The Concept of Academic Mobility: Normative and Methodological Considerations

2019 ◽  
Vol 57 (4) ◽  
pp. 1625-1664
Author(s):  
Rafael Quintana ◽  
Richard Correnti
Keyword(s):  
Educational Inequality ◽  
Achievement Gaps ◽  
Data Set ◽  
Academic Mobility ◽  
Representative Data ◽  
Nationally Representative ◽  
Socially Relevant ◽  
Methodological Considerations

Most of the literature on the development of educational inequality has operated under the achievement gaps paradigm, often assuming that the underlying normative and methodological foundations related to equality and justice in education are a settled matter. In this article, we argue that important normative dimensions are overlooked with traditional mean-based measures, and that metrics that capture students’ academic mobility as they progress through school can provide the informational base needed to describe and evaluate these policy and socially relevant aspects. We discuss some key normative principles and methodological dimensions related to academic mobility and provide an empirical example of the mobility metrics presented using a nationally representative data set.

IT Outsourcing and Firm Characteristics

2014 ◽  
Vol 10 (1) ◽  
pp. 1-18
Author(s):  
Ludivine Martin ◽  
Nicolas Poussing
Keyword(s):  
Information Technology ◽  
Statistical Approach ◽  
It Outsourcing ◽  
Firm Characteristics ◽  
Data Set ◽  
Unit Level ◽  
Representative Data ◽  
Nationally Representative

This paper seeks to identify the characteristics of firms that choose to transfer all or at least part of the fulfilment of their information technology needs to an outside party. The authors focus both on outsourcing and on offshoring. With a statistical approach, based on a large and nationally representative data set at the firm unit level, the authors look at the profiles of firms that have decided to outsource and/or offshore at least part of their ICT activities. The authors show that the firms with the most specific ICT needs choose to acquire these services from external suppliers or firms located abroad. The firms with the highest level of ICT investment are also the firms that choose to resort to outsourcing to a great extent.

Early Predictors of ASD in Young Children Using a Nationally Representative Data Set

2013 ◽  
Vol 35 (4) ◽  
pp. 303-331 ◽  
Author(s):  
Laurie M. Jeans ◽  
Rosa Milagros Santos ◽  
Daniel J. Laxman ◽  
Brent A. McBride ◽  
W. Justin Dyer
Keyword(s):  
Young Children ◽  
Data Set ◽  
Representative Data ◽  
Early Predictors ◽  
Nationally Representative

scholarly journals Gender and Minority Achievement Gaps in Science in Eighth Grade: Item Analyses of Nationally Representative Data

2017 ◽  
Vol 2017 (1) ◽  
pp. 1-19 ◽  
Author(s):  
Xiaoyu Qian ◽  
Ratna Nandakumar ◽  
Joseph Glutting ◽  
Danielle Ford ◽  
Steve Fifield
Keyword(s):  
Achievement Gaps ◽  
Eighth Grade ◽  
Minority Achievement ◽  
Representative Data ◽  
Nationally Representative

scholarly journals Intermediate‐Term Risk of Stroke Following Cardiac Procedures in a Nationally Representative Data Set

2017 ◽  
Vol 6 (12) ◽  
Author(s):  
Laura Stein ◽  
Alison Thaler ◽  
John W. Liang ◽  
Stanley Tuhrim ◽  
Amit S. Dhamoon ◽  
...  
Keyword(s):  
Data Set ◽  
Representative Data ◽  
Cardiac Procedures ◽  
Nationally Representative

Childhood Intelligence Predicts Adult Trait Openness

2016 ◽  
Vol 37 (2) ◽  
pp. 105-111 ◽  
Author(s):  
Adrian Furnham ◽  
Helen Cheng
Keyword(s):  
Structural Equation Modeling ◽  
Structural Equation ◽  
Social Background ◽  
Study Data ◽  
Equation Modeling ◽  
Direct Effects ◽  
Data Set ◽  
National Child Development Study ◽  
Nationally Representative ◽  
The Uk

Abstract. This study used a longitudinal data set of 5,672 adults followed for 50 years to determine the factors that influence adult trait Openness-to-Experience. In a large, nationally representative sample in the UK (the National Child Development Study), data were collected at birth, in childhood (age 11), adolescence (age 16), and adulthood (ages 33, 42, and 50) to examine the effects of family social background, childhood intelligence, school motivation during adolescence, education, and occupation on the personality trait Openness assessed at age 50 years. Structural equation modeling showed that parental social status, childhood intelligence, school motivation, education, and occupation all had modest, but direct, effects on trait Openness, among which childhood intelligence was the strongest predictor. Gender was not significantly associated with trait Openness. Limitations and implications of the study are discussed.

