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CALIFORNIA SOCIOLOGY FORUM VOL. 7 

Proximity and Social Integration 
Carla Ocampo 

Department of Sociology 
 California State University, Los Angeles 

ABSTRACT  
Research has linked integration to student persistence among 
college students. However, integration tends to be lower among 
commuter students, who make up a majority of college students. 
A separate body of research has linked schools to the formation of 
social ties. However, based on the role of proximity in shaping the 
likelihood of social tie formation, increased distance may decrease 
the formation of ties among students. Based on these findings, this 
study explores if physical proximity to campus influences 
integration into the campus community among college students. 
This study collected quantitative data about student participation, 
interaction, and proximity through a questionnaire distributed to 
students on a commuter campus. The findings did not support a 
correlation between proximity and integration. However, the data 
does show patterns related to these variables that may inform 
future research. 
 
The focus of this study is to examine student integration into the 
campus community among commuter students. Integration refers 
to student involvement in the university’s community, including 
academic and social activities (Ribera, Miller, and Dumford 
2017). Both aspects are important for student success because they 
provide a sense of academic and social support, which can foster 
attachment to the campus community. As such, research has found 
that student integration influences the educational persistence of 
college students (Kirk and Lewis 2015; Ribera et al. 2017). Kirk 
and Lewis found that integration and a sense of community have 
a positive relationship with educational persistence. College 
students who feel more socially and academically integrated into 
their campus community are less likely to drop out of school and 
more likely to graduate. Therefore, integration is important in 
determining student retention and educational success.  

Two factors that influence integration into the campus 
community are participation and interaction. Participation in 
campus events and ties to other members of the campus 



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community, such as peers and staff members, have been shown to 
support integration among students. As Ribera et al. (2017:549) 
explain, “[i]nvolving students early on in effective educational 
practices may help these students forge supportive academic and 
social relationships with members of the campus community and 
encourage positive intergroup dialogue among students from 
diverse backgrounds.” Altogether, these factors are likely to create 
a feeling of social cohesion and belonging for students, leading to 
higher rates of persistence. However, students’ integration varies 
based on several factors, including students’ place of residency, on 
or off campus. Research has found that commuter students are less 
integrated into their educational institutions and feel a lower sense 
of attachment to the community (Kirk and Lewis 2013). Lower 
attachment can harm the educational success of commuter 
students and may lead to lower student retention at commuter 
campuses. This integration gap is significant because most college 
students live off campus and must commute to attend school (Kirk 
and Lewis 2013). Therefore, a substantial portion of students have 
a low retention rate, potentially leading to lower levels of 
educational success.  

Although researchers have noted this lack of integration 
among commuter students, more research on the factors 
influencing this pattern is still needed. Research on commuter 
students and commuter campuses is more limited than research on 
non-commuter students and non-commuter campuses. Research 
has paid less attention to the issues that commuter students face 
and the factors that influence their educational experiences. 
Accordingly, this research aims to add to the current literature on 
commuter students and commuter campuses. This study examines 
the factors that shape commuter students’ integration on 
commuter campuses. More specifically, it will explore if a 
student’s proximity to campus influences their integration into the 
campus community. The dependent variable is integration into the 
campus community. Integration refers to participation in events 
and interactions with others on campus. Students are expected to 
build feelings of social support through interactions with other 
students in non-academic settings. Similarly, students are 
expected to build feelings of academic support through 
participation in academic activities and interaction with faculty. 



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Together, these measures are meant to gauge both academic and 
social involvement, which are key factors that determine feelings 
of integration. 

The primary independent variable of interest is proximity 
to campus. Proximity refers to students’ commute distance. Some 
other variables are also included as possible independent 
variables, such as commute time, commuter status, and mode of 
transportation. The hypothesis was that there would be a negative 
relationship between proximity and integration into the campus 
community. Therefore, interaction and participation are expected 
to decrease as commute distance increases. However, the study’s 
findings do not support this hypothesis. The data analysis found 
that the relationship between proximity and integration was not 
statistically significant, which does not support a correlation 
between them. Despite these findings, the data revealed patterns 
about these variables. The data points toward a low level of 
integration among the respondents, most of whom were 
commuters. Furthermore, having to commute does appear to 
influence the amount of interaction among respondents based on 
participant responses but the extent of the influence is unknown 
based on the data within this study. 

