Silviase/jgov_v1.4_full_ann huggingface dataset:
deepen our understanding of parental strategies in using EAs during the early elementary

years (grades 1 to 4). Specifically, the study investigates whether (1) children’s participation

in extracurricular activities (EAs) varies according to parents’ educational backgrounds (as a

proxy for socioeconomic status), (2) their EA participation is related to two aspects of their

non-cognitive development, and (3) the EA participation mediates a relation between parents’

educational background and non-cognitive development.

### 2. Relevant Literature

#### 2.1. Social Class and EA Participation in Elementary Education

Two different childrearing approaches, “concerted cultivation” and “the

accomplishment of natural growth”—these terms were coined by Lareau (2003, 2011) in her ethnographic work—have been widely used to understand social class inequality and its impact on children’s cognitive and non-cognitive development. “Concerted cultivation” is a cultural logic of childrearing that middle-class parents tend to follow; with respect to the topic of this article, these advantaged parents are more likely to organize their children’s time by using leisure activities orchestrated by adults. On the contrary, working-class and poorer counterparts follow “the accomplishment of natural growth,” an alternative cultural logic of childrearing that presumes that children will grow up acceptably without much adult intervention; these children participate in fewer organized activities. A qualitative study by
Chin and Phillips (2004) offers a different view by assessing summer activity gaps; this study

found that, while parental desires to help their child develop skills do not vary by social class,

disadvantaged parents have more limited financial and institutional resources, resulting in

unequal access to such activities (Chin and Phillips 2004). Quantitative studies using

large-scale longitudinal data basically support Lareau’s point that social class is associated

with parents’ application of a “concerted cultivation” childrearing style during the elementary

years (e.g., Bodovski 2010; Bodovski & Farkas 2008; Cheadle 2009; Cheadle & Amato 2011;

Covay and Carbonaro 2010).

As found in the United States, higher-SES parents are more likely to use EAs to

benefit their children in Japan. Most studies (e.g., Baker et al. 2001) focus on EAs in

academics, referred to as shadow education, at the secondary education level. Several studies,

however, have assessed relationships between family SES and elementary-age children’s

participation in shadow education services in Japan.

According to Kaneko (2004), 54.2% of sixth-grade pupils, at public schools in

Tokyo and surrounding prefectures, whose fathers graduated from college took some type of

juku (shadow education services in academics) as compared to 33.9% of those with fathers

who did not complete college. This disparity is especially large for shadow education services

that specifically focus on preparation for the entrance examinations of prestigious private

junior high schools; 15.4% of the sixth-grade students with college-educated fathers attended
this type of juku, compared to only 4% of their counterparts with non-college-educated fathers. Similarly, Honda (2008), using a nationally representative retrospective survey, found that college-educated mothers tended to practice childrearing consistent with “concerted cultivation,” including the use of shadow education services when their children were attending elementary schools. Sugihara (2011) also demonstrated unequal access to enrichment lessons in the shadow education industry, based on the educational level of both parents, at the fifth-grade level in Tokyo. As for younger children, a small longitudinal study including both surveys and interviews (Holloway, Yamamoto, Suzuki, & Mindnich 2008) showed, based on responses from 116 mothers, that college-educated mothers with financial resources are more likely to use shadow education for their child at the second-grade level, and that educated mothers appear to value cultivating their child’s skills. Furthermore, through in-depth interviews with 16 mothers over three years (when their child was in preschool through second grade), Yamamoto (2013) reported that middle-class mothers use shadow education services and extracurricular activities, whereas working-class mothers rarely do so. In addition, large-scale, Internet-based surveys were conducted in 2009 and 2013 by Benesse, the largest private correspondence education provider in Japan. Reports on the 2009 survey data (Kataoka 2010; Nishijima, Kimura, & Suzuki 2012), which included children from age 3 to grade 11, assessed factors associated with EA participation and indicated relationships between family SES (i.e., parents’ educational backgrounds and
household income) and EA participation (sports and art activities).

#### 2.2. Extracurricular Activity Participation and Elementary-Age Children's Development

Through EA participation, children demonstrate their skills and are evaluated by

others, having experiences of success and failure like those in school; such organized,

structured activities help children to develop skills, attitudes, and behaviors aligned with

school success (Lareau 2003, 2011). Studies using data from the Early Childhood

Longitudinal Study–Kindergarten Class of 1998–99 (ECLS-K) have indicated some effects of

EA participation on forms of cognitive and non-cognitive skills and development, such as

reading achievement (Bodovski & Farkas 2008) and math skills (Dumais 2006). Additionally,

Covay and Carbonaro (2010), also using the ECLS-K, focused on relationships between

children’s family SES, EA participation, and advantage in cognitive and non-cognitive skills.