Subtractive MLM and Prosodically Defective Morphemes

2017 ◽  
Author(s):  
Eva Zimmermann
Keyword(s):  
Prosodic Structure ◽  
Standard Assumption ◽  
Data Set ◽  
Representative Data

It is shown how the theory of PDM accounts for instances of subtractive MLM—the empirical phenomenon that is notoriously challenging for the claim that morphology is additive. Two general mechanisms inside PDM can predict subtractive MLM: usurpation of moras and the defective integration of morphemic prosodic nodes. Usurpation can arise if a segment underlyingly lacks a mora and ‘usurps’ it from a neighbouring segment that is hence deprived of it. In the second scenario, a prosodic node that is underlyingly not integrated into the higher/lower prosodic structure is affixed to a base and remains defectively integrated in the output. Given the standard assumption that only elements properly integrated under the highest prosodic node of the prosodic hierarchy are visible for the phonetics, this affix node and everything it dominates remain phonetically uninterpreted. It is shown how all attested types of subtractive MLM in the representative data set fall out from these two basic mechanisms.

STEM-Focused Career Courses and College Pipeline for Students with Learning Disabilities

2021 ◽  
pp. 089590482110199
Author(s):  
Jennifer A. Freeman ◽  
Michael A. Gottfried ◽  
Jay Stratte Plasman
Keyword(s):  
High School ◽  
Learning Disabilities ◽  
High School Students ◽  
The United States ◽  
Students With Learning Disabilities ◽  
School Students ◽  
Data Set ◽  
Stem Majors ◽  
Career And Technical ◽  
Nationally Representative

Recent educational policies in the United States have fostered the growth of science, technology, engineering, and mathematics (STEM) career-focused courses to support high school students’ persistence into these fields in college and beyond. As one key example, federal legislation has embedded new types of “applied STEM” (AS) courses into the career and technical education curriculum (CTE), which can help students persist in STEM through high school and college. Yet, little is known about the link between AS-CTE coursetaking and college STEM persistence for students with learning disabilities (LDs). Using a nationally representative data set, we found no evidence that earning more units of AS-CTE in high school influenced college enrollment patterns or major selection in non-AS STEM fields for students with LDs. That said, students with LDs who earned more units of AS-CTE in high school were more likely to seriously consider and ultimately declare AS-related STEM majors in college.

scholarly journals The COVID Connection: Pandemic Anxiety, COVID-19 Comprehension, and Digital Confidence

2021 ◽  
pp. 000276422110031
Author(s):  
Laura Robinson ◽  
Jeremy Schulz ◽  
Øyvind N. Wiborg ◽  
Elisha Johnston
Keyword(s):  
Logistic Models ◽  
The United States ◽  
Sociodemographic Factors ◽  
Future Research ◽  
Lower Probability ◽  
Data Set ◽  
Digital Inequality ◽  
Partner Status ◽  
General Anxiety ◽  
Nationally Representative

This article presents logistic models examining how pandemic anxiety and COVID-19 comprehension vary with digital confidence among adults in the United States during the first wave of the pandemic. As we demonstrate statistically with a nationally representative data set, the digitally confident have lower probability of experiencing physical manifestations of pandemic anxiety and higher probability of adequately comprehending critical information on COVID-19. The effects of digital confidence on both pandemic anxiety and COVID-19 comprehension persist, even after a broad range of potentially confounding factors are taken into account, including sociodemographic factors such as age, gender, race/ethnicity, metropolitan status, and partner status. They also remain discernable after the introduction of general anxiety, as well as income and education. These results offer evidence that the digitally disadvantaged experience greater vulnerability to the secondary effects of the pandemic in the form of increased somatized stress and decreased COVID-19 comprehension. Going forward, future research and policy must make an effort to address digital confidence and digital inequality writ large as crucial factors mediating individuals’ responses to the pandemic and future crises.

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