World education finance policies and higher education access: A statistical analysis of World Development Indicators for 86 countries

Yang, Lijing; McCall, Brian P.

doi:10.1016/j.ijedudev.2012.11.002

Cited by 37 publications

(27 citation statements)

References 48 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Background -For our user model, we drew inspiration from a common formula for research in the social and life science domains: some process-often orchestrated by a government agency-collects and updates a well-curated dataset that captures some general observations (e.g., health details of citizens, or economic statistics), and a researcher uses a subset of the data to draw conclusions. Examples of this can be found throughout economics [31,33,36,46,49], medicine [16,19,30,40,41], and more. Since our current work focuses on filter-based transformations, there are some use cases we do not support, such as grouping-based transformations [26,27] and non-declarative, or ordered, transformations [26], which we leave for future work.…”

Section: Overviewmentioning

confidence: 99%

“…For the current work, we assume all transformations are in the form of filters (i.e., relational selections); thus, some transformations are not possible (e.g., folding or extraction), but for many applications-such as research in economics [31,33,36,46,49] and medicine [16,19,30,40,41] that use curated datasets (several of which we test in our experiments)-filters are the only transformations needed.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Constraint-based explanation and repair of filter-based transformations

Antenucci

Cafarella

2018

Proc. VLDB Endow.

View full text Add to dashboard Cite

Data analysts often need to transform an existing dataset, such as with filtering, into a new dataset for downstream analysis. Even the most trivial of mistakes in this phase can introduce bias and lead to the formation of invalid conclusions. For example, consider a researcher identifying subjects for trials of a new statin drug. She might identify patients with a high dietary cholesterol intake as a population likely to benefit from the drug, however, selection of these individuals could bias the test population to those with a generally unhealthy lifestyle, thereby compromising the analysis. Reducing the potential for bias in the dataset transformation process can minimize the need to later engage in the tedious, time-consuming process of trying to eliminate bias while preserving the target dataset. We propose a novel interaction model for explain-andrepair data transformation systems, in which users interactively define constraints for transformation code and the resultant data. The system satisfies these constraints as far as possible, and provides an explanation for any problems encountered. We present an algorithm that yields filterbased transformation code satisfying user constraints. We implemented and evaluated a prototype of this architecture, Emeril, using both synthetic and real-world datasets. Our approach finds solutions 34% more often and 77% more quickly than the previous state-of-the-art solution.

show abstract

Section: Overviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Constraint-based explanation and repair of filter-based transformations

Antenucci

Cafarella

2018

Proc. VLDB Endow.

View full text Add to dashboard Cite

show abstract

“…The World Bank's Development Indicators Database has been used in previous peerreviewed research relating to education (see Shin & Harman, 2009;Yang & McCall, 2013). This metric is not a measure of the level of education but a measure of relative access.…”

Section: Independent Variablesmentioning

confidence: 99%

Women on Corporate Boards

2016

View full text Add to dashboard Cite

How do a country's basic institutions enable or hinder women's rise to the boards of public companies? The study evaluates this question with reference to the five basic institutions that research suggests are common across all countries: family, education, economy, government, and religion. The study draws on a sample, which consists of 23 countries, and the study is framed in neo-institutional theory. In analyzing the role of these institutions, the article seeks to understand better the relationships between specific institutions and the share of board seats held by women. The results suggest that four of the five basic institutions are related to the share of board seats women hold. Family, education, economy, and government influence women's rise to the board; however, religion does not influence women's rise to the corporate board of directors.Keywords corporate board diversity, corporate boards, board demography, institutional theory, women on boards Female corporate board directors remain a minority in the vast majority of boardrooms of publicly listed companies the world over (Branson, 2012).

show abstract

“…Over 10000 ectopic pregnancies are diagnosed each year [4]. In Iran, 13 stillbirths per 1000 live births have been reported [5], but accurate statistics on miscarriage rates in Iran are not available, and from 70.45 to 116.9 miscarriage per 1000 live births are reported [6].…”

Section: Introductionmentioning

confidence: 99%

The Impact of Implementing Steps of Empowerment Model for Women with Failed Pregnancies on Decisional Conflict for Re-pregnancy: A Randomized Controlled Trial

Kheirkhah¹,

Salehabadi²,

Esmaeeli³

et al. 2020

Preprint

View full text Add to dashboard Cite

Background: Failed pregnancy is a common and destructive experience. It has physical and psychological effects on both women and families. They may become reluctant to re-pregnancy. Providing the coping strategies can help to adapt to failed pregnancies, and make informed decisions about future pregnancies. This study was designed and performed to determine the effect of implementing steps of empowerment model for women with failed pregnancies on decision conflict for re-pregnancy. Method: This interventional research is a randomized controlled trial with a control group that was conducted in Iran from January 2020 to May 2020. Participants were 80 women who had been hospitalized in a referral center during past 3-6 weeks due to failed pregnancies. The eligible women with random allocation of sealed envelope site were divided into two groups of intervention (n=40) and control (n=40) and a separate code was determined for each person. The intervention was performed in four, 90-minute sessions based on the model steps (threat perception, problem solving, educational participation, and evaluation) for intervention group. O'Connor's decisional conflict scale was completed before and six weeks after intervention by both of groups. Data were analyzed using SPSS edition 16 with the independent T-test, Fisher and chi-squared tests. Results: The score of decisional conflict and, its subscales did not differ between the two groups before the intervention (P = 0.65), but six weeks after the intervention, the decisional conflict and, all its subscales in the intervention group reduced. (P < 0.001).Conclusion: Empowerment education in women with a failed pregnancy improved their decision conflict in re-pregnancy, so empowerment education along with health care services for women with failed pregnancies is recommended. Trial registration: This randomized control trial was registered on the TCTR site with the code TCTR20191226001. Registered on 26 December 2019.

show abstract

World education finance policies and higher education access: A statistical analysis of World Development Indicators for 86 countries

Cited by 37 publications

References 48 publications

Constraint-based explanation and repair of filter-based transformations

Constraint-based explanation and repair of filter-based transformations

Women on Corporate Boards

The Impact of Implementing Steps of Empowerment Model for Women with Failed Pregnancies on Decisional Conflict for Re-pregnancy: A Randomized Controlled Trial

Contact Info

Product

Resources

About