1.
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INTERNSHIP
PORTFOLIO
XIAOYANG
SUN
SPRING
2015
2. 2
TABLE
OF
CONTENTS
Resume……………………………………………………………………………………………………………..3
Organizational
Analysis………………………………………………………………………………………7
Data
Cleaning
and
Appending……………………………….…………………………………………….36
Self
Reflection……………………………………………………………………………………………………43
Writing
Sample………………………………………………………………………………………………….49
List
of
References………………………………………………………………………………………………78
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Xiaoyang Sun
Address: Contact Information:
214 North 10th St. Phone: 310-920-9127
Apt 3A E-mail: tuf15311@temple.edu
Philadelphia, PA, 19107
Professional Objective__________________________________________
To obtain experience in the area of applied social science research aimed at improving
the educational opportunities for minority and underrepresented groups. Particularly
desire to acquire an internship in which I can further develop my knowledge and skills in
qualitative and quantitative methods related to my specialization in Sociology of
Education.
Educational Background________________________________________
M.A. in Sociology (anticipated May 2015)
Ph.D. Sociology (anticipated May 2017)
Department of Sociology
Temple University
Philadelphia, PA 19140
B.A. in Sociology (June 2013)
Department of Sociology
Minzu University of China
Beijing, China 100081
Research and Teaching Experience_______________________________
Quantitative Intern
Research for Action
January 2015 to Present
Cleaning and preparing data with Stata for quantitative analysis; Merging data from
individual dataset; Generating graphs and figures useful in developing sound research
reports; Writing summaries using bullet points to explain the findings of a particular
quantitative analysis.
Graduate Teaching Assistant
Department of Sociology, Temple University, Philadelphia, PA
August 2013 to Present
Assist faculty with course-related responsibilities, including exam preparation and
grading, one-on-one student advising, and work with online course system (Blackboard).
Course I work as a TA for including: Sociology of the Self, Introduction of Sociology,
Ethnicity and Immigrations in the U.S.
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Research Assistant
School of Education, Minzu University of China, Beijing
September 2012 to June 2013
Assisted a visiting UCLA professor with an ethnographic study of faculty life and
organizational change at China’s leading minority university. The study focused on
challenges the university faced in maintaining its mission to serve ethnic minorities.
Responsibilities including assisting in arranging the interview schedule, transcription and
translation, and data coding and analysis.
Field Worker
Minzu University Rural Development Project
February 2011
Conducted fieldwork in a rural region of northern China to evaluate government funded
infrastructure projects relating to community improvements; administered surveys and
interviewed community members and leaders. Served as lead author of the final report
titled, “Research on the Service Condition of Public Infrastructure and Strategic Analysis
in Shangdianzicun Beijing” (awarded “Outstanding Achievement Prize for a Team
Project” by Minzu University).
Field Worker
Minzu University Fei Xiaotong Research Project
Spring & Summer Semesters 2011
Conducted collaborative research at a Beijing nursing home for senior citizens.
Interviewed senior citizens and health care providers about the quality of the nursing
facilities and available resources. Developed a final report titled, “Research of Low-
Income Senior Citizens’ Living Conditions in a Nursing Home” (awarded “Third Prize in
the Fei Xiaotong Minzu University School of Ethnology and Sociology Student Research
Competition”)
Volunteer Experience___________________________________________
Volunteer Teacher, Beijing Elementary School for Immigrant Workers’ Children
July 2010 to June 2011
Provide lessons on moral and civic education to the children of Beijing immigrants from
the country-side on a weekly basis.
Volunteer Teacher, Minzu University Rural Development Project
Winter Break 2011
Taught children in grades 1 through 6 the basics of creative expression through painting.
Research Papers and Presentations_______________________________
Rhoads, Robert A., and Xiaoyang Sun. (2014, April). “Ethnic Diversity in China and the
Role of Minzu University: Analyzing Organizational Narratives of Change.” Paper
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presented at the Annual Meeting of the American Educational Research Association
(AERA), Philadelphia.
Sun, Xiaoyang. (2014). “Income Inequality/Disparity among First-Generation
Immigrants in the U.S Labor Market: Examining the Effect of Country of Origin with
2012 American Community Survey Data.” Unpublished paper.
Academic Awards and Honors___________________________________
▪ Graduate Teaching Assistantship from the Department of Sociology, Temple University
(August 2013 to present)
▪ Certificate of Completion in Advanced Academic Intensive English Program, UCLA
Extension (Summer 2012)
▪ “Outstanding Academic Performance Scholarship,” Minzu Department of Sociology
(2009-10)
▪ “Academic Excellence Scholarship Award” from the Hong Kong Xin Shan Foundation
(based on grades for the academic year 2010-11)
▪ “Third Place Award in the Fei Xiaotong Research Project” from the Minzu University
School of Ethnology and Sociology (June 2011)
▪ “Outstanding Achievement Prize for a Team Project” by Minzu University (February
2011)
▪ “Third Place Award” (among all Beijing university students) from the National English
Contest for College Students (NECCS) (July 2010)
▪ “Excellent Speaker Award” from Minzu University English Speech Contest (July 2011)
▪ “Outstanding Volunteer Award,” Minzu Department of Sociology (2010-11)
Language and Technical Skills___________________________________
▪ Fluent in Chinese Mandarin and English (TOEFL score of 106)
▪ Skilled with SPSS, STATA, Word, Excel, PowerPoint
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Professional Affiliations & Conferences___________________________
▪ Attended the 2014 Annual Meeting of the American Educational Research Association
(AERA), Philadelphia, Pennsylvania.
▪ Attended the 2014 Annual Meeting of the Association for the Study of Higher
Education (ASHE), Washington D.C.
References____________________________________________________
Available upon request.
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Organizational
Analysis
of
Research
for
Action
1. Clients and Customers
Research for Action (RFA) is a non-profit research organization that does applied
research to help address educational inequality and improve teaching quality and thus
better students’ outcomes in the very disadvantage and segregated neighborhoods and
communities. RFA also does evaluation projects for schools, districts, educational
organizations and communities, providing research-based advice for educational policy
making locally and national wide. The projects are typically longer-term research, during
which multiple publications are produced. Normally publications are individual
documents – research reports or evaluation studies – that typically fall under a project.
With in mind the kind of research RFA does, it is not hard to imagine the potential clients
and customers they have. RFA accepts funding from both individual clients and
organizational clients. Some of their funders are American Association of University
Women, Bread Loaf Rural Teachers’ Network, New York City Mathematics Project, The
Social Impact of the Arts Project (SIAP) (UPenn), City University of New York, and
Educating Children for Parenting (now Educating Communities for Parenting) etc. The
above examples of RFA’s founders reveal the needs and interests of their customers and
clients. The founders of RFA are mainly educational agencies and institutions that
concern themselves with the educational opportunities of women, children, the wellbeing
of rural teachers etc. They also devote to research on the external factors that may have
impacts on people’s educational outcomes such as extracurricular math tutoring, artistic
and sports activities.
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A larger portion of RFA’s work is supported by the Philadelphia institutions such
as The Philadelphia Foundation, and Philadelphia Education Fund etc., therefore the
research and studies RFA generate are also mainly within the Philadelphia area. The
economically deprived neighborhoods and communities (mainly in the northern part of
Philadelphia) are all aware of the fact that educational institutions, such as some of the
clients of RFA, devote time and money into researching educational inequality and racial
segregation in the very disadvantaged areas in Philadelphia. And those educational
institutions also invest a lot of money on providing all kinds of programs that aim at
improving academic performance and enriching the out-school lives of the kids in those
neighborhoods. At the same time, those educational institutions also found research
organizations such as RFA to do evaluation research on the efficiency of these special
programs. Thus local people in the poor neighborhoods have very high expectations of
the clients of RFA, they have the assumption that the effort these local institutions put has
the potential to alleviate unequal opportunity and access to educational resource and to
help more lower class kids to realize upward mobility through education, and the
communities in the areas of Philadelphia encourage their kids to attend these programs
with great enthusiasm.
The relationship between RFA and its clients are mutual. The educational
institutions that are eager to act on the inequality in education in Philadelphia trust the
ability of RFA to conduct thorough and rigorous research in order to provide information
and feedbacks of their programs and projects helping the poor. At the same time, RFA is
also able to trust the will and determination of their clients and founders that they would
only want to conduct just and unbiased research and implement effective and fair
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programs. I did a small interview with one research associate at RFA about what they
expect from their clients and founders, he told me that before they take the case and
accept the funding, they will have to make sure the study their clients want them to do
does not contain any politically extreme elements or would mislead the public on certain
sensitive issues. RFA also makes sure that what their founders want to publish based on
the research does not violate the interest of the vulnerable population such as the poor
and people of color, and RFA promises the research will protect the privacy of the
respondents. Thus RFA ceases serving their clients when RFA believes what their clients
ask for is not in line with the value of RFA which is to address educational inequality and
help the vulnerable population.