 
LITERATURE REVIEW 
Proximity and Space 
Hip, Corcoran, and Wickes (2014) explore the theory that physical 
proximity influences the likelihood of social cohesion and social 
tie formation by focusing on the impact of proximity, using the 
distance decay function as a theoretical basis. According to the 
distance decay hypothesis, “residents are most likely to form ties 
to those living near them, and this likelihood drops sharply when 
moving further away from the residence” (Hip et al. 2014:3). 
Based on this hypothesis, proximity is expected to influence social 
tie formation positively. Small and Adler (2019:115) examine the 
role of space in determining social ties and social integration 
through the relationship between social ties and proximity, 
explaining how physical proximity is widely studied as a variable 
that may influence social relations, noting that the “importance of 
propinquity to tie formation has been uncovered empirically many 
times.” Findings also suggest the likelihood of forming social ties 



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is higher with closer physical proximity between people. These 
findings support the hypothesis of the distance decay function 
with empirical backing for the relationship between physical 
proximity and the likelihood of social tie formation. As the theory 
hypothesizes, closer proximity is correlated with the formation of 
social ties. 

Research has also shown the importance of spaces that 
promote social tie formation, with Small and Adler (2019:118) 
writing, “studies have found that participation in establishments is 
associated with the characteristics of the ties formed.” These 
studies have found that participation is linked to stronger ties 
formed because of homophily. Establishments that produce 
stronger ties include schools, indicating that schools are sites that 
will promote social tie formation. In a study focusing on 
neighborhood features and community ties, Hip et al. (2014) 
found support that proximity to establishments that promote or 
dissuade social tie formation also influences social ties. Since Hip 
et al. (2014) find that proximity to these establishments influences 
the likelihood of tie formation, the researchers expected that those 
who live farther away from campus are less likely to form social 
ties and, therefore, be less integrated into the campus community. 

 
Integration  
Ribera et al. (2017) explore the relationship between a sense of 
community and participation by analyzing quantitative survey 
data. The authors draw upon secondary data from first-year 
students attending forty-four different 4-year colleges. The study 
focused on participation and college characteristics as 
independent variables and feelings of belonging as the 
independent variable. Ribera et al. (2017:560) found that along 
“with one co-curricular activity (serving as a student leader), 
participating in a learning community and engaging in a service-
learning project was found to be positively related to students’ 
sense of peer belonging and institutional acceptance.” Therefore, 
participation in activities on campus is associated with increased 
feelings of belonging. Similarly, Procentese, Gatti, and Falange 
(2019:258) used survey data to examine the same variables, 
finding that “individuals’ participation is predicted by their 
emotional and affective bond to the community and 



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representations about the relationships and responsibility-taking 
within it, via this emotional bond.” Unlike Ribera et al. (2017), 
Procentese et al. (2019) used participation as their independent 
variable and bond to the community as the dependent variable. 
Although the direction of this relationship remains unclear, the 
findings support a correlation between this set of variables. Based 
on these findings, Procentese et al. (2019) included participation 
and sense of belonging as measures of integration, although it 
focused more on participation. 

 
Factors Influencing Integration  
Persistence theory understands “‘integration’ and ‘patterns of 
interaction’ as two key components that distinguish students who 
persist with their education from those who do not” (Kirk and 
Lewis 2015:49). Kirk and Lewis (2015) examined how a student’s 
integration into their educational institution is influential on 
student persistence through how different variables influence 
integration at a commuter campus. The study uses a mixed method 
design, with a questionnaire portion and a focus group study. The 
findings indicate that students who are more integrated are more 
likely to continue their education than those who are less 
integrated. However, commuter status influences how integrated 
students are. Kirk and Lewis (2015:54) find that students “who 
lived on campus reported higher [collegiate sense of community] 
CSOC than those living off-campus.” This finding indicates that 
commuter students were less likely to feel integrated into their 
campus communities. Based on this finding, it is expected that 
there will be a low level of integration and sense of community 
from commuter students. 

Kirk and Lewis (2015) also examined the role of other 
identities in influencing integration, such as race, gender, sexual 
orientation, and marital status; however, the study found that only 
sexual orientation is a predictor of integration. These variables 
provide insight into factors influencing integration among all 
students, including those who commute. One finding explains 
lower integration and a sense of community among commuting 
students. Based on qualitative data from a case study, Kirk and 
Lewis (2015:56) found time to be an influence, and these “time 
gaps were more pronounced among commuting students who 



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acknowledged limitations with transportation and scheduling.” 
This finding points to extra time constraints faced by students who 
do not live on campus compared to those who do. Constraints 
include the time spent commuting, which can be longer based on 
commute distance or method of transportation.  

