scholarly journals Immigration Arrests and Educational Impacts: Linking ICE Arrests to Declines in Achievement, Attendance, and School Climate and Safety in California

AERA Open ◽  
2021 ◽  
Vol 7 ◽  
pp. 233285842110397
Author(s):  
J. Jacob Kirksey ◽  
Carolyn Sattin-Bajaj
Keyword(s):  
Academic Achievement ◽  
School Climate ◽  
English Learners ◽  
Fixed Effects ◽  
Individualized Education Program ◽  
The United States ◽  
Ordinary Least Squares ◽  
Policy Implications ◽  
Least Squares Regression ◽  
Trump Administration

With increased tensions and political rhetoric surrounding immigration enforcement in the United States, schools are facing greater challenges in ensuring support for their students of immigrant and Latinx origin. This study examined the associations between county-level immigration arrests and academic achievement, absenteeism, and measures of school climate and safety for students in the California CORE districts. Using ordinary least squares regression analyses with year, grade, school, and student fixed effects, we found that immigration arrests corresponded to declines in academic achievement, attendance, and various measures of school climate and safety for Latinx students and Latinx students who were English learners. We also find small declines in measures of school climate and safety for students who ever received special education services via an Individualized Education Program. Associations were strongest for arrests that occurred during the Trump administration compared with those that occurred during the second term of the Obama administration. Policy implications are discussed.

The Influence of Pay-To-Play Fees on Participation in Interscholastic Sports: A School-Level Analysis of Michigan’s Public Schools

2016 ◽  
Vol 13 (12) ◽  
pp. 1317-1324 ◽  
Author(s):  
Jennifer Zdroik ◽  
Philip Veliz
Keyword(s):  
Public Schools ◽  
The United States ◽  
Ordinary Least Squares ◽  
Policy Implications ◽  
School Level ◽  
Bivariate Analysis ◽  
Future Research ◽  
Least Squares Regression ◽  
Participation Rates ◽  
Interscholastic Sports

Background:School districts in the United States are turning toward new sources of revenue to maintain their interscholastic sports programs. One common revenue generating policy is the implementation of participation fees, also known as pay-to-play. One concern of the growing trend of participation fees is how it impacts student participation opportunities. This study looks at how pay-to-play fees are impacting participation opportunities and participation rates in the state of Michigan.Methods:Through merging 3 school-level data sets, Civil Rights Data Collection, the Common Core of Data, and participation information from MHSAA (Michigan High School Athletic Association), bivariate analysis and ordinary least squares regression were used in our analysis.Results:Our findings indicate that certain types of schools are able to support pay-to-play fees: relatively large schools that are located in suburban, white communities, with relatively low poverty rates. We also found that participation fees are not decreasing the number of sport opportunities for students, participation opportunities are higher in schools with fees; but participation rates are similar between schools with and without participation fees.Conclusions:Participation fee policy implications are discussed and we offer suggestions for future research.

Profiles in workplace giving: a cluster analysis of ‘types’ of givers within a public university

2022 ◽  
Author(s):  
Jorge Ruiz-Menjivar ◽  
Tracy Johns ◽  
Tara Counts ◽  
Yong Liu ◽  
Jennifer Amanda Jones
Keyword(s):  
United States ◽  
Cluster Analysis ◽  
The United States ◽  
Ordinary Least Squares ◽  
Public University ◽  
Strategic Marketing ◽  
Public Employees ◽  
Least Squares Regression ◽  
Job Classification ◽  
Employment Duration

This study examines public employees’ donations to a workplace giving campaign at a large public university in the south-east of the United States. First, we employed logistic regression to predict the likelihood of donating through workplace giving programmes using a sample of employees at a large public university (N = 11,726). Second, we estimated an ordinary least squares regression to identify the significant predictors of donation value with a subsample of employee donors (n=1,832). Third, we developed donor profiles (for example, clusters) of employee benefactors using K-medoids clustering. Factors such as sex, age, education and salary were significant predictors of both being a donor and the donation amount. Additionally, employment duration was significantly related to being a donor and the donation amount, while job classification only predicted being a donor. Employee donors fell into five distinct clusters. These findings contribute to our knowledge of workplace giving campaigns and can be used to develop strategic marketing campaigns.