2. Community
Although Research for Action (RFA) has built its reputation through the nation in
terms of doing rigorous educational studies and evaluation, it is a Philadelphia-based
research institution which means most of its main projects and research revolves around
the areas of Philadelphia. Philadelphia is the 5th
largest city in the United States and has
about 1,553,165 people by 2014, it was the first capital city of the nation, and it was
ranked number 4 in the list of “You must go to” places in the world in 2014. Having all
the nice thing people say about Philadelphia in mind, we must admit Philadelphia as a
major city with large urban areas has its own problems that must be addressed in order to
accomplish sustainable growth and development, including one of the country’s highest
poverty rates, high crime rates, a declining real estate market and an unemployment rate
above the nation’s average etc. And there are many other issues that come with high
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poverty rates, limited educational resources and unequal educational opportunities is one
of them, and this is what RFA intends to address and help with.
Due to the terrible economic conditions of Philadelphia, there are many low-
income communities, especially in the northern part of Philadelphia. In those poor
communities where the schools are under-funded have been failing minorities and
contributing to social reproduction and cycles of high school dropouts, drug addiction,
crime, etc. One recently published book by Alice Goffman titled On the Run: Fugitive
Life in an American City gives us a good glimpse of the poor situation in these
neighborhoods. This ethnographic study is done in one of the poorest racially segregated
neighborhood in Philadelphia, it gives rich and in-depth description of how desperate the
young black males in this neighborhood is. Due to the deep rooted structural and
institutional racist that permeates our society, it is hard for those young black males to
enter the mainstream world and benefit from public institutions such as schools, hospitals
etc. And it seems like that the only way to make a living is to break rules and violate the
laws by selling drugs etc. Thus very few of the young black males can stay completely
free from jail or poison which makes them live fugitive lives.
And it is in this kind of community context--further damaged by withdraws of
federal support for schools and social programs under neoliberal economic regimes--that
RFA seeks to operate and have an impact. RFA intend to alleviate the terrible situation in
these communities by conducting educational research that fully explores the
complexities of educational inequality in Philadelphia, interpreting research for multiple
audiences, and also providing recommendations on education reform for educational
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“policy organizations and foundations, communities and school districts, and city- and
state-level policymakers”1
.
The work RFA does has profound meanings to the residents in those communities
because they stick to the goal of “better helping their clients and their community
understand the current state of knowledge on key issues”. And a lot of people in the poor
communities have very high expectation and hope towards RFA’s work in addressing and
alleviating educational inequality as their work is straightforward and friendly to all
public reader with a variety of educational levels. According to one of the research
associates at RFA, a lot of residents, schools and companies etc. in the areas of
Philadelphia are very cooperative when collecting data as part of their own effort to help
alleviate inequality together with RFA. And in these processes, RFA has been getting
more and more support and founding from both personal and institutional levels and
continuing to “draw national attention as an organization that exemplifies the value of
being a locally-focused, applied research organization”.
3. Careers
Given the nature of Research for Action (RFA) is a research organization that
concerns their research effort to addressing inequality and other issues in the field of
education, most of RFA’s staff are professionals who have academic background in
social science and educational study. In order to give an even clearer glimpse of what
RFA’s staff composition is, I browsed through most of their staff’s bios on their website.
1
http://www.researchforaction.org/menu/about-us/
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Based on what I have observed, many of RFA’s staff is trained in universities in the area
of Philadelphia such as Temple University, University of Pennsylvania, Drexel
University, and there is also some staff from Colombia University, University of Georgia,
and Florida State University etc. The kind of degree RFA’s staff hold ranges from
Bachelor’s degree in Sociology to M.S. in public policy and finally to Ph.D. in Urban
Education etc. Therefore we can say that RFA’s staff composition is quite diverse.
In terms of career path and choice of RFA’s staff, I found the short conversation I
had with my adviser at RFA who is the project director of 21 Century convincing. I asked
him why he did not want to become a professor working at a good university, he briefly
told me why he chose his current career path at RFA instead of being a faculty and
teaching at universities and colleges. My adviser Jina Gao is originally from China and
he came to the United States to pursue his Ph.D. in Foundations of Education at Florida
State University. He was an excellent student at school and especially good at
quantitative research skills due to his statistical background in economics, thus he was
chosen to work for the local government where his university was in Florida, even when
he was still finishing up his doctoral study. And from then on he was set on the track of
working as a researcher for governmental office and research institutions. Therefore his
suggestion for is that, once I decide what to choose between working for research
institutions and teaching at universities, it is not easy to switch because these two tracks
could be quite different in many ways. For example, the style and quality of publications
is very different at research institutions whose goal is to write and present the research
results in a concise and straightforward way so it could be open to public audiences.
Whereas for faculties at universities, it is more important to generate new theories, find
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new areas to explore and publish articles in very good journals in the field. Thus the
nature of the first permanent job to a great extent decides the lifelong career path. I found
that conversation very enlightening since what I am doing now at RFA is a great
opportunity for me to find out which one of these two tracks appeals to me more, so I can
make better career choice in the future.
Due to the nature of social science, the methodological training needed in RFA is
qualitative method, quantitative method and also mixed method. And RFA has gained
profound recognition in their methodological strengths. They provide methodological
training to every new staff, even to their interns, based on their preference. With
qualitative training, RFA lays emphasis on the careful analysis of interviews, documents
and other format of qualitative data; with quantitative training, RFA not only provides
numerous opportunities for their staff to get hands-on experience with real data, ranging
from basic data cleaning and synthesizing to advanced quantitative analysis, RFA also
teaches their new staff how to design quantitative studies and carry out the study with
efficiency by both traditional paper-pencil based questionnaires and internet based
surveys. Normally, RFA “begins every project by identifying the most pressing research
questions, and employing the methodological approach that will yield the most robust
and useful results”.
The field RFA’s in is called “applied research and policy making” and people
with skills in such areas can work in other industries besides educational research centers.
For example, public health research, public policy research, governmental offices that do
policy research, foundations such as the Pew Foundation (in Philadelphia) do policy
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research. Education is not the only field that intersects with RFA, but public policy and
applied research is the bigger field.
4. Safety
Organizational risk can contain a wide array of risks, including budgetary risk,
investment risk, program management risk, safety risk, inventory risk, legal liability risk
and the risk from information systems etc. What the major and crucial risks are for
organizations, to a great extent, depends on the nature of the organization and the way the
organization is structured. With the case of Research for Action (RFA), because it is a
non-profit research organization, the biggest risk faced by RFA is its funding structure,
given that the organization largely operates on the basis of grant money (soft money) and
does not have a huge source of steady and predictable income. Although the Executive
Director, Kathleen Shaw who is a former Temple University professor has been very
successful at raising revenue for RFA, especially in light if its significant contributions to
improving education, she still must depend on wealthy donors and grant opportunities.
Should such revenue decrease significantly over the course of time, then RFA could
become quite vulnerable.
Other risks faced by RFA relate to competitions for research funding and
opportunities. And such competitions could come from research centers at the nearby
universities and colleges such as University of Pennsylvania, Temple University or
Drexel University, or in terms of national projects from universities and research centers
around the country. Other than the formal educational institutions, RFA also needs to
compete for funding, clients and customers against non-profit research agencies and
organizations that provide similar service and conduct similar kind of social science
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research. Such organizations come to mind are Equal Measure (OMG Center for
Collaborative Learning which also provide research-based evaluation and philanthropic
services), Research for Better Schools (RBS which is “a private nonprofit educational
R&D firm also located in Philadelphia”) etc. 2
With the fierce competition from other
similar research organizations in mind, there is also potential risk of topic researchers at
RFA being recruited elsewhere in those research organizations mentioned above;
therefore RFA will also need to work on building a staff-friendly corporate culture that
ensures staff loyalty.
And then there are also risks for RFA including researchers and field workers
working in the context of applied settings such as schools and the potentials for mistakes
or ethical lapses to occur. As we all know, it is very important for researchers to keep in
mind their goal of conducting just research and sticking to ethical principles when doing
research. I can recall seeing a truck running through the city of Philadelphia last semester
carrying a big sign with eye-catching notes on it: tell Temple University to stick to higher
ethical standard. After doing little search online, I found it was about “an ethics
investigation by Temple University into two of its professors and their research in favor
of – and funded by – the private prison industry”. 3
In this case, the two professors were
charged of not sticking to the disclosure standards for working papers and opinion and
the publication of their final work spurred some public attention to this issue. Thus RFA
as a research organization also faces the risk of being charged with these accusations if
they don’t pay attention to the ethical principles when carrying out research of their own.
2
http://www.rbs.org/About-RBS/History/289/
3
https://www.insidehighered.com/news/2014/06/11/temple-‐u-‐professors-‐
accused-‐not-‐
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Last but not least, there is also the risk of danger for RFA’s researchers working
in the field, especially in high-crime or run-down areas in the city of Philadelphia or other
urban areas where often times schools face the biggest challenges.
5. Power
Power is a crucial component within any social organization. Where there is
hierarchy, there is power structure and power stratification. Therefore I would think about
the power within Research for Action (RFA) in two ways--internal power dynamics
among actors within RFA and then also RFA as an organizational player in a broader
context. Issues of power at RFA may be considered in terms of the internal organizational
structure and any hierarchy that may exist as well as the overall role and influence of
RFA as a player in the larger educational research and policy making arena.
