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.

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.

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 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.

Diagnostics of professional competence of IT students based on digital footprint data

2020 ◽  
pp. 4-11
Author(s):  
I. G. Zakharova ◽  
Yu. V. Boganyuk ◽  
M. S. Vorobyova ◽  
E. A. Pavlova
Keyword(s):  
Information Technology ◽  
Educational Program ◽  
Professional Competence ◽  
Objective Data ◽  
Text Data ◽  
Data Set ◽  
Job Requirements ◽  
Digital Footprint ◽  
Graduate Employment ◽  
The University

The article goal is to demonstrate the possibilities of the approach to diagnosing the level of IT graduates’ professional competence, based on the analysis of the student’s digital footprint and the content of the corresponding educational program. We describe methods for extracting student professional level indicators from digital footprint text data — courses’ descriptions and graduation qualification works. We show methods of comparing these indicators with the formalized requirements of employers, reflected in the texts of vacancies in the field of information technology. The proposed approach was applied at the Institute of Mathematics and Computer Science of the University of Tyumen. We performed diagnostics using a data set that included texts of courses’ descriptions for IT areas of undergraduate studies, 542 graduation qualification works in these areas, 879 descriptions of job requirements and information on graduate employment. The presented approach allows us to evaluate the relevance of the educational program as a whole and the level of professional competence of each student based on objective data. The results were used to update the content of some major courses and to include new elective courses in the curriculum.

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 Is the Genotype-Phenotype Map Modular?: A Statistical Approach Using Mouse Quantitative Trait Loci Data

Genetics ◽  
2000 ◽  
Vol 156 (1) ◽  
pp. 305-311 ◽  
Author(s):  
Jason G Mezey ◽  
James M Cheverud ◽  
Günter P Wagner
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Statistical Approach ◽  
Genetic Effects ◽  
Statistical Distribution ◽  
Data Set ◽  
Alveolar Region ◽  
Phenotypic Characters ◽  
Statistical Support ◽  
Complex Characters

Abstract Various theories about the evolution of complex characters make predictions about the statistical distribution of genetic effects on phenotypic characters, also called the genotype-phenotype map. With the advent of QTL technology, data about these distributions are becoming available. In this article, we propose simple tests for the prediction that functionally integrated characters have a modular genotype-phenotype map. The test is applied to QTL data on the mouse mandible. The results provide statistical support for the notion that the ascending ramus region of the mandible is modularized. A data set comprising the effects of QTL on a more extensive portion of the phenotype is required to determine if the alveolar region of the mandible is also modularized.

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