Nonrobustness of the Carryover Effects of Small Classes in Project STAR

2015 ◽  
Vol 117 (3) ◽  
pp. 1-26
Author(s):  
Kitae Sohn
Keyword(s):  
Academic Achievement ◽  
Effective Schools ◽  
Test Scores ◽  
Fixed Effects ◽  
The United States ◽  
Student Characteristics ◽  
Carryover Effects ◽  
Teacher Aides ◽  
Ineffective Schools ◽  
Regular Classes

Background Class size reduction (CSR) is an enduring school reform undertaken in an effort to improve academic achievement and has been widely encouraged in the United States. Supporters of CSR often cite the positive contemporaneous and carryover effects of Project STAR. Much has been discussed regarding the robustness of the contemporaneous effects but not regarding that of the carryover effects. Purpose This article checks the robustness of the carryover effects of STAR's small classes. Setting STAR was undertaken in 75–79 schools in Tennessee. Participants: Each year in the experimental period, 6,000–7,000 students in grades K–3 participated in the experiment, for a total of 12,000 students during the entire period. Intervention As students initially entered STAR schools, they were (arguably) randomly assigned to small classes with 13–17 students, regular classes with 22–25 students without teacher aides, and regular classes with 22–25 students with teacher aides. The experiment was performed from 1985 through 1989, but information on STAR students continued to be collected thereafter. Research Design STAR is a randomized controlled field experiment. Data Analysis In this article, STAR schools are divided into “effective” schools and “ineffective” schools. Effective schools are defined as schools where the test scores of students in small classes were statistically significantly higher than those of students in regular classes at the 5% level in both math and reading. By contrast, ineffective schools are defined as schools where the test scores of students in small classes were not statistically significantly higher than those of students in regular classes at the 5% level in either math or reading. Separately for effective schools, schools other than effective schools, and ineffective schools, the academic achievement of students is regressed on variables indicating small class assignment, along with student characteristics and school-by-entry wave fixed effects. Findings The carryover effects of CSR are not robust; they are driven mostly by effective schools, which account for at most a quarter of STAR schools. During this investigation, it is revealed that, in contrast to the protocol of randomization, observable student characteristics in these schools are not randomly distributed between small and regular classes. They are instead distributed in such a way as to increase the academic achievement of students in small classes and decrease that of students in regular classes. Recommendations Caution is recommended when citing the positive carryover effects of S TAR.

scholarly journals Bikes or Bust? Analyzing the Impact of Bicycle Infrastructure on Business Performance in San Francisco

2019 ◽  
Vol 2673 (12) ◽  
pp. 277-289
Author(s):  
Raleigh McCoy ◽  
Joseph A. Poirier ◽  
Karen Chapple
Keyword(s):  
San Francisco ◽  
Business Performance ◽  
The United States ◽  
Ordinary Least Squares ◽  
Grocery Stores ◽  
Least Squares Regression ◽  
Mode Shift ◽  
Bicycle Infrastructure ◽  
The Impact ◽  
Over Time

Transportation agencies at the local, state, and federal levels in the United States (U.S.) have shown a growing interest in expanding bicycle infrastructure, given its link to mode shift and safety goals. These projects, however, are far from universally accepted. Business owners have been particularly vocal opponents, claiming that bicycle infrastructure will diminish sales or fundamentally change the character of their neighborhoods. Using the case of San Francisco, this research explores the relationship between bicycle infrastructure and business performance in two ways: change in sales over time, and a comparison of sales for new and existing businesses. An ordinary least squares regression is used to model the change in sales over time, isolating the effect of location on bicycle infrastructure while controlling for characteristics of the business, corridor, and surrounding neighborhood. Through a series of t-tests, average sales for businesses that pre-date bicycle infrastructure and for those that opened after the installation of such projects are compared. Ultimately, the research suggests that location on bicycle infrastructure and changes in on-street parking supply generally did not have a significant effect on the change in sales, with a few exceptions. Businesses that sell goods for the home or auto-related goods and services saw a significant decline in sales when located on corridors with bike lanes. New and existing businesses generally had similar sales, though not across the board. New restaurants and grocery stores had significantly higher sales than their existing counterparts, suggesting bicycle infrastructure may attract more upmarket businesses in those industries.

Product diversification, business structure, and firm performance in Taiwanese property and liability insurance sector

2017 ◽  
Vol 18 (5) ◽  
pp. 486-499 ◽  
Author(s):  
Chen-Ying Lee
Keyword(s):  
Firm Performance ◽  
Financial Services ◽  
Fixed Effects ◽  
Ordinary Least Squares ◽  
Product Diversification ◽  
Least Squares Regression ◽  
Fixed Effects Model ◽  
Content Type ◽  
The Impact ◽  
Business Structure

Purpose The purpose of this study is to analyze product diversification, business structure and insurer performance with a comprehensive look at the property-liability (P/L) insurance operations. Design/methodology/approach Using a panel data, this study employs an ordinary least squares regression model, fixed effects model and random effects model to examine the impact of product diversification and business structure on the performance of P/L insurers. The study assesses insurer performance using both risk-adjusted return on assets and risk-adjusted return on equity. Findings The study finds that product diversification is significantly negatively related to the performance of P/L insurers. The results are consistent with the diversification discount theory. The empirical results reveal that business lines have significant impacts on firm performance, particularly on the lines of fire and marine insurances. Furthermore, the interaction between product diversification and firm size implies that product diversification significantly increases the performance of large-sized insurance firms. Originality/value The study provides some valuable insights into the effects of diversification and business structure on the performance of P/L insurers in a developing country. The study’s findings suggest that management of P/L insurers should clarify their objectives and carefully assess the company’s resources when dealing with product diversification and business structure. The results have practical implications for the financial services industry in Taiwan.