In terms of internal power relations, one might consider the nature of the
employees and volunteers comprising the organizations staffing. For example, the most
powerful actor at RFA is the Executive Director, Kathleen Shaw. She also has a high
standing beyond RFA given that her work has recognized by the Association for the
Study of Higher Education (ASHE) in terms of giving her the first ever "Excellence in
Public Policy in Higher Education" award in November 2013. This award recognized
Shaw as an individual who contributes excellent work at the nexus of academic
scholarship and policy practice in the field of public policy and higher education. Her
status no doubt brings greater power and influence to the overall organization with the
broader policy arena.
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What is more, in terms of the internal dynamics of power, there are many other
roles and working arrangements that must be analyzed. Within the job structure at RFA,
there are four levels of jobs: administrators, research associates, data analysts and interns,
from higher positions to lower ones in the hierarchy of power. The administrators at
higher level are in charge of keeping RFA running by raising funding, attracting
customers, clients, and promoting RFA in the market. Once staff at administration level
succeeds in bringing in money and projects, the next level research associates would be
in charge of designing the research, building research agenda, generating different levels
of task for people at lower levels to do. Then the next level of data analysts would be the
people doing the real physical working of carrying out the research, including collecting
data, entering data, cleaning datasets for statistical analysis, and doing some basic level of
data analysis. Then on the bottom of the power structure within RFA would be interns
like me. The interns normally are undergraduate or graduate students from universities in
Philadelphia. Most of the times, interns work for free at RFA without getting paid, but
RFA does provide 10 dollars traffic stipend if interns manage to work 10 hours per week.
Although interns have some discretion in terms of their work schedule at RFA (RFA
really is relaxed and flexible in terms of the working schedule for interns, as long as the
interns can fulfil 10 hours a week, it does not matter on what days the interns have to
work at RFA), they have no control over what projects they would be working on. The
research associates and data analysts would supervise the interns and tell them what to do
which further will determines what kind of training the interns get. Because the interns
are at the bottom of the power stratification, they may not always get the exact kind of
training and working experience they intended to gain.
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In terms of RFA’s relationships with other organizations, including the city of
Philadelphia, the State of Pennsylvania, and other entities, its power and influence is
largely tied to its success in doing meaningful policy-oriented research. When the
organization is successful, its power expands and its ability to generate grants and
additional funding increases. This further strengthens the cycle of power. But on the other
hand, when the organization fails to achieve its research goals for a variety of complex
reasons, its overall power and influence within local community, the state, and the whole
nation may suffer.
6. Identity and Diversity
Identity and diversity are crucial dimensions when looking at organizations in
society. Society is comprised of mass of heterogeneous individuals therefore people are
sorted along the line of gender, race, class, and sexual orientation etc. At Research for
Action (RFA), I clearly observed how gender, race and sexual orientation shapes the
organization and its relationship to its staff, clients, funding base and even to the larger
community.
Examining the research RFA does, I don’t think sexual orientation play much of a
role in shaping RFA’s research agenda and policy impact. However, the organization is
guided primarily by concerns linked to gender, race/ethnicity and social class relative to
educational equity. Nearly all the research RFA does address these issues. For example,
RFA’s current work in Rutgers University’s RU STEPped Up for Success Initiative
program is concerned with the evaluation of an NSF-funded program aimed at increasing
recruitment and retention of underrepresented minorities and women in college STEM
majors. The evaluation of this project has great potential in implicating policy making
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processes and promoting the opportunities for women and minorities to purse college
majors and careers in the STEM field. Currently, a big chunk of RFA’s effort is devoted
to the 21st Century Community Learning Centers which is the project on am working on
as an intern there. 21st
Century Community Learning Center is a project that is funded
through a federal grant to create OST activities in six school districts and communities in
the areas of Philadelphia, and all these six school districts and communities have very
high poverty rate and manly comprised of African American residents. And what RFA
researchers do is to conduct a mixed-methods evaluation of each of these six school
districts and communities to determine the impact of program activities on students’
educational outcomes. Therefor the research results shed light on how governmental
grants and community efforts to provide out-school-tutoring will improve the teaching
quality of some of the very poor and racially segregated neighborhoods.
The way RFA’s research agenda and policy impact are shaped by gender,
race/ethnicity and social class could also be revealed by its founders and customers.
Browsing through the founders’ and clients of RFA, I saw institutions and organizations
such as College Access Foundation, New York City Mathematics Project, Lehman
College, City University of New York, Ms. Foundation for Women and Congreso de
Latinos Unidos all of which indicate their concerns related to gender, race/ethnicity, and
social class. Thus based on examining the kind of research RFA does and the customer
and founding source, I argue RFA’s research agenda and policy impact are clearly shaped
by gender, race/ethnicity and social class.
One could also look at the internal dynamics of RFA and see how identities such
as gender, sexuality, race/ethnicity etc. shape the organizational structure within it. I
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argue RFA seems to be an empowering space for women, especially given that the
Executive Director Kate Shaw is a woman. And by examining the staff directory, I found
that out 25 of RFA’s full time employees, 16 of them are women. Thus RFA is a place
where women have great chance to purse professional careers and a place where women
get autonomous and independence. Race and ethnicity are also active in the internal
dynamics of RFA. Among the same 25 staff of RFA, 2 of them are African American,
and among those two African American employees, the African American woman works
in a key position as the director of finance. Also as I know, 1 of the 25 employees is
originally from China, one originally from India. Given sexuality is not the kind of
identity a lot people are open about, nor is it something once can visually identify, so it is
not easy to argue sexuality plays an important role at RFA. However, I do know as a fact
that the office assistance (the main secretary) is gay and he is apparently comfortable
coming out at RFA. Because the office assistance is one of the people who interviewed
me in the beginning, so we had some casual conversation where he openly talked about
his partner and their plane of adopting a child. Therefore I would assume RFA is also
highly supportive of LBGT people, again given the progressive/liberal orientation of
RFA's leadership.
7. History, mission, values, goals
Research for Action (RFA) is a non-profit research organization in Philadelphia,
center city. Founded in 1992, RFA works with public school districts, postsecondary
institutions, and educational and community organizations to improve the educational
opportunities for those traditionally disadvantaged students. Engaged mainly in
educational research, program evaluation, and strategic advice etc., RFA aims at applying
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academic research to promoting equal educational opportunities and increasing
educational quality in the areas of Philadelphia as well as throughout the nation. RFA has
achieved its aim and goal by doing quantitative, qualitative and mixed method research
and presenting these research results in a straightforward manner that is reader friendly to
public audiences.
The organizational mission and goal of RFA is to use research as the basis for the
improvement of educational opportunities and outcomes for traditionally underserved
students. Their work is designed to strengthen public schools and postsecondary
institutions; provide research-based recommendations to policymakers, practitioners and
the public at the local, state and national levels; and enriches the civic and community
dialogue about public education. Take the project I am currently working on at RFA for
example. The 21st
century project is an evaluation project on 12 community learning
center providers in the area of Philadelphia. 21st
Century community learning center
program is founded by the U.S. Department of Education and its goal is to provide
extracurricular tutoring and activities and enrich student’s school life to students in high
poverty communities. So what we do here is basically collecting questionnaires and
attendance records of students from the 12 providers, and then collecting academic
performance records from the schools those students attend. Finally, we compare the
students’ academic performance at school before and after they attend the community
learning center tutoring and other activities. With our report on the student outcomes after
attending community learning centers, we give overall evaluations of the program in
terms of its efficiency in improving students’ academic performance at school. At the
same time, we also report problems and issues that stood out in the process of
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implementation of the program and provide corresponding suggestions and advice to the
local level staff and institutions, as well as to the federal level institutions. By doing
research and generating evaluation reports like this, RFA helps improving the school life
and learning experience of disadvantaged students in high poverty neighborhoods and
communities thus fulfilling its mission and achieving its goal.
RFA has applied its value of addressing educational inequality and promoting
educational quality to all of their work over the years since it was founded. Education is
becoming an increasingly important mean of realizing upward social mobility in modern
world. Acquiring basic knowledge of the world as well as gaining professional skills, to a
great extent, determines where one will land in the social strata today. Therefore it is
urgent and significant to be aware of the fact that a large portion of school age population
in our society is still living in poverty and does not have equal opportunities to pursue
education. Sociology of education is where my own research interest lies, making the
intern experience at RFA a perfect fit in terms of developing my own research interest
and skills. The overarching value of addressing and alleviating educational inequality
throughout all RFA’s work corresponds to mine own and inspires me from the beginning
of my academic life. It is also the reason why I stick to my academic life—doing
something in the real world, knowing what I do will actually make changes in people’s
life, and hopefully make the world a better place for all of us.