They showed that third-grade pupils from advantaged families tended to participate in six

types of EAs (sports, clubs, dance, music, art, and performing arts), and that participation in

some EAs influenced non-cognitive skills (approaches to learning) and cognitive skills (math

and reading scores), explaining a modest but identifiable portion of SES-related advantage in

both skill types.

Fletcher, Nickerson, and Wright (2003) indicated that participation in club activities

is related to academics and positive teacher evaluations of academic ability, and involvement
in EAs sports is associated with higher teacher evaluations of social ability, though their sample size was small (N = 147). In addition, other studies with relatively small samples showed positive relationships between some types of EA participation and well-being (Lagacé-Séguin & Case 2008), teacher evaluated socio-emotional behavior (Metsäpelto & Pulkkinen 2011), and behavioral adjustment in school (Molinuevo et al. 2010). Furthermore, studies focusing on the effects of participation in organized team sports activities indicated that it increases self-esteem (Slutzky & Simpkins 2009) and decreases social anxiety (Schumacher Dimech & Seiler 2011). It should be noted, however, a study using large-scale cross-sectional data (Howie et al. 2010) shows no difference between children with and without EA participation in terms of problem behaviors.

In Japan, most studies assessing effects of EA participation have focused on relationships between taking shadow education courses and educational achievement (e.g., whether students are accepted by competitive high schools or universities) at the secondary level; they have not examined the effects of EA participation during the elementary years or the impact of other types of EAs, such as music and sports. As for academic EAs in the elementary years, following Lareau (2003), the study by Honda (2008), using nationally representative retrospective data on mothers and children, showed that a “rigorous” childrearing aligned with “concerted cultivation,” including use of shadow education services during the elementary years, predicted higher academic achievement in ninth grade that was
subsequently related to later educational and occupational achievement.

### 3. Rationale for This Study

The literature suggests, on the whole, an association between social class and EA participation (e.g., Lareau 2003, 2011), and that EA participation contributes to children's cognitive and non-cognitive development (e.g., Covay & Carbonaro 2010). Meanwhile, studies in Japan have revealed associations between SES and EA participation including shadow education services (e.g., Juku), but have not assessed effects of EA participation at the elementary level. Moreover, some methodological issues in the Japanese literature need to be addressed. The studies in Japan utilize retrospective or cross-sectional (often regional) data that do not capture the gradual changes in EA participation. Given the cross-sectional nature of the data, it would be difficult to reveal the direct effects of EA participation on any aspects of child development over time.

To overcome the lack of studies and this methodological weakness in existing

research, this study analyzes unique longitudinal data that include information regarding EA participation and child development over four years along with time-invariant family SES (i.e., parents' educational backgrounds as a proxy). More specifically, the study investigates whether (1) children participate differently in EAs according to parental education level (observed in each of four years, from first through fourth grade), (2) EA participation during
early elementary school years is related to two aspects of children's non-cognitive development (i.e., problem behavior and orientation to school), and (3) parental education level is associated with the non-cognitive aspects of child development through the differences in EA participation related to parental education level. While this study cannot assess cognitive aspects of child development because the dataset does not contain this information, it should illuminate the relationships between SES, EA participation, and children's non-cognitive aspects of development in Japan, where parental advantages are transmitted to their children largely outside the centralized, relatively egalitarian compulsory education system. It should be highlighted that Japanese schoolteachers evaluate non-cognitive as well as cognitive development; specifically, they assess children's classroom behaviors and attitudes and document the results on a report card at the end of each semester beginning in first grade. These subjective judgments of the teacher become part of children's evaluation criteria along with the results of conventional written examinations, and thus they can be important in affecting later decisions on students' admission to high schools and universities (Kariya 2009a). It is therefore crucial to investigate whether parents' educational background, a major component of SES, influences children's behavioral problems and orientation to school from the very first year of compulsory education, which is likely to be the root of behavioral and attitude differentiation in the formal school system. The present study examines parents' strategies for transmitting their advantages to their children along
with consequences of unequal access to learning opportunities outside school, in a society where children receive relatively similar school experiences nationwide.

### 4. Research Questions and Hypotheses

This study examines the effect of unequal access to EA participation—a potential source of inequality outside the official school system—on students' behavior and orientation to school that schoolteachers formally and informally evaluate. The first research question is as follows:

(RQ1) Is parental education background associated with children’s EA

participation?

It is hypothesized that college-educated parents are more likely to employ three categories of EA (i.e., academics, high culture, and sports), since the advantaged parents demonstrate “concerted cultivation” (Lareau 2003, 2011) and “rigorous” childrearing (Honda 2008). The study considers parental education background as a proxy for SES, as the literature (e.g., Cheadle and Amato 2012) indicates that parental education is the strongest predictor of social-class parenting practices interpreted as “concerted cultivation” whereas other perspectives of social class such as household income are more weakly related to them.