The Role of the Perceptions of School Climate and Teacher Victimization by Students

2017 ◽  
Vol 35 (23-24) ◽  
pp. 5526-5551 ◽  
Author(s):  
Francis L. Huang ◽  
Colleen Lloyd Eddy ◽  
Emily Camp
Keyword(s):  
Special Education ◽  
Public Schools ◽  
School Climate ◽  
Fixed Effects ◽  
Administrative Support ◽  
The United States ◽  
School Bullying ◽  
Data Set ◽  
Teacher Victimization ◽  
K 12

Violence directed toward teachers in schools is relatively understudied in comparison with other school-based forms of peer aggression (e.g., school bullying). Based on the nationally representative Schools and Staffing Survey (SASS) 2011-2012, approximately 10% of K-12 public school teachers in the United States, received a threat in the past 12 months and 6% reported being physically attacked. The effects of teacher-directed violence are far reaching and affect not just the victimized teacher, but the larger community itself. In the current study, we used multilevel logistic regression models with state fixed effects to analyze the SASS data set. The analytic sample consisted of 24,070 K-12 teachers in 4,610 public schools and specifically excluded special education teachers and teachers in alternative settings (i.e., online schools, special education centers, juvenile correction facilities). Guided by authoritative school climate theory, we tested for the beneficial associations of disciplinary structure and administrative support with the reduced likelihood of a teacher being threatened or physically attacked by a student, while controlling for teacher (e.g., gender, years of experience, race/ethnicity), school (e.g., school size, percent minority enrollment), and state-level factors. Results indicated that teachers who felt supported by the administration and worked with others (i.e., the principal and other teachers) who enforced the rules consistently were less likely to be victims of threats of injury or physical attacks. Although school climate has been shown to have a positive effect on student outcomes, the current study also suggests that school climate, characterized by consistent rule enforcement and supportive administrators and teachers, may play a role in reducing the likelihood of teacher victimization.

scholarly journals Comparison of Competing Approaches to Analyzing Cross-Classified Data: Random Effects Models, Ordinary Least Squares, or Fixed Effects with Cluster Robust Standard Errors

2021 ◽  
Author(s):  
Young Ri Lee ◽  
James E Pustejovsky
Keyword(s):  
Least Squares ◽  
Random Effects ◽  
Fixed Effects ◽  
Good Alternative ◽  
Ordinary Least Squares ◽  
Alternative Methods ◽  
Least Squares Regression ◽  
Monte Carlo Simulation Study ◽  
Random Effects Models ◽  
Fixed Effects Regression

Cross-classified random effects modeling (CCREM) is a common approach for analyzing cross-classified data in education. However, when the focus of a study is on the regression coefficients at level one rather than on the random effects, ordinary least squares regression with cluster robust variance estimators (OLS-CRVE) or fixed effects regression with CRVE (FE-CRVE) could be appropriate approaches. These alternative methods may be advantageous because they rely on weaker assumptions than what is required by CCREM. We conducted a Monte Carlo Simulation study to compare the performance of CCREM, OLS-CRVE, and FE-CRVE in models with crossed random effects, including conditions where homoscedasticity assumptions and exogeneity assumptions held and conditions where they were violated. We found that CCREM performed the best when its assumptions are all met. However, when homoscedasticity assumptions are violated, OLS-CRVE and FE-CRVE provided similar or better performance than CCREM. FE-CRVE showed the best performance when the exogeneity assumption is violated. Thus, we recommend two-way FE-CRVE as a good alternative to CCREM, particularly if the homoscedasticity or exogeneity assumptions of the CCREM might be in doubt.

scholarly journals Association between local public housing authority policies related to criminal justice system involvement and sexually transmitted infection rates

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Jonathan Purtle ◽  
Erdal Tekin ◽  
Luwam T. Gebrekristos ◽  
Linda Niccolai ◽  
Kim M. Blankenship
Keyword(s):  
Criminal Justice ◽  
Public Housing ◽  
Fixed Effects ◽  
Local Level ◽  
Population Level ◽  
Ordinary Least Squares ◽  
Housing Authority ◽  
Least Squares Regression ◽  
Transmitted Infection ◽  
Sexually Transmitted