8. Bureaucracy
Bureaucracy is an important concept in sociology, especially when it comes to the
sociological study in the field of organization and politics. Many significant sociology
figures have discussed about this concept, including Karl Marx, Max Weber and Peter
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Blau. In the discussion of Weber, bureaucracy is an efficient mechanical system that
operates mainly based on the principle of rationalization. In modern times, bureaucracy is
the administrative system governing any formal institution and organization.
Research for Action (RFA) as a non-profit research organization constitutes its
own bureaucracy. The bureaucracy within RFA helps the running and maintenance of the
organization with administrative, research-related, customer funding-related polices and
rules.
Rules and policies regarding the administrative system suggest the power
distribution within RFA. I would argue staffs on the administrative level have more
power, so to speak, in terms of grasping the general direction of RFA. Especially the
executive director Kate Shaw, she is in the highest position in the organization where she
could convoke meetings with people on the administrative level to solicit opinions and
feedbacks on the current administrative rules and policies thus they can make adjustments
and improvement. The administrative rules and policies make it clear to all the people
within the bureaucracy what their roles and responsibilities are thus assured the
functioning of the whole organization.
Rules and policies regarding research and searchers help clarify the principles on
research related ethics including how to do research and how to treat their respondents
when conducting research. For example, in the research-related policies at RFA require
their research associates and data analysts to stick to the principles of confidentiality
which means they would not give away the information or data they collected during
work to anyone for any purposes.
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People can find these rules and policies in the personnel brochure, or you can talk
to the human resource manager and the main secretary at RFA regarding any specific
policies and rules that are not covered in the personnel brochure. Because I am either a
full time employee or a paid intern, I don’t have to sign any formal legal contract with
RFA. Therefore I had to do a little interview with the human resource manager to find out
where I could find the information. And the human resource manager, in the
conversation, told me that once new staff (either a full time employee or a paid intern)
signs the contract with RFA, they will provide the new staff with several hiring material,
including the personnel brochure that contains clear rules and policies of the
organization. And most of the time, people can find very detailed information the history,
mission, staff directory, clients and founder etc. of the organization on RFA’s website.
Unfortunately, RFA does not have its rules and policies online, as the human resource
manager told me, that information is more of internal documents they share with their
staff. And the administrative level staffs such as human resource manager, main
secretary, and the executive director are the key to the implementation of administrative,
research-related, customer funding-related polices and rules that I have discussed above.
Staffs at administrative level will hold meetings on regular basis to discuss the problems
and issues that stand out and make sure the people in the corresponding position will take
care of them on time so the implementation of the rules and policies will be assured and
supervised.
9. Laws and ethics
Research for Action (RFA) mainly depends on establishing and maintaining high
levels of public trust given that their funding and support mostly comes through grants
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and foundations. This means they must pay great attention to tightly following all
relevant legal and ethical considerations. Especially as a research organization whose
product is very much likely to influence public opinions and add to public knowledge,
RFA needs to be very cautious with lawful and ethical issues within their process of
conducting research to assure the objectivity and fairness of their final research findings.
Legally speaking, RFA is a non-profit organization thus they must be careful not
to take partisan positions lest they lose their standing as a non-profit organization. But
because they are also advocates for education and for addressing educational inequality,
they must walk a fine line in terms of the political positions they adopt with regard to
supporting more equitable schools, well avoiding any appearance of
partisanship. Therefore, this requires RFA to see a ethical balance here so they will not
take extreme partisan positions with any side but, at the meantime, are able to speak for
the disadvantage and marginalized population such as people of color, lower class people
and sexual minorities. One important way to avoid ethical issues within the organization
that comes to mind is that RFA should always keep transparent and clear record of their
funding budge. So if anyone doubts on the objectivity and unbiasedness of their research
results based on the source of money that founds the study, they would have everything
on record and have nothing to hide from the public.
Another aspect to look at the issue in terms of ethics in the field is that RFA must
be very careful in conducting the research they do in schools, universities and lower class
neighborhoods, given that most human subjects in those settings are very likely to be
vulnerable population in our society, for example, school children are under 18 years of
age and hence many research projects must include parental approval. Thus RFA has to
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stick to the ASA Code of Ethics in mind all the time when they go about collecting data
from human subjects in order to protect these vulnerable people from getting hurt and
being exploited. And this way of avoiding ethical issues probably means building close
ties to families and communities in which they conduct their research.
Furthermore, RFA benefits from its many research grants and projects and thus
has an ethical responsibility to fully give back to the communities and school districts in
which they conduct their work. It is very important and necessary to think about what
they can do in return for their respondents who participated in the research project and
contributed to RFA’s work. For example, maybe RFA can, by their publication, bring
public attention to the very school district that is in great needs for money, investment
and social support; maybe RFA can foster the public awareness of the severity of
educational inequality in urban areas to promote and solicit policy reforms from the level
of local, state and federal government.
Based on what I have argued above, in order to ensure that RFA field workers and
researchers engage in ethical practices, the organization should always pay close attention
to the essential ethical obligations of researchers to avoid missteps that would induce
ethical issues. Therefore training new employees at RFA should is always a crucial
process through which ethical considerations would be stressed and emphasized.
10. Money
Nonprofit organizations (NPOs), from a legal perspective, are organizations that
use their revenues to better and further accomplish its organizational missions or goals
that embody their ultimate value instead of distributing its revenues to any benefit seeker
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within or out of the organization. In a common sense perspective, nonprofit organizations
(NPOs) are organizations that do not see making profit as the main organization goal.
They are instead more concerned with, most of the times, addressing social inequality
and solving social problems. And due to the nature of nonprofit organizations (NPOs),
people sometimes are very likely to associate nonprofit organizations with charitable
organizations. Although they are two types of organizations, there are some organizations
that are both charitable and nonprofit at the same time, such as Lucile Packard
Foundation for Children's Health in Palo Alto, California, Alexander City Kiwanis
Foundation in Alex City, Alabama, and Vietnam Veterans Workshop New England
Shelter for Homeless Veterans in Boston, Massachusetts etc.
Therefore Research for Action (RFA) as a non-profit organization, it first of all,
meet some of the state’s educational institutions evaluation requirements and thus gets
some funding from state and local governments. Federal, state, and local government
grants fund many programs provided by nonprofits, especially in areas such as urban
human service, higher education and public education etc. As far as I know, the 21st
century project is one of the projects that are founded by the federal government. Other
than getting grant money from governments, RFA also dependents on research grants and
foundation’s philanthropic support to get money. And those research grants and
foundations could be both corporate and individual, but most of them are philanthropic in
nature. Such founders of RFA , for example, includes William Penn Foundation which is
a charitable foundation that is “dedicated to improving the quality of life through efforts
that close the achievement gap for low-income children, ensure a sustainable
environment, foster creativity that enhances civic life, and advance philanthropy in the
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Philadelphia region”. 4
And the money source and the nature of founders definitely have
significant power in shaping the mission and purpose of the organization. The kind of
research RFA does reflects the main concern and focus of their clients and founder. The
research of RFA will have to address the issues such as income inequality their founders
like William Penn Foundation would care.
RFA as a nonprofit research organization also gets money and funding from self-
generated fees for research related services they provide. For example, for a lot of
evaluation project RFA does, they get income for doing that kind of work for their
clients. In another word, their clients who come up with certain programs and projects
would buy service from RFA to evaluate the implementation and efficiency of their
programs and projects. Last but not least, RFA also benefits from volunteer assistance
(such as unpaid interns like me) which is in essence a form of income source in that labor
is a cost. RFA every year would need about 5 to 8 interns, depending on the workload of
the specific year. Normally the interns from universities in Philadelphia don’t get paid
doing intern work at RFA. However, the interns do get involved with the actual projects
RFA work on and will do the literal work that contribute to the real projects. Therefore I
would argue getting unpaid interns every year also counts as one source of income.
Again, I suggest you ask for a copy of the budget or at least get some info. However, I
have to say that the above arguments are merely based on summarizing RFA’s present
research grants listed on their website which is available to public. For more detailed
4
http://www.researchforaction.org/
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income source, I probably have to result to budget information of RFA which is not
available to everyone.
11. Web and social media presence
In the era of internet, social media have become an increasingly popular and
important way for organizations and institutions to promote themselves. Through social
media such as Google, YouTube, LinkedIn, Facebook, Twitter etc., organizations build
their public image and convey their organizational missions and goals by posting pictures
related to some of their activities or texts that report what has been going on in with them;
they also utilize social media as a way to promote their influence and attract potential
customers and clients by posting significant work and project online to make them
available to public.
With Research for Action (RFA), they have their own website
http://www.researchforaction.org/. This is RFA’s official website where they introduce
themselves to public by describing who they are, what they do, what their strength are,
who their customers and founders are, and what they have published in their field etc.