After empirically clarifying the relationship between parental education level and each type of EA participation, respectively, the study tackles the second research question:
(RQ2) Are the three categories of EA participation related to levels of and changes in

the two aspects of children’s non-cognitive development?

In this research question, levels indicate differences between individuals and changes in their learning. It is hypothesized that each category of EA participation is related to levels of changes in children's problem behavior and orientation to school, since prior research indicates that participating in organized activities outside school hours is associated with children's well-being (Lagacé-Séguin & Case 2008), socio-emotional behavior (Metsäpelto & Pulkkinen 2011), and behavioral adjustment in school (Molinuevo et al. 2010). Especially, EA participation should help them adapt to school (e.g., interacting comfortably with teachers) and to have a positive orientation to school, as children obtain learning experiences in adult-led, structured activities that are similar to school settings (Lareau 2003, 2011).

(RQ3) Is parental education background related to levels of the two aspects of children's non-cognitive development through the three categories of EA participation?

This study hypothesizes that parents with higher education tend to send their child to EAs (RQ1), and that EA participation influences the two aspects of children’s non-cognitive development (RQ2). If so, parental education level should be related to individual differences in the two aspects of children’s non-cognitive development through the three categories of
EA participation. Therefore, the study hypothesizes that EA participation partly mediates the relationship between parents' education level and their children's non-cognitive development.

### 5. Method

#### 5.1. Data

This study uses the Longitudinal Survey of Babies in the 21st Century, conducted by the Ministry of Health, Labour and Welfare in Japan. This longitudinal survey includes ten waves of national data collected between 2001 and 2011, targeting 53,575 babies born during January 10–17 and July 10–17, 2001 in Japan. Because the monthly vital statistics collected by the Ministry of Health, Labour and Welfare indicate no systematic or seasonal pattern in the population, the data are assumed to be representative. Most respondents to the survey were mothers. This survey was initially administered at approximately six months postpartum (on August 1, 2001 and February 1, 2002), and then at the same time each year through Wave 6. Wave 7 was conducted 1.5 years after Wave 6, and subsequent waves were administered on January 18 and July 18 each year, since the children had reached school age. This means that the respondents' children were in the same school age from Wave 7 (first grade) to Wave 10 (fourth grade).

The average response rate for each wave was about 90%; roughly 73% of the initial sample from Wave 1 responded to the survey in Wave 10. These figures represent fairly low
attrition, and Kitamura (2013) argued that attrition bias is not a serious concern with regard to these data. It is not known why some respondents chose not to continue participating, but their reasons were most likely unrelated to child development.

The present study utilizes Waves 7 through 10, as these include information on EA participation and child development. In addition, demographic data and parental educational backgrounds were obtained from Waves 1 and 2.

#### 5.2. Dependent Variables

The study created two dependent variables: Behavior Problems Index (BPI) and Positive Orientation to School (POS). Both of these indicate non-cognitive child development factors that were repeatedly reported by survey respondents (mostly mothers) at four points in time (Wave 7 to 10).

## Behavior Problems Index (BPI)

This index of children’s behavioral problems has been used by frequently cited

sociological studies (e.g., Peterson & Zill 1986) and has been adapted for studies in sociology

of education (e.g., Domina 2005) to examine children’s socio-emotional status and well-being

This study uses 20 survey items that indicate behavioral problems. The respondents checked

all of the following items that were applicable to their child: (1) using harsh language, (2)

does not keep promises/tells lies, (3) does not initiate conversation, (4) does not listen, (5)

plays in dangerous areas, (6) delinquency, (7) spends many hours watching TV or plays video
games, (8) lack of physical exercise, (9) incessantly asks for things he or she wants, (10) does

not/cannot play with friends, (11) often fights with other children, (12) bullies/being bullied,

(13) does not want to go to school, (14) concerns about studies, (15) concerns regarding food

(including balanced diet and likes/dislikes), (16) concerns about level of sickness, (17)

worsening eyesight, (18) tendency to become sick, (19) concerns related to sex, and (20)

other. Each item checked was coded as 1, and non-checked items were shown as 0.