AbstractThe policies of U.S. local public housing authorities influence which populations have access to stable housing, an important resource for health. We assessed whether the restrictiveness of local public housing authority policies related to people with criminal justice histories—a population at high risk for HIV/STIs—were associated with HIV/STI rates at the local-level. An ecological analysis was conducted using data from 107 local public housing authority jurisdictions. The independent variable was a score that quantified the presence/absence of eight policies related to the ability of people with criminal justice histories to obtain and retain public housing. The dependent variables were county-level rates of HIV, gonorrhea, syphilis, and chlamydia. Ordinary least squares regression with state fixed effects was used. We find that the restrictiveness of housing authority policies towards people with criminal justice histories were significantly associated with higher HIV and gonorrhea rates, but not syphilis or chlamydia. For example, local housing authorities with a policy score more restrictive than the median score had an additional 6.05 cases of HIV per 100,000 population (32.9% increase relative to the mean rate) and 84.61 cases of newly diagnosed gonorrhea (41.3% increase). Local public housing authority policies related to people with criminal justice histories could affect HIV/STI risk at the population-level. These policies should be considered in studies and interventions at the intersection of housing, health, and justice involved populations.

Legal family, cultural dimensions, and FDI

2019 ◽  
Vol 15 (3) ◽  
pp. 285-314 ◽  
Author(s):  
Tanja Steigner ◽  
Marian K. Riedy ◽  
Antonina Bauman
Keyword(s):  
Fixed Effects ◽  
Cultural Distance ◽  
Common Law ◽  
Ordinary Least Squares ◽  
Cultural Dimensions ◽  
Source Country ◽  
Least Squares Regression ◽  
Legal Origin ◽  
Content Type ◽  
The Impact

Purpose The purpose of this paper is to investigate the interaction between legal origin and cultural distance and its impact on foreign direct investment (FDI) flows into the OECD. Design/methodology/approach Ordinary least squares regression analysis is used to evaluate FDI flows into OECD countries between 2003 and 2012. Estimations use fixed effects and clustered standard errors. Findings FDI flows from civil to common law countries are greater than vice versa. Further, cultural distance impacts FDI flows depending on the legal origin of the source country. Specifically, more FDI flows from civil and common law countries, when the host country has a higher (lower) power distance (individualism) score. Civil law countries send more FDI into countries with higher masculinity, uncertainty avoidance and indulgence scores and with lower long-term orientation scores. The opposite is the case with common law source countries. The findings remain robust for various changes to the sample selection. Research limitations/implications The concepts of cultural distance and legal origin have been criticized. However, neither concept has been rejected; rather, both concepts persist as robust empirical research tools. Practical implications Scholars, managers and investors can gauge the impact of cultural distance on FDI flows based on the legal family of the source country. Further, policy makers might want to consider rebranding their countries in terms of cultural perceptions to show the attractiveness of specific cultural dimensions to foreign companies and investors. Originality/value To the best of the authors’ knowledge, this is the first paper that jointly investigates FDI, legal origin and national culture.

scholarly journals Deciding on Discipline: The Importance of Parent Demeanor in the Transmission of Discipline Practices

2019 ◽  
Vol 8 (3) ◽  
pp. 95
Author(s):  
Jessica L. Burke ◽  
Jessica M. Doucet
Keyword(s):  
South Carolina ◽  
The United States ◽  
Ordinary Least Squares ◽  
Physical Punishment ◽  
Mediation Effect ◽  
Voter Registration ◽  
Future Research ◽  
Least Squares Regression ◽  
Discipline Practices ◽  
Asking Questions

Although child abuse is a social problem in the United States, many cases go unreported because there is not a consensus as to what disciplinary actions are deemed abusive. Thus, it is paramount to understand the demarcation between physical punishment and physical abuse among parents and their use of certain forms of discipline. This study examines how discipline experienced by adolescent respondents affects their choice of discipline practices in adulthood. A random sample of residents was selected from three South Carolina counties using the 2016 state voter registration list. Respondents were mailed a survey asking questions pertaining to their disciplinary practices and experiences. Analyses were conducted using the ordinary least squares regression. Those who experienced abusive discipline as a child were significantly less likely to report that they use the same discipline techniques as their parents. However, adding parenting traits into the model revealed a mediation effect. Abusive discipline no longer plays a significant role in how respondents discipline their own children once the perceived demeanor of their parent is taken into consideration. These findings suggest that disciplinary techniques are less important than a parent’s attitude when correcting their children’s behavior. Implications for the current research, limitations, and directions for future research are discussed.

Sign in / Sign up

Export Citation Format

Share Document