The official website of RFA is a straightforward and user friendly one compared with a
lot other official website of other organizations. It is first of all, visually unique with
RFA’s pinwheel logo on the upper left corner of the webpage, and then the whole
webpage is comprised of dark blue, dark orange and light orange which are also the main
color tone of RFA’s business card. From this point of view, RFA has done a good job in
building their image on social media by creating this unique visual representation of their
website and their business card. Second, the webpage has a place where you can put the
key word and search the specific topic related to the key word, then anything on their
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webpage that contains that key word would come out automatically. This is a very user
friendly design that could save the users the trouble of going through massive
information on webpage and immediately direct people to the things they need. What’s
more, RFA has also put their Tag Cloud on the right side of the webpage. With the Tag
Cloud, users can easily identify what are the most frequently used words in their recent
work, what they are most concerned with in their recent projects, and what are the aspects
their recent work revolves around. Again, this is a place where internet users could get a
basic sense of the nature of RFA, and it is also a place where potential customers or
clients could easily identify whether RFA is a good match to their purpose. Another very
useful feather of RFA’s webpage is that they have a button called “Donate” by which one
can click and donate any amount of money to RFA. I think that is a practical function the
webpage given the way RFA functions financially.
I argue the main goals on social media for RFA is to call attention to their work in
disadvantaged communities, especially in terms of strengthening K-12 education for low-
income populations. And I also think that their goals on social media should be to
promote the organization in manner that can be used to encourage funders to support the
organization--given that RFA is a non-profit and depends on such support. That way they
would have more resource to do meaningful research that helps the disadvantaged
students in lower class neighborhoods.
One way I have in mind in terms of improving their web and social media
presence they should offer more talks and presentations related to their findings--so that
regular people and scholars as well will become familiar with the public policy role RFA
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plays. Their goals are really worthwhile and their research and findings should be shared
more widely.
12. Performance
A good way to evaluate an organization’s performance is to assess whether the
organizational goals and missions are successfully fulfilled or not. As a non-profit
research organization engaged mainly in educational research, program evaluation, and
strategic advice etc., Research for Action’s (RFA) mission is to use research as the basis
for the improvement of educational opportunities and outcomes for traditionally
underserved students. Their work is designed to strengthen public schools and
postsecondary institutions; provide research-based recommendations to policymakers,
practitioners and the public at the local, state and national levels; and enriches the civic
and community dialogue about public education.
Therefore based on their mission, RFA’s performance can be assessed by its
ability to acquire grant and funding support, as well as its efforts to produce policy
oriented research findings. On one hand, from the founder/client information I can collect
from RFA’s website, it is clear RFA has been getting continuous funding from clients
and founders who provides RFA the ability to fulfill and deliver their mission. Thus from
this regard, RFA as a non-profit research organization has been performing efficiently in
terms of striving for grant and funding which is the premise of delivering its ultimate
organization mission and goal—doing research to influence the real world. On the other
hand, RFA has also been doing a good job in generating research based findings and
recommendations to influence the public policy making process. For example, in 21st
Century Project, RFA’s researchers produce evaluation report that examines the
efficiency and outcomes of the project through rigorous research. Based on the research
results, RFA also indicates the strengths and challenges of OST (out school tutoring)
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programs in Philadelphia, and provides corresponding recommendations and suggestions
for program providers at local scale as well as OST System at city wide scale. And a lot
of the recommendations aiming at strengthening individual programs and improving the
capacity of the City’s OST system are extremely practical which, to a great extent,
guarantees the implementations of these recommendations in the real world thus assures
the delivering of RFA’s mission.
Another key area for assessing RFA’s performance is more difficult to accurately
gauge, and that involves evaluating their actual impact on the kinds of educational
policies and practices they hope to impact. This means actually examining the schools
and educational institutions they work with to determine if changes related to
improvement and increased equity have taken place or not. For the purpose of the
organizational analysis memos in this class, I have limited resource and access to literally
go to these places to collect data, however, it is still ultimately the best way to assess the
organization’s performance.
As to improving RFA’s performance, I would, first of all, suggest RFA extend
their publicity by taking advantage of the internet era and building a health and positive
public image on multiple social media sites such as LinkedIn, Facebook, Twitter, and
YouTube etc. so that they can attract more founders and clients to bring more financial
guarantee for their ability to continue their research. At the meanwhile, it could also help
RFA broadly and further distribute their research findings and the recommendations
based on the research results to draw public attention and thus increase efficiency in
delivering these recommendations in reality. Last but not least, I would suggest RFA
build more partnerships with educational institutions or other research organizations like
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themselves so they can collaborate on more significant transformative tasks and projects;
in this way RFA and its partners together can have more meaningful discussions of
educational policies and problems and how to impact them.
37.
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Site:
Research
for
Action
Date: 03/17/2015
Having dealt with raw data about 8 weeks at RFA, I intend to test my ability of
dealing with data by taking on a data cleaning and appending task independently.
Although the task might not sound too exciting, I still find it challenging and important.
My daily routine at RFA normally starts with my supervisor assigning a task from his
project, and he will tell me what to do and how he wants the task to be done. If I have any
other questions in the process, I would go to my supervisor for further help anytime.
Therefore, at my intern at RFA, I always get detailed guidance and instruction from
people on how to write certain command and how to deal with the unexpected situation
when running command. This time with this independent task, I want to get a project that
is similar to what I normally do at RFA but use the task as a test to see if I can complete
the data cleaning process from the beginning to end all on my own without asking any
question and seeking any help. Although logging raw data and cleansing dataset seem to
be a tedious job, it is still the very crucial part of quantitative study because it constitutes
the premise of accurate statistical analysis. Without accurate and precise data, no matter
how complicated the statistical procedures are, the quantitative results could be
misleading and even meaningless. What is more, my main purpose of doing internship at
RFA is to get plenty hands on experience on dealing with massive data and preparing
data, including logging, cleansing, and synthesize dataset so that I can become adept
taking care of data within Stata, thus this challenge task is a perfect way to evaluate my
goal at RFA.
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As I have stated above, I intend to challenge myself with the task of logging raw
data from Excel into Stata, cleansing and preparing the data ready for further statistical
analysis. Unlike what I usually do, I would not ask for any help from anyone when
completing this task and will deal with any unexpected situation with data cleansing on
my own. The project with which I will challenge myself is Elev8. Basically, Elev8 is a
community schools efforts in four sites across the country – Baltimore, Chicago, New
Mexico and Oakland initiated by The Atlantic Philanthropies (Atlantic). Elev8 mainly
aims at improving students outcomes by providing OST (out-school-time) programs in
disadvantage neighborhoods and communities. The evaluation work RFA does is by
analyzing the data from the community schools that participated in the Elev8 program.
These local schools will provide raw data in Excel files.
In order to take on this challenge, I talked to my supervisor first, explained my
intention of challenging myself, and asked him if he has any projects he works on that
need some data cleaning job. He told me he could use some help with Elev8 project
which needs someone to log the data from Excel and then clean it up within Stata. The
Elev8 sounds exactly perfect for my purpose, so we had a short discussion of the task
where he first showed me what the raw data looked like. Within the Excel file, it has
several variables we need for analysis. However, the variable that matter to us the most is
the year variable. Because we have data from both before the implementation of Elev8
program and after Elev8 program. With year variable, we can compare the school
performance and students’ outcomes before and after the implementation of Elev8
program to generate compelling evidence illustrating the efficiency of the program.
However, the year variable in the Excel file is not an independent variable, so transposing
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year variable is needed. And after the transposing year variable, he needed me to clean
the data in Stata, including getting rid of invalid variables, removing duplicated entries,
cleaning all the leading and tailing space in the data etc. And then he assured me that I
could do it on my own because I have done all these tasks in my days at RFA with the
help and guidance of him and his assistant. So I had my notebook ready with which I
wrote down the steps doing data cleaning from the past experience at RFA, and I took a
good look at the raw data in Excel. I also went back to the syntax file that I have cleaned
data with before, the commands all got freshened up in my mind again. Thus, after
having a discussion of the task with my supervisor and freshening up my memories of the
commands and steps of doing data cleaning, I knew I was ready to do this and challenge
myself.
My task actually went really well which is I did not expect. When I got the raw
data from my supervisor, I first cut out all the information that is not useful according to
the need of my supervisor. As I have figured out myself through cleaning data at RFA, it
is always a good idea to first cut out the variables in Excel instead of write a drop
command in Stata. Then I also cut the table name on the first row in Excel because Stata
automatically recognizes the first row of Excel sheet as variable names. So when I cut the
table name, all the variable names will be on the first row which will be recognized by
Stata. Then I had to do a transpose action in Excel by copying the table that contains all
the variables I need and transpose it when pasting. This way, Excel flip the row and
column so the all the data will vary by year. This is the last step of preparing data in
Excel. Next step, I need to log the data in Excel into Stata. I first opened a new syntax
window in Stata, and put my name and the project name on top within the asterisk box on
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the very top of the syntax. Then I wrote command “cd*****” which tells Stata from
where I want to find and open the raw data. I then did the import command by writing
“import excel "transpose excel.xlsx", firstrow sheet ("Alburquerque") clear” which
signifies the name of Excel file and which sheet within that Excel file I want to use. After
this command, the data was logged into Stata and I could open the data editor window to
visually analyze the data and decide what to do with it next. In data editor window, I
spotted leading and tailing space scattered within the Attendance Rate variable, so I
decided to do a trim command which will help me get rid of the spaces. By writing
“replace Varname=trim(Varname )”, I successfully cleaned the space within ** variable.