 
RESEARCH QUESTION AND HYPOTHESIS 
The main research question is: does proximity influence 
integration into the campus community among commuter 
students? Two different bodies of research have influenced the 
research question: research on space and college students’ sense 
of community. The focus on proximity is based on literature that 
examines how space influences the formation of social ties. This 
study will expand the distance decay hypothesis to examine 
proximity to campus. The distance decay function examines the 
role of geographical proximity in shaping the formation of social 
ties. According to the hypothesis, the closer the proximity between 
a person and a space, the more likely they are to form social ties 
within that space. The study aims to examine if proximity will 
influence the social ties formed on campus and student integration 
by applying the distance decay hypothesis to distance from 
campus. Based on the distance decay hypothesis, it is expected 
that students who live closer to campus will be more likely to form 
social ties on campus and therefore, will be more integrated within 
the campus community. The study measures proximity as the 
distance between where students live and their campus based on 
commute distance in miles, including commute time as a separate 
measure of proximity. The findings of Ribera et al. (2017) and 
Procentese et al. (2019) informed the conceptualization of 
integration into the campus community. Both studies found a 
relationship between social ties to the campus community and 
participation. Furthermore, Ribera et al. (2017) noted that 
participation and interaction shaped social tie formation between 
students, strengthening the feeling of community. As a result, the 
study included participation and interaction as a measure of 
student integration. 

H0: proximity to campus will not impact integration into 
the campus community. H1: proximity will have a negative 
relationship with integration. H2: proximity will have a negative 



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relationship to interaction with students. H3: proximity will have 
a negative relationship to interaction with staff members. H4: 
proximity will have a negative relationship to participation in 
events on campus. The null hypothesis, H0, predicts no correlation 
between proximity and integration is expected. Based on the 
literature on proximity, physical proximity is expected to 
influence social tie formation, therefore as students are farther 
from campus, they will be less integrated. Since the study 
operationalized integration as interaction with others and 
participation in campus events, H1 will be analyzed through 
proximity’s correlation with the measures of integration.  

An alternative hypothesis is that only commuter status 
will affect student integration. It is possible that there will be no 
difference in integration based on proximity to campus between 
commuter students. The difference may only be between 
commuter students and non-commuter students. It is also possible 
that a separate variable, such as responsibilities outside of school, 
influences this relationship. As Kirk and Lewis (2015:49) note, 
“[m]ost commuter students are faced with additional 
responsibilities beyond just being a student.” Responsibilities 
such as work can lead to less free time for students, decreasing the 
time that they spend on campus. As a result, these students would 
be less likely to interact with others or participate in events on 
campus. Accordingly, they would also be less integrated into the 
campus community due to their lack of social ties with peers and 
staff members. 

 
METHODS 
Data 
This project emerged from a secondary analysis of survey data 
collected from a target population of students enrolled at 
commuter campuses. The sampling frame for the original data 
collection was students at California State University-Los 
Angeles, since the university is a commuter campus serving the 
greater metropolitan Los Angeles area; of note, the university also 
has a large female population. The sampling process focused on 
recruiting students enrolled in required undergraduate courses 
within the College of Natural and Social Sciences (NSS). The 
sample was recruited through non-probability sampling. The 



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recruitment process involved emailing professors and asking them 
to share the recruitment flyer with their students. Initially, the 
recruitment process focused on contacting professors who were 
teaching seminar courses with high numbers of students. 
However, this later started to involve professors teaching courses 
with multiple open sections. Those who agreed shared the 
recruitment flyer by posting it on Canvas or distributing a printed 
copy in class. Emailing professors began on October 12, 2023, and 
ended on October 22, 2023. Out of 37 professors who were 
emailed, 5 replied and agreed to share the recruitment flyer with 
their class. Overall, professors’ responsiveness was low, making it 
difficult to gather participants for the questionnaire. The 
questionnaire was open to from October 12, 2023, to October 31, 
2023. Altogether, the sampling process took 20 days to complete. 
The response rate was also low among students, with most 
students from these courses not taking the questionnaire. As a 
result, the final sample included 37 students, much lower than the 
targeted sample of 100 respondents. Of the 37 responses, only 30 
were valid. The sample was drawn from classes in different 
schools within the College of NSS. Most of the respondents were 
commuter students; 4 lived on campus, and 30 did not live on 
campus, which was expected due to the demographics of the 
university. 25 respondents were female, 9 were male, 3 were non-
binary; the larger proportion of female respondents was expected 
due to the school’s demographics. The sample included 10 
freshmen, 18 sophomores, 4 juniors, and 3 seniors; characteristics 
which were also expected since the sample was drawn from lower 
division courses with higher enrollment. 
 
