. However, given that academic activities do predict the level of ‘‘other” activityparticipation, it is possible that the ninth grade students who are answering the questions regarding activity participationare confusing the two. Second, the availability of ‘‘arts” activities is not significantly associated with arts participation.

308 E. Stearns, E.J. Glennie / Social Science Research 39 (2010) 296–309

But the availability of ‘‘media” activities is significantly associated with arts participation, again suggesting that a level ofconfusion among the ninth grade students who are answering the questions regarding activity participation.

Finally, we ask whether the activities themselves are associated with academic outcomes, or whether participation ratesmediate between activity availability and academic achievement and dropout rates. Our results indicate that some types ofactivities, particularly academic and sports activities, are associated with the student outcomes of academic performanceand staying in school. For academic and sports activities, opportunities to participate have a positive and significant influ-ence on academic achievement that persists even net of participation rates, although it is mediated somewhat by participa-tion rates. Some types of activities may be more prestigious than others, and in particular, academic clubs and sports may beperceived as paths to college. For the most part, however, participation rates mediate the association between resources andoutcomes, suggesting that it is not enough for schools to provide resources: instead, in order to expect the benefits of extra-curricular activity participation, they must also offer activities that match student interest and encourage students to par-ticipate in those activities.

Several different mechanisms may account for the association between activity participation and academic outcomes,some of which indicate a causal relationship. Establishing whether the relationship is causal is, however, beyond the scopeof this research. It may be that, in finding schools with high participation rates, we are identifying those schools that functionwell as communities, with students who engage with the school community through extracurricular activities. These stu-dents, then, are also doing well in terms of their academic achievement and in staying in school. On the other hand, partic-ipation in extracurricular activities may lead to improved attitudes toward school. Students who like school might workharder at their academic work and be less likely to leave a setting that they like.

Participation in activities may also increase students’ commitment to school, thus lowering their risk of dropping out. Ourresults regarding the association between sports and vocational activity participation and dropout rates suggest that thesetwo types of participation may be particularly useful for keeping potential dropouts in school. These results are consistentwith existing research on sports participation (Davalos et al., 1999; Mahoney, 2000; Mahoney and Cairns, 1997), but do sug-gest avenues for further investigation. Furthermore, depending on the type of activity, students may learn useful skills thatwill help them in their academic courses. In addition, students may build social capital with other students and teachers.Their involvement in school-based extracurricular activities may give some structure to their discretionary time, leavingthem less time to engage in deviant activities. Whatever the mechanism, our results clearly and consistently link participa-tion rates and academic outcomes.

There are, however, a number of limitations to our findings. In examining all types of extracurricular activities, we treatthe activities as equivalent, even though they probably require different amounts of investments of time and energy. Differ-ent activities also have varying requirements and/or prerequisites for participation and varying activity advisors/coachesmay be more or less amenable to having more students participate in the activities. Unfortunately, our data would not allowus to make finer distinctions among different types of activities or different levels of student commitment to each activity. Inaddition, it would also be useful to examine participation throughout high school for these students, but our data are limitedto ninth grade students. Given the nature of the questions that we are asking, however, ninth graders provide the best oppor-tunity to answer questions regarding how the structure of opportunity is related to decisions to participate in extracurricularactivities.

For a number of reasons, extracurricular activities are important for many high school students, and these experiencesmay continue to influence them after high school. Emphasis on school accountability in policies like No Child Left Behindmay shift school resources away from extracurricular activities, such as sports teams and other activities that are not directlyrelated to student achievement. Schools with fewer resources and a lower academic profile may be more likely to cut suchprograms. Yet our results suggest that schools that provide more extracurricular activities and have more students partici-pating have better academic outcomes in terms of performing at grade level and staying in school. Thus, extracurricularactivities may help students become engaged with learning and enhance a school’s academic profile.

Acknowledgments

This work was supported by grants from the Education Policy Working Group of the Provost’s Initiative in the Social Sci-ences at Duke University and a Faculty Research Grant from the University of North Carolina at Charlotte. Many thanks toLinda Renzulli for her comments on an earlier draft of this paper and to Meredith Badinelli-Best for her able researchassistance.

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