Next, in order to make all the variables numerical for the purpose of analysis, I did a
destring command by writing “destring Varname, replace force” which transform all the
string values in the *** variable into numerical; and by adding force to the end, Stata will
forcefully turn all the other format of variables into missing value. And after I did some
basic rename commands that rename the variables based on what I was told, I did a save
command which saves the cleaned data into the same folder as the “cd” command
indicates. I then basically did the same thing with the rest of data from Oakland,
Baltimore, and Chicago and saved them independently. The last step was to combine all
the data from these 4 cities into a one complete dataset that has the same variables in
them. So I first opened the data from Alburquerque as the main dataset, and then did the
append command by writing “append using "dataset name" ” 3 times, and finally the data
from all the other 3 cities were appended to the main dataset. In the end, I just saved the
synthesized data with a new name under the folder I found convenient. In order to check
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the outcome of the data cleaning and synthesizing, I open the merged data in Stata, and
all the variables came out just as I wanted so the task turned out to be very successful.
This task turned out to be successful in the end which makes me pleased with my
days at RFA. And after I sent the final cleaned dataset to my supervisor, he was very
satisfied with my work and even asked the HR manager to send me an email, inviting me
to their summer internship program. From this challenge task experience, I learned many
things that, I think, will benefit me throughout my career. The most important lesson I
learned is that people should always be confident and not be scared to challenge
themselves with things they are uncertain about. I didn’t even think of taking on such a
task that require me to perform on data cleaning on my own until this challenge exercise
in the syllabus. I get so used to the everyday routine at RFA where I get orders to do
certain things and get help when there are issues and problems that I it never cross my
mind that I should take on a task initiatively and try to do it all by myself. I was
subconsciously intimidated to do a task on my own at RFA because I only had very
limited training on Stata and quantitative method, so I was scared to make mistakes and
disappoint people at RFA who hired me as an intern. However, after I literally took the
first step out and pushed myself to do this on my own, I realized it is not as hard as I
thought it would be despite of some fears and difficulties I experienced when doing it.
Then I came to the conclusion that the best way to acquire a skill is through doing it on
your own, only in that way can you test yourself to see if you have the ability to perform
with that skill independently. And only when you are able to accomplish the task
completely on your own can you say that you successfully master the skill. However, I
also gained some precious experience technically with using Stata. The first thing is that I
42. 42
realized, similar to SPSS, one can use the drop-down menu in Stata to do certain
command. People all say how intuitive Stata commands are, I almost forget Stata also has
drop-down menu that works the same way as the command. One short cut to learn a new
command could be through using the drop-down menu first, and then Stata will
automatically write the corresponding commands in the window box. So I can remember
and learn from this command and next time when I have to use that again, I should have
it in my mind that I can just write the command myself. Another small shortcut I learned
from this challenge task is that when cleaning data, sometimes it is faster and more
continent to do some cleaning with raw data in Excel. For example, it is always a good
idea to get rid of the empty rows or columns within the data in Excel so when you log
data in Stata it looks a lot more tidy and organized. And the action of transposing data
can only be accomplished in Excel. Thus the useful experience I learned through this
challenge excise is that Excel could be quite useful when cleaning data in collaboration
with Stata.
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Self-Reflection of Internship at Research for Action
Xiaoyang Sun 04/20/2015
1. Experience at the Site (RFA)
Doing the internship at Research for Action (RFA) is something I never thought I
would do because I always lack confidence in my quantitative knowledge and skill.
However, I pushed myself to do so through the Independent Study in the doctoral
program and realized how rewarding such an experience could be. The most exciting
thing happened when I first started at RFA is when I learned that my supervisor Jian Gao
is originally from China and his assistant MB who also supervises me from time to time
is an alumni of our department. The reason why this fact matters to me is that I used to
get intimidated from asking questions or helps from my teacher and supervisor by the
relationship between supervisors and supervisees, teachers and students; given the fact
that in Chinese culture, teachers and supervisors are greatly respected with high authority,
and students are encouraged to always have a serious relationship in a respectful way
with their teachers, instead of a casual and friend like one. Therefore I never have called
my teachers or supervisors by their first name. There should always be titles such as
Professor or Doctor before their last name. Due to that, I often times get too nervous and
uncomfortable to make myself clear in terms of explaining my questions and issues. I
dread having conversations with my professors. However, at RFA, the fact that my
supervisor is originally from China makes me feel much more relaxed because I know if
there is something complicated, I can explain better in Mandarin, thus there will be less
miscommunication or misunderstanding. And out of habit, I always call my supervisor
Dr. Gao or Professor Gao given the environment and atmosphere at RFA is quite
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academic just like universities. But my supervisor told me many times I can call him Jian
instead of professor Gao since he doesn’t teach. And with his assistant M who graduated
from Temple not so long ago, I also feel less nervous when asking questions and having
conversations with him. Because our common experience at Temple, it is easier to relate
to each other like peers and colleagues.
Having a more relaxed and colleagueial relationship with people enables me to
ask more important questions and have more useful conversations at RFA, thus I learned
many new knowledge and skills quickly. Before I started at RFA, I also turned to
Lyda.com (which is an online course program provided by Temple) and took the course
on Excel where I learned many skills and shortcuts to improve my efficiently working
with Excel. At one time, my advisor asked me to generate some graphs with Excel in
order to show some trends of the data. I recall the online Excel course arguing trend line
is a proper way to show trend, so I generated trend line with the data he gave me, and he
was very pleased with my work. When reporting what I did with the data by generating
trend lines, I asked him what the nature was of trend lines in Excel. Is it based on the
average of actual data? Or is it a line based on the standard deviation of actual data? I did
some research online first to found out the nature of trend line but could not find any
result. Then my advisor told me that the trend line in Excel, in essence, is a linear
regression, thus the line is a predicated value based on actual data. And because Excel
does not provide p values like SPSS and STATA, people normally don’t use it for
advanced statistically analysis. Instead, people more often use it as a straightforward
mean to do descriptive analysis. He was very pleased with my efficiency and accuracy of
46. 46
my work, and complimented me on my curiosity to ask questions and learn new
knowledge.
Through such experience and conversations at RFA, I found myself making huge
progress in many aspects. I, first of all, gained great confidence in my capacity to do
quantitative work. I used to doubt myself on doing quantitative study because statistics
and math are never my strength, however, when I force myself to do so I realized that I
not only are able to do that, I also am able to do it well. Another precious experience at
RFA is that I get more exposure to American culture in a formal social setting and
realized the cultural differences between the U.S. and China, so I learned to be more
flexible in instructing my action at workplace in the U.S. with schemas and frames in the
American cultural tool kit. I gradually built a more relaxing relationship with my
coworkers at RFA and treat them as equal colleagues who I can have conversation and
discussion with, and then I feel less uncomfortable asking questions. Only in that way can
I learn and progress faster as faster at RFA.
2. Professional Inspiration from the Internship
My main purpose of interning at RFA is to get hands on experience with
massive data and become adept working with STATA, and eventually develop the
ability to deal with data as if it is a second nature. Although someone can argue data
cleaning is a tedious and repetitive job, I still seems crucial and important to me. First
of all, I think accurate data is the very premise of any meaningful quantitative study.
Without accurate dataset, the quantitative results could be misleading and even
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invalid. What is more, we as graduate students only have limited exposure to the
experience of dealing with real data in class. However, a good way to master a skill is
through continuous practice; and become adept by running into all kinds of problems
and incidents when practicing. Thus during interning at RFA, I had a lot opportunities
dealing with real data and became pretty adept at logging data, cleansing and
synthesizing data. At the meanwhile, I also became more efficient with Excel and
explored a lot of very useful functions within Excel that I didn’t know before. And all
these skills add great advantage to me when hunting jobs in the job market given how
everything is computerized nowadays thus most professional jobs require these skills.
The massive contacts with STATA at RFA enables me to apply into practice the
theories I was taught in school and examine the applicability of different statistical
procedures we learned in class to real data. The combination of theory and practice
greatly improved my understanding and capacity in quantitative study which benefits
me a lot when seeking for a professional job in the field of applied social science
research due to the fact that quantitative method is more of a dominant practice.
The intern experience at RFA inspired me in many ways in terms of how I
look at research and the field. It made me more determined to do applied research
because I see how being able to go out collecting data, analyze data and interpret the
data results, in this case, could influence police making and thus educational reform
that address educational inequality and ameliorate that. By doing applied research,
people are literally able to do things that make meaningful changes in the real world
which deepens my appreciation of doing research, and at same time, further sparkles
my interest in this field. I hope to contribute to this field by working as a professional
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in the future and thus this intern experience at RFA definitely adds to my advantage
in that regard.