Methods 
The data from this study is quantitative data collected through 
responses to a questionnaire. At the beginning of the 
questionnaire, respondents were presented with an informed 
consent form, ensuring that participants freely gave consent. The 
survey also asked participants if they were over the age of 18. 
Those who answered “no” were not shown any of the following 
questions from the questionnaire. The following questions were 
ordered based on the topic. The topics were interaction and ties to 
other students, participation in campus activities, interaction and 



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ties to staff and faculty members, and demographic questions. The 
questionnaire consisted of 31 questions, including 30 closed-
ended questions and 1 open-ended question. The open-ended 
question allowed respondents to type in their commute time in 
minutes. The closed-ended questions consisted of Likert scale 
items, multiple-choice items, select-all-that-apply items, and 
slider items with set parameters.  

Questions collecting information about integration, the 
dependent variable, gathered data related to interaction and 
participation on campus. First, participants were asked about 
interaction with other students. Frequency of interaction was on a 
scale ranging from “every day” to “never.” Students’ likeliness to 
seek or offer support to other students was on a scale ranging from 
“extremely likely” to “extremely unlikely.” Participants were also 
asked about interaction with staff members, with students’ 
likeliness to seek academic or personal support from staff being 
on a scale ranging from “extremely likely” to “extremely 
unlikely.” Participants were asked how often they participated in 
events on campus, including club events, office hours, 
departmental events, and campus-wide events. Participation is a 
discrete variable using a slider to indicate the number of times 
students participated in each event in a semester.  

There were also questions within the questionnaire that 
measure the independent variable, proximity. The study measures 
proximity to campus as distance to campus in miles. Commute 
time was measured in minutes. Respondents were also asked if 
proximity influences their behavior. Perceived influence of 
proximity is split into two dichotomous variables, asking 
participants to choose “Yes” or “No” to indicate if proximity 
influenced participation or interaction on campus.  

After the data collection period, the data was transferred 
to SPSS and cleaned. The variable values for the slider questions 
and select-all-that-apply questions had to be manually inserted in 
SPSS. The variable measures were also adjusted for each item 
when needed. After cleaning the data, data analysis for this project 
began. Secondary data analysis was conducted through cross-
tabulations and chi-square tests. Data analysis focused on 
examining the correlation between independent and dependent 
variables.  



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RESULTS 
The data analysis consisted of chi-square tests and cross-
tabulations of the data collected. The chi-square tests aimed to 
measure the relationship between proximity and the study’s 
measures of integration. Chi-square tests whether there is a 
significant association between two categorical variables, such as 
nominal or ordinal. Unlike regression, chi-square testing does not 
model the relationship between a dependent and independent 
variable. A total of three chi-square tests were conducted. These 
tests focused on proximity and interaction with peers, proximity 
and interaction with staff, and proximity and participation. The 
chi-square tests include Pearson chi-square, likelihood ratio, and 
linear-by-linear association. Within these tests, a significance of 
<.05 is considered statistically significant and rejects the null 
hypothesis. Conversely, a significance of >.05 is statistically 
insignificant and does not reject the null hypothesis. 

The first analysis examined the relationship between 
proximity and interaction with peers. The cross-tabulation was run 
on items that measured proximity and the frequency of 
respondents spending time with their classmates in their free time. 
The results of the analysis on the 30 valid cases are included in 
Table 1 and Table 2 (see Appendix). The chi-square value was 
64.750 with a p-value of .173, indicating that the relationship 
between the variables is not statistically significant. The 
likelihood ratio value was 44.206 with a p-value of .851. Finally, 
the linear-by-linear association value was .096, with a p-value of 
.757. None of these tests found a significant relationship between 
the variables and the analysis supports the null hypothesis that 
there would be no relationship between proximity and interaction 
with peers on campus.  

The second analysis examined the correlation between 
proximity and interaction with staff members. Another cross-
tabulation was run on the items measuring proximity and the 
likelihood that respondents would seek support from staff about 
academic concerns. Table 2 and Table 3 show the results of the 
analysis. There were 30 valid cases in this analysis. The chi-square 
value was 41.510, with a p-value of .579. The likelihood ratio 
value was 42.770, with a p-value of .524. Finally, the linear-by-
linear association value was 2.066, with a p-value of .151. Again, 



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none of the tests found a significant relationship between the 
variables, reinforcing the null hypothesis that there is no 
relationship between proximity and interaction with staff 
members on campus. 