Responses were added to compute each child’s Behavior Problems Index (BPI) score, which

could range from 0 to 20. A higher BPI score indicates a higher degree of perceived

behavioral problems. Table 1 presents descriptive statistics of the BPI. $ ^{1} $

## Positive Orientation to School (POS)

The other dependent variable indicating a non-cognitive aspect of child development

was Positive Orientation to School (POS), which is intended to indicate a child’s attitude

toward school. $ ^{2} $ In this study, POS was created based on the respondents’ answers (with

choices of yes, no, and neither) to the following five statements: s/he looks forward (1) to

seeing friends at school, (2) to school studies (including physical education and music), (3) to

school-provided lunches, (4) to seeing teachers and trusting them, and (5) to school activities

(such as field trips and field days). The responses to the five statements were coded to create

a continuous variable: coding yes as 2, neither as 1, and nor as 0. This continuous coding was

used and responses to the five statements were added to indicate each child’s positive
orientation to school on a range from 0 to 10. $ ^{3} $

#### 5.3. Independent Variables

This study uses three key independent variables that indicate categories of EA participation: academics, high culture, and sports. The respondents indicated whether their child was participating in each of 16 types of EAs for each wave. Responses were coded into the three categories of EA participation. $ ^{4} $ These time-varying variables, measured in each wave, show the number of EAs in which the respondent's child participated for each category of EA or organized activity outside school hours; the variable for EAs in academics ranges from 0 to 3, whereas the other two variables for EAs in high culture and sports range from 0 to 2.

The study first uses these ordinal variables with a parental education variable to estimate participation rates in each category of EA, identifying relationships between parental education and EA participation. Then, these variables are included in the final analysis to clarify whether each category of EA participation explains levels of changes in children's BPI and POS scores. Table 1 presents a summary of the descriptive statistics for the following variables.

## EA Participation in Academics

This category includes six types of EAs: juku (cramming schools), abacus, calligraphy, private tutoring, distance learning, and English conversation lessons (which can
also include other languages, according to the questionnaire). These EAs are considered academically oriented, helping children to become academically advanced in school, while some parents may use this category of EA to remedy a specific skill (e.g., doing arithmetic faster). This ordinal variable indicates the number of academic EAs in which children participated. Students were coded as 0 if they participated in no EA in this category, 1 if they were involved in one EA, 2 for two EAs, and 3 for three or more EAs (a small number of students participated in four or five types of EA but were coded as 3). $ ^{5} $ Distributions of EA participation are shown in Table 2.

## EA Participation in High Culture

This ordinal variable shows the number of EAs in high culture in which the

respondent’s child participated: 0 = none, 1 = one EA, 2 = more than 2 EAs in this category.

These EAs are considered to be adult-led organized lessons in high culture. Four such types of EAs were considered: music (e.g., piano), painting/crafts, the Japanese art of flower arrangement/tea ceremony, and ballet/dance.

## EA Participation in Sports

This variable, ranging from 0 to 2, was coded in the same manner as EA participation in high culture. This category includes six types of EAs: gymnastic exercises, swimming, baseball/softball, soccer, tennis, and the Japanese art of fencing (kendo) or self-defense (judo). All these EAs require substantial physical activity even for
elementary-age children.

#### 5.4. Control Variables

Variables that indicate parents’ SES and children’s demographic information were created and then included as control variables in the analysis.

## Parental Education

This categorical variable, ranging from 0 to 2, was created to indicate parental education levels. A score of 0 means that neither parent was college-educated (N = 14,981; 44.3%). A score of 1 indicates that one of the parents received an associate, bachelor's, or graduate degree (N = 9,908; 29.3%). The other students were coded as 2, as they had two college-educated parents (N = 8,910; 26.4%). $ ^{6} $

Note that an associate degree from a two-year higher education institution is included as a college education. This categorization is based on Kikkawa (2009), who contended that Japanese society is mainly divided into two groups (depending on whether one has a college education including an associate degree), as people's education level is the strongest predictor of their opinions and attitudes regarding social issues including education (Kikkawa, 2009).

## Annual Household Income

This log-transformed variable was created based on the respondents’ answers to

Wave 7, showing each family’s extent of economic capital.
## Sex

Female children were coded as 1 and males as 0. This information was obtained

from Wave 1. Sex probably influences the types of EAs in which a child participates, as

reported by Kataoka (2010) and Nishijima, Kimura, and Suzuki (2012); more boys tend to

participate in EAs related to sports and more girls in EAs related to high culture.

## Born in January

Children born in January were coded as 1, and those born in July were indicated as 0.

This factor was also included in the analysis because parental decisions and child

development may change as the child grows up.

In addition to these time-invariant variables, three time-varying variables were

created: “housewife,” “father’s absence,” and “number of siblings.” These time-varying

variables were created based on information obtained from Waves 7 to 10.

## House wife

A mother not looking for a job or serving as a housewife was coded as 1, and all

others (e.g., full-time worker, self-employed, and part-time worker) were coded as 0. This

binary variable was created as the mother’s physical presence at home may be related to the

use of EAs and children’s non-cognitive development.

## Father's Absence

This binary variable indicates the father’s relative presence at home, specifically