3. Overall Self-Evaluation
Near the end of the intern, I realized I have become more confident of myself
since I started at RFA. I also have come to better understand the atmosphere of
professional workplace in the U.S. context by becoming more flexible when dealing with
cultural difference. I have been enlightened by other interns at RFA who are graduate or
undergraduate students from Temple or University of Pennsylvania. I admire their
courage of willing to take the challenging tasks such as interning at RFA which is
something I need to learn from them. And I am extremely impressed by MB
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Income Inequality among First-Generation Immigrants in the U.S Labor Market:
Examining the Effect of Region of Origin
Xiaoyang Sun
Abstract
Objective. This study explores the effect of region of origin on U.S. immigrants’
economic outcomes. It does so by examining income disparity in the U.S. labor market
among first generation immigrants, sorting out the effects of the immigration process
from the effects of immigrants’ characteristics and from the responses of the host society
(Evans 1984:1086) by controlling for length of residence, English proficiency and
educational Attainment. Method. Data for first generation immigrants aged from 25 to 64
who are still active in the labor market was obtained from 2012 ACS (American
Community Survey) 5 years sample. OLS Linear regression procedures were used to test
the correlation between income disparity and region of origin with educational
attainment, English proficiency, and length of residence as control variables. Conclusion.
There are annual income disparity existing among first generation immigrants of different
region of origin and this disparity is statistically significant. However, as has indicated by
the data, the effect of region of origin on annual income becomes weaker after controlling
for sex, English proficiency, length of residence, and educational attainment.
Introduction
The United States is often described as a country of immigrants and this idea
remains true even in the contemporary context (Slack and Jensen 2007: 1415). The flock
of immigrants from all over the world not only helps sustain the U.S population at a level
where it can reproduce the population itself, it also supports the U.S economy with
abundant personnel for the labor force. “Beyond population size, the most notable impact
of immigration has been the broadening of the social and cultural diversity of the
American population” (Hirschman 2005: 595). However, despite the great contribution
immigrants make to the U.S society, problems still exist in that “literature on
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international migration contends that immigrants often experience considerable hardships
when entering the labor market of a new country” (Raigman and Semyonov 1997: 108).
A further issue revealed by some of the research on immigration has shown
differences in annual income relative to region of origin. Thus, an analysis of immigrants
coming to the United States and the difficult adjustments they face should also consider
the effect of region of origin on annual income. Immigrants are an ethnically diverse
group and this diversity is analytically useful because it allows us to “separate the
consequences of immigration per se from consequences of characteristics of immigrants,
notably language, culture, and the possession of modern work skills” (Evans 1984:1065).
For example, on the one hand some immigrants such as Asians or Africans come from
countries where the language and culture are very distinctive from that of the United
States. On the other hand, some immigrants such as Europeans or Australians are from
countries that are rather close to the United States in terms of language and culture, as
well as other social aspects. Therefore, it is critical to examine the work experience, with
annual income as a main indicator in this paper, of immigrants from different regions to
better understand the overall adjustment and challenges they face as part of the
immigration process.
This paper seeks to examine key economic hardships faced by first-generation
immigrants (foreign born) particularly in terms of whether they experience relatively low
annual income within the U.S. labor market. Specifically, I address the following
research questions: 1) Is there income disparity among first-generation immigrants
related to their region of origin? 2) If there is income disparity, what is the extent of such
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disparity? And, 3) After controlling for English proficiency, educational attainment, and
length of residence, are there still annual income differences related to region of origin?
Existing Research
The existing research literature pertaining to income disparity among immigrants
and related to region of origin is quite limited. This is especially true when it comes to
studies of the U.S. context that employ contemporary data. Perhaps the closest study to
what I am proposing was conducted by Evans (1984), titled, “Immigrant Women in
Australia: Resources, Family, and Work.” This study utilized a 1 percent public use
sample from the 1981 Australian Census to study the working experience of immigrant
women in Australia in terms of four indicators: their labor force involvement,
occupational niche, entrepreneurship, and income. Although this research is somewhat
dated, it nonetheless offers a framework for me to follow in examining the contemporary
U.S. context. Thus, my research study follows a similar line of inquiry as Evans but
extends that work in two significant ways. Frist, this paper will use 2012 American
Community Survey (ACS) 5-year sample to study the income disparity in the
contemporary U.S. context. Second, this paper will also look at immigrant men to see if
there are gender differences in annual income among immigrant groups. In what follows,
I organize my review of the literature into three sub-sections: economic hardship
immigrants experience in the U.S. labor market, differences in economic outcomes
related to region of origin, and demographic factors and labor outcomes.
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Economic Hardship Immigrants Experience in the U.S. Labor Market
Raigman and Semyonov (1997) have indicated that “immigrants often experience
considerable hardships when entering the labor market of a new country” (109). This
widely noticed and highly debated phenomenon has attracted a good number of
researchers to conduct studies pertaining to economic hardships generally experienced by
immigrants. For example, many researchers are interested in the income disparity in labor
markets among foreign born immigrants and native born non-Hispanic whites. Li (2000),
using micro data of 1996 Canadian census, found that “all immigrant groups in Canada
earned less than their native-born counterparts. The magnitude of net earning disparities
between immigrants and native-born Canadians varies, depending on gender, racial origin
and less so on CMA level” (290).
Madamba and De Jong (1997) studied job mismatch as an indicator of poor
economic performance among Asians in the U.S. Their study looked at six subgroups of
Asian workers: Chinese, Indian, Japanese, Vietnamese, Filipinos, and Korean. The results
reveal that “Asian immigrant workers were more likely to experience job mismatch than
the native born. In 1990, recent male immigrants in four of the six Asian groups had
greater job mismatch than did native born worker” (539). Based on the preceding study,
De Jong and Madamba (2001) further examine the economic performance of immigrants
by classifying underemployment into four types: unemployed, part-time employed,
working-poor, and job mismatch. After comparing these four types of underemployment
for immigrants and native born populations, they indicate that overall, “immigrant
underemployment was greater than that of native born” (117). The working-poverty rates
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and unemployment rates were higher among blacks and Hispanics but when it came to
job mismatch, it was highest among Asians.
Furthermore, in a study examining labor market outcomes of immigrants across
European destinations, Adsera and Chiswick (2007) argue that there are great earning
disadvantages for immigrants when compared to native born populations. With the 1994-
2000 waves of ECHP (the European Community Household Panel) survey data, they
reported that, “overall, immigrants in Western Europe earn around 40% less at arrival
than the native born in that destination with the earning differential greater for those born
outside the EU than for immigrants born in other EU countries” (519). Hence, their study
offers further evidence of the labor-market challenges many immigrant groups face.
Gender may also be a factor in immigrant income inequality. With a specific
focus on the labor market outcomes of immigrant women, Schoeni (1998) compares
immigrant women with native born women in the U.S. between 1970 and 1990. The
results show that while only a slight difference in labor market outcomes was found in
the 1970s, this difference grew significantly over time. “Relative to natives, immigrant
women’s participation rate and weekly earnings (among working women) became lower,
and their unemployment rates became higher and by 1990, the wage gap was 14 percent”
(74). Along the same line, Boyd (1984) also argues in his study that “immigrant women
are observed to have occupational statuses which are lower on the average than those of
other sex and nativity groups… (1091)”. Similar findings are provided by Raigman and
Semyonov (1997) in their study of immigrant women in Israel. They used data from the
1983 census of population conducted by Israel’s Central Bureau of Statistics to examine
the “double disadvantage hypothesis”: this hypothesis basically posits that the labor
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market environment for immigrant women is likely to be extremely harsh compared with
native born men due to the joint effect of gender and immigration. Through the study
they came to the conclusion that “both immigrant men and women, regardless of
ethnicity, experienced declines in labor force participation and suffered occupational
loss” (120). However, the data suggest an even worse labor force participation decline for
immigrant women in the transition of moving to a new country.
There are also studies that look at native born children of immigrants (2nd
generation immigrants) as well. In a study conducted by Takei, Sakamoto, and Kim
(2013) they divide second generation Southeast Asian Americans (SEAA) into six
subgroups comprised of Cambodian, Filipino, Hmong, Laotian, Thai, and Vietnamese.
They find through the study that the earnings of these six groups are less than their white
counterparts even after controlling for age, educational attainment, English proficiency,
marital status, veteran status, disability status, metropolitan residence, and region of
residence. These results indicate that, “The SEAA groups generally appear to be
disadvantaged relative to white men” (211). Chiswick’s (1983) study also compares the
earnings and employment of American-born Chinese, Japanese, and Filipino men with
American-born white men. The findings reveal that when key mediating variables are
held constant, Chinese and white men show similar earnings and employment, with
Japanese men earning 4 percent lower weekly wages. However, “Filipino men…have
substantially lower levels of schooling, employment, and earnings” (211). Although this
study shows some improvement in terms of earnings and employment for native born
Chinese and Japanese men, the negative outcomes for Filipino men reveal that significant
differences may exist among the Asian American population.