For the final analysis, the data was examined through 
another cross-tabulation. This analysis focused on proximity and 
participation in events on campus. The cross-tabulation was run 
on data collected about proximity and those who indicated 
participating in no campus activities. Table 5 and Table 6 show the 
results of this analysis. There were 30 valid cases included in the 
analysis. The chi-square was 9.225 with a p-value of .601. The 
likelihood ratio value was 12.052, with a p-value of .360. The 
linear-by-linear association value was 1.023, with a significance 
of .312. None of these values were statistically significant, 
meaning the null hypothesis could not be rejected since there was 
no relationship between proximity and participation in events on 
campus. 

Based on these three analyses, a null relationship exists 
between proximity and integration into the campus community. 
Analysis found that none of the measures of integration were 
correlated with proximity. However, an examination of the 
responses shows some patterns. The data indicates that 
respondents consider their commute to influence the amount of 
time they spend interacting with others and participating in events 
on campus. 24 of the respondents answered that proximity 
influences how often they interact with other students. 
Furthermore, the data shows that many of the respondents have 
low levels of integration into their campus community, with 22 
respondents answering that they did not participate in any 
activities on campus. 7 respondents indicated that they 
participated in office hours. Finally, 17 respondents answered that 
they never spent time with their classmates during their free time. 

Several limitations impacted the representativeness of this 
study. Due to the sampling method the study employed the 
research findings may have limited generalizability to California 
State University students. Since the study used non-probability 
sampling to recruit the sample, it is less representative of the 
students than a sample recruited through probability sampling. 
The sampling frame also focused on general requirement courses, 



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which first and second-year students tend to take. Kirk and Lewis 
(2015) found that the number of years students have attended their 
school influenced their integration. Therefore, it is likely that there 
are differences in integration among first and second-year students 
compared to students who have attended the school longer.  

Another limitation is that the study only drew its sample 
from one campus. The demographics of California State 
University Los Angeles may have influenced the findings, since 
the university primarily serves students of color, with a large 
Hispanic population, which is not representative of all commuter 
campuses. Students of different ethno-racial backgrounds may 
face different circumstances that influence their integration in 
school, resulting in the collection of different responses. A more 
diverse sample of students could help determine if differences in 
integration exist between various ethno-racial groups. The small 
sample size also greatly limits the validity and representativeness 
of the sample and the resulting data. However, bootstrapping the 
data could strengthen the statistical analysis, which I failed to 
account for while analyzing the data. Bootstrapping samples from 
the existing data to estimate the properties of a larger sample to 
provide a more accurate statistic for small samples. Due to these 
issues, there is limited representation for the study’s target 
population, commuter students.  

 
DISCUSSION 
The study examined the correlation between proximity and 
commuter student integration into the campus community. To 
answer the research question, there is no correlation between 
proximity and integration into the campus community among 
commuter students. The data analysis showed no correlation 
between the study’s measures of integration and proximity. 
However, the data did show an overall lack of integration among 
respondents. Most respondents answered that they did not 
participate in any of the activities that were listed in the 
questionnaire. Furthermore, many also said that they did not 
interact with other students in their free time at all. Overall, there 
was support for low levels of participation and interaction among 
the respondents, which researchers should examine in the future. 



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 It is possible that other variables may influence the 
correlation between integration and commuting. As Kirk and 
Lewis (2015) find, time may be an influence that lowers the 
integration of commuter students. The combination of time spent 
on class work, commute time, and other responsibilities reduces 
the amount of time that commuter students spend on campus. 
Spending less time on campus makes it less likely for them to 
engage in behaviors that promote integration and a sense of 
community. Another explanation is a lack of interest in integration 
among commuter students. Kirk and Lewis (2015) also note that 
some commuter students may not be interested in fostering an 
attachment to their educational institution, choosing to spend little 
time participating in events or interacting with others on campus. 

This study contributes to the limited existing literature on 
integration among commuter students. The research explores the 
relationship between integration and commuter status by 
examining if there were differences in integration due to commute 
distance. This focus on proximity also adds to the research on the 
influence of space on the formation of social ties. Based on this 
research, the study applied the distance decay function to a 
student’s proximity to campus, but the results did not support the 
hypothesized relationship. Although proximity was not correlated, 
future research can contribute to the understanding of the 
relationship between commuting and student integration on 
campus. Based on the data, many respondents answered that their 
commute time influenced the amount of time they spent 
interacting with others. Although this study could not add to the 
understanding of this relationship, future research should explore 
the impact of commuting on students.  