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Differences in Economic Outcomes Related to Region of Origin
Sakamoto, Goyette and Kim (2009) note in their study that, “Immigrants are
heterogeneous, reflecting the wide array of their countries of origin as well as varying
degrees of selectivity involved in their immigration circumstances” (259); thus, it is not
hard to see that immigrant as a social status constitutes many subgroups with each
subgroup facing different circumstances and potential hardships. Among all immigrants,
Raigman and Semyonov (1997) presented the “triple disadvantage hypothesis”
contending that female immigrants from less developed countries are more likely to be
unemployed in the labor market in Israel due to the joint effect of gender, country of
origin, and immigrant status. De Jong and Madamba (2001) found similar results
supporting a double disadvantage hypothesis, asserting that immigrants are challenged by
their immigrant status as well as their minority status, when compared with native born
minorities, respectively.
Immigrants in the U.S constitute culturally and ethnically diverse populations of
people coming from all over the world. Along these lines, studies have shown that the
immigration laws and policies could be “explicitly biased against particular nationalities”
(Ewing 2012: 1). This form of “favoritism” in U.S. immigration history dates back to the
1880s when anti-Chinese legislation was passed, although in the 1950s efforts were
undertaken to erase such forms of discrimination. For example, the Immigration and
Nationality Act of 1952 was a one such attempt but it was far from perfect: “Although it
eliminated race as a basis of exclusion from the United States, it retained the racist bias of
the national-origins quota system” (Ewing 2012: 5). Similar evidence of the
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discriminatory treatment on a national-origins basis is also highlighted by Foner (2013) in
a study that gives specific examples of exclusion policies and laws that “barred the entry
of Asians—in the case of the Chinese, as early as 1882” (Foner 2013: 18). Limitations
against Asian immigration is also noted by Massey et al (1998) when they noted that
during the 1960s Asians were blocked from entry into the U.S., and “racist immigration
laws that explicitly favored northern and western Europeans” were practiced (64). The
studies discussed above by Ewing, Foner, and Massey et al are helpful in terms of
providing evidence of the discriminatory practices historically speaking; however,
empirical studies using more recent data are necessary in order to examine whether such
practices still exist in contemporary U.S. society.
As noted previously, a study conducted by Evans (1984) examined the work
experiences of immigrant women in Australia in terms of four primary indicators: labor
force involvement, occupational niche, entrepreneurship, and income. This study
indicates that overall, immigrants from North America and Western Europe often times
do better than immigrant women from Third World countries in terms of landing better
jobs and gaining occupational prestige. Specifically, after adjusting for educational
attainment and other demographic characteristics, the effect of region of origin on income
difference decreases significantly for Mediterranean women; this suggests that the effect
of region of origin is actually spurious. Based on the empirical results, Evans came to the
conclusion that “the Australian labor market appears to be nearly blind to ethnicity, and
the labor market treats everybody about equally” (p. 1086).
But other empirical studies reveal a region of origin effect. For example, Boyd’s
(1984) empirical study focusing on immigrants in Canada highlighted unequal treatment
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among immigrants of different countries of origin. She specifically noted that the
disadvantage of being foreign born varies based on birthplace of immigrant women in
Canada, and that “the analysis indicates that the double negative of being female and
foreign born is less of a factor for the occupational attainment of women born in the
United States and in the United Kingdom, than it is for women born in Europe and
elsewhere” (p. 1091). Also, a study done by Adsera and Chiswick (1999) reported a
similar effect with country of origin impacting labor market outcomes among immigrants
in Europe. They noted in their study that immigrants who are not EU born suffer
economically in the labor market compared to their counterparts who are EU born. There
was an exception to their findings, pointing out that, “the earnings of English Americans
are not significantly different from those born in the EU” (p. 518). Another research
study conducted by Schoeni (1998) also noted the economic outcomes among immigrant
women based on their country of origin, highlighting that “immigrants born in the United
Kingdom and Canada, Europe, Japan, Korea, China, the Philippines, and the Middle East
have had steady or improved wages and unemployment relative to U.S.-born women. At
the same time, immigrants from Mexico and Central America have experienced relatively
high unemployment and low earnings” (57).
Demographic Factors and Labor Outcomes
Demographic factors in analyses of immigration often times consider such
attributes of immigrants such as educational level, age, or the skill level of a particular
immigrant population often compared to members of the same country who decide not to
emigrate. For example, some studies have examined the degree to which a particular
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group of immigrants possesses more advanced labor skills in some cases “measured by
the share of professionals among entering immigrants” (Lobo and Salvo 1998: 738).
One stream of research relating to demographics and immigration focuses on the
effects of educational attainment and the degree to which immigration decisions are
informed by a belief that a host country offers a greater return on educational investment.
Chen (1995), in a study of Taiwanese immigrants in the U.S., argued that “emigrants are
self-selected from more able persons because they are willing to sacrifice their current
benefits and family ties and are therefore very strongly motivated to pursue economic
improvement in a foreign country” (251). A key finding of Chen’s that Taiwanese
immigrants with higher levels of educational attainment emigrated to the U.S. on the
basis that they believed the U.S. labor market offered greater returns to schooling (260).
Other scholars also have examined immigration decisions in light of perceptions of
greater returns to education. Cobb-Clark (1993) added gender as a variable to the
immigrant self-selection equation analyzing the experiences of women immigrants to the
U.S. She found that, like men, women self-selected to immigrate to the U.S. under
conditions in which the GDP is high but the returns to education are low and tended to do
better in the U.S. labor market.
Although it is not the intent of this paper to examine policy and its impact on
decisions to immigrate or not, it is worth noting that scholars have identified links
between immigration policy and whether certain immigrant populations became more or
less select based on professional qualifications. An example of this type of analysis is
offered by Lobo and Salvo (1998) in their treatment of Asian immigrants to the U.S.
They examined Immigration and Naturalization Service (INS) data for the period 1972 to
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1994 with a particular interest in how changes in immigration policy resulted in more or
less selective populations of Asian immigrants in terms of professional credentials. They
primarily focused on three periods reflective of changes in U.S. immigration policy: 1)
1972-1977, 2) 1978-1991, 3) 1992-1994. One particular period of interest followed the
Immigration Act of 1990, “which allowed for a substantial increase in the entry of those
with professional qualifications” (739). Lobo and Salvo’s results show that the period
from 1978-1991 saw a decrease in professional credentials among Asian immigrants, and
then an increase during 1992 to 1994. As they explained: “With the Immigration Act of
1990, there was once again an upswing in the occupational selectivity of immigrants. The
share of professionals among Asian immigrants increased to 33 percent” (748-49) and
this corresponded with a decrease in Asian immigrants identified as “operators,
fabricators, and laborers” (749). One explanation for this shift was the fact that the 1990
Immigration Act included an expanded allotment of employment preferences.
Conceptual Map
Reflected in the conceptual map below, I expect to see that region of origin and
annual income are correlated and are statistically significant; in other words, I
hypothesize that there are statistically significant differences in the mean annual income
among immigrants based on their different regions of origin. Basically, English
proficiency, length of residence, and educational attainment are the main factors that to
some extent determine the annual income of certain groups of immigrants. As is
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generally assumed, many English speaking countries (e.g., Australia, Canada, the United
Kingdom, etc.) tend to be among the most advanced countries in terms of economic
development factors. Immigrants to the United States from such countries are more likely
to exhibit higher English proficiency levels and have higher levels of educational
attainment. Consequently, they are more likely to land some of the better jobs that offer
higher annual incomes. Therefore, I hypothesize that after controlling for these two very
important variables (English proficiency and educational attainment), the effect of region
of origin on annual income should decline or even disappear.
Gender
English Proficiency
Length of Immigration
Educational Attainment
Region of Origin Annual Income
Much research has noted that length of residence also plays a very important role
in determining annual income among immigrants; in this sense, it is believed that with
the accumulation of social and human capital over the years after becoming a new
immigration, they gradually catch up with native-born Americans in terms of annual
income. Thus, I hypothesize that after controlling for length of residence, the effect of
region of origin on annual income disparity among immigrants may further decline.
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Data and Method
The data for this paper are from the 2012 ACS 5 year sample. Using OLS
regression, with controls for gender, educational attainment, English proficiency, and
length of residence, the emphasis is on measuring the effect of region of origin on income
disparity among first generation immigrants.
The dependent variable INCWAGE_LOG is a continuous variable transformed by
getting the log of INCWAGE in order to make the dependent variable more normally
distributed so it does not violate the normality assumption in OLS regression. The
original INCWAGE (income wage) variable reports each respondent’s total pre-tax wage
and salary, which is their income received as an employee. The amounts are expressed in
contemporary U.S. dollars. I selected INCWAGE as the original dependent variable
instead of total personal income because the wage and income salary received as an
employee is a better indicator to examine the labor market performance of first-
generation immigrants.
The main independent variable in the study BPLGROUPS is a categorical
variable recoded by collapsing the original BPL (birthplace) variable in the ACS data that
indicates the U.S. state, the outlying U.S. area or territory, or the foreign country where
the person was born. I collapsed all of the foreign birthplaces into 10 groups: North
America, South America, Europe, East Asia, Southeast Asia, Middle East, Other Asia,
Africa, Australia and New Zealand, and Others and will compare income disparity among
immigrants based on these 10 regions of origin.
Control variables include the following: EDUC (educational attainment) as a
continuous variable indicates respondents’ educational attainment, as measured by the