Furthermore, despite the research findings, it would be 
worth revisiting this question with a better sampling method. 
Future studies on this topic should use more representative 
sampling methods, such as random sampling. Acquiring a larger 
sample should also be a priority for future research. The low 
number of responses that were collected limited the findings of 
this study. In the cross-tabulations, many of the cells were empty 
due to the low sample size. Researchers may find a different 
relationship among these variables with a larger and more 
representative sample. Overall, it was difficult to examine patterns 



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of behavior with the low number of responses, lowering the 
validity of the study’s findings. Using a different sampling method 
may have resulted in a larger response rate. The sampling frame 
used was narrow, involving only students enrolled in lower-
division classes. A broader sampling frame that includes the whole 
student body may have improved the response rate. Furthermore, 
including other college campuses in the sampling frame could 
have also improved the sample size and representativeness of the 
sample by including a larger and more diverse student body from 
which to collect responses. 

In conclusion, the relationship between commuter status 
and integration on campus still needs further examination. The 
focus on commuter students is significant because much research 
on college students tends to focus on non-commuter students, 
despite commuters being a large portion of the student population. 
A better understanding of integration can lead to a better 
understanding of student retention and success among commuter 
students. The more that is known about integration, the better that 
educational institutions can meet the needs of commuter students. 
As the commuter population increases, it is important that these 
students do not fall behind based on their place of residence or any 
responsibilities that reduce the time they spend on campus.  
 

REFERENCES 
Hipp, R. John, Jonathan Corcoran, Rebecca Wickes, and Tiebei Li. 2014. 

“Examining the Social Porosity of Environmental Features on 
Neighborhood Sociability and Attachment.” PLoS One 9(1):1-15. 
DOI: 10.1371/journal.pone.0084544. 

Kirk, C. Micheal and Rhonda, K. Lewis. 2015. “Sense of Community on an 
Urban, Commuter Campus.” International Journal of Adolescence 
and Youth 20(1):48-60. DOI: 10.1080/02673843.2013.763833. 

Procentese, Fortuna, Flora Gatti, and Annarita Falanga. 2019. “Sense of 
Responsible Togetherness, Sense of Community and Participation: 
Looking at the Relationships in a University Campus.” Human 
Affairs 29:247-63. DOI: 10.1515/humaff-2019-0020. 

Ribera, K. Amy, Angie L. Miller, and Amber D. Dumford. 2017. “Sense of 
Peer Belonging and Institutional Acceptance in the First Year: The 
Role of High Impact Practices.” Journal of College Student 
Development 58(4):545-63. DOI: 10.1353/csd.2017.0042. 

Small, L. Mario and Laura Adler. 2019. “The Role of Space in the Formation 
of Social Ties.” Annual Review of Sociology 45:111-32. DOI: 
10.1146/annurev-soc-073018-022707.  



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APPENDIX  
Table 1: Cross-tabulation for Peer Interaction and Proximity 

 
 
Table 2: Chi-Square Tests for Peer Interaction and Proximity 

 
 
Table 2: Cross-tabulation for Interaction with Staff and Proximity

 



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Table 3: Chi-Square Tests for Interaction with Staff and Proximity 

 
 
Table 4: Cross-tabulation for Participation in Activities and Proximity

 



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Table 5: Chi-Square Test for Participation in Activities and Proximity 

 
 
 
 
Carla Ocampo (She/Her) is a second-year graduate student in the 
Department of Sociology at California State University, Los 
Angeles. Her primary research interests include race and ethnicity, 
immigration, and political attitudes. She is currently working on 
her thesis, researching policy preferences related to climate-
related migration. In 2024, she received the Golden Eagle Paper 
Award from the Sociology Department for “Proximity and Student 
Integration.” The paper examines the relationship between 
commute distance and student integration in the campus 
community at Cal State LA. 
 
 
Featured Award-Winning Paper: We are proud to recognize 
“Proximity and Social Integration” by Carla Ocampo as the 
Award-Winning Paper of the Golden Eagle Sociology Student 
Paper Competition in Spring 2024. This paper was selected by the 
Student Affairs Committee of the Department of Sociology as it 
stood out as the strongest among a pool of excellent submissions. 
Congratulations to Carla for this well-deserved recognition! 

 


	Proximity and Social Integration - Carla Ocampo



