scholarly journals Female unemployment and its determinants in Poland in 2016 from the spatial perspective

2018 ◽  
Vol 9 (2) ◽  
pp. 183-204
Author(s):  
Karolina Lewandowska-Gwarda
Keyword(s):  
Social Factors ◽  
Statistical Data ◽  
Value Added ◽  
Traditional Role ◽  
Spatial Perspective ◽  
Geographic Space ◽  
Working Age ◽  
Research Questions ◽  
Gwr Model ◽  
Geographical Space

Research background: Through the cultural progress and socio-economic development in Poland women have obtained the same rights as men in the labour market. Nevertheless, they continuously face discrimination and the difficulty, resulting from their traditional role, in finding or maintaining employment. Purpose of the article: The main objective of this study was an analysis of female unemployment and its determinants in Poland in 2016 from the spatial perspective. The following research questions were also specified: Is female unemployment dependent on social factors (do they play the key role)? Are the factors determining the level of female unemployment spatially diversified? Is the GWR model an effective tool in analysis of female unemployment? Methods: The research applied GIS and spatial analysis methods including Geographically Weighted Regression, which enables the identification of the variability of regression coefficients in the geographical space. The analysis was carried out based on statistical data presenting the share of unemployed women in the working age population for 380 Polish districts (NUTS 4, LAU 1) in 2016. Findings & Value added: The research results showed that in the period 2003-2016 the female unemployment was getting lower, but it was still higher than men. It was also spatially diversified. Moreover, the determinants of female unemployment were diverse in the geographic space and did not have a significant impact on the variable in all spatial units. The existence of clusters of districts, characterised by similar interactions and its strength, was also confirmed. The results of this analysis proved that non-economic (social) factors largely affected the level of female unemployment in Poland in 2016. Using GWR enabled drawing detailed conclusions concerning the determinants of female unemployment in Poland, it proved to be an effective tool for the analysis of this phenomenon.

scholarly journals Female unemployment and its determinants in Poland in 2016 from the spatial perspective

2018 ◽  
Vol 9 (2) ◽  
pp. 183-204 ◽  
Author(s):  
Karolina Lewandowska-Gwarda
Keyword(s):  
Social Factors ◽  
Statistical Data ◽  
Value Added ◽  
Traditional Role ◽  
Spatial Perspective ◽  
Geographic Space ◽  
Working Age ◽  
Research Questions ◽  
Gwr Model ◽  
Geographical Space

Research background: Through the cultural progress and socio-economic development in Poland women have obtained the same rights as men in the labour market. Nevertheless, they continuously face discrimination and the difficulty, resulting from their traditional role, in finding or maintaining employment. Purpose of the article: The main objective of this study was an analysis of female unemployment and its determinants in Poland in 2016 from the spatial perspective. The following research questions were also specified: Is female unemployment dependent on social factors (do they play the key role)? Are the factors determining the level of female unemployment spatially diversified? Is the GWR model an effective tool in analysis of female unemployment? Methods: The research applied GIS and spatial analysis methods including Geographically Weighted Regression, which enables the identification of the variability of regression coefficients in the geographical space. The analysis was carried out based on statistical data presenting the share of unemployed women in the working age population for 380 Polish districts (NUTS 4, LAU 1) in 2016. Findings & Value added: The research results showed that in the period 2003-2016 the female unemployment was getting lower, but it was still higher than men. It was also spatially diversified. Moreover, the determinants of female unemployment were diverse in the geographic space and did not have a significant impact on the variable in all spatial units. The existence of clusters of districts, characterised by similar interactions and its strength, was also confirmed. The results of this analysis proved that non-economic (social) factors largely affected the level of female unemployment in Poland in 2016. Using GWR enabled drawing detailed conclusions concerning the determinants of female unemployment in Poland, it proved to be an effective tool for the analysis of this phenomenon.

scholarly journals What determines the permanent emigration of Poles? The analysis of the spatial diversification of causes in three economic age groups

2017 ◽  
Vol 67 (2) ◽  
pp. 149-172 ◽  
Author(s):  
Karolina Lewandowska-Gwarda ◽  
Elżbieta Antczak
Keyword(s):  
Geographically Weighted Regression ◽  
Statistical Data ◽  
Age Groups ◽  
Time Span ◽  
Regression Coefficients ◽  
Economic Factors ◽  
Working Age ◽  
Spatial Diversification ◽  
Geographical Space ◽  
Socio Economic Factors

Our paper seeks answers to the following questions: What are the determinants of permanent emigration from Poland and how do they vary for specific economic age groups (pre-working, working, and post-working age)? Do the causes of permanent emigration differ over space in these categories, and if so, how? We applied GIS and ESDA instruments, including geographically weighted regression, which allowed us to identify the variability of regression coefficients in the geographical space. Our research indicated socio-economic factors (among others: poviats budget income, feminisation rate, unemployment rate), which, with varying force and in varying directions, affected the studied variable in specific parts of the country. The analyses were performed on the basis of statistical data on the numbers of de-registrations for residence abroad in Poland’s NUTS-4 in three economic age groups (pre-working, working, and post-working age) for the time span from 2005 to 2013.

scholarly journals RETURN MIGRATION TRENDS IN LATVIA: RE-ATTRACTING THE MAIN HUMAN RESOURCE FOR SUSTAINABLE REGIONAL DEVELOPMENT

2019 ◽  
Vol 1 ◽  
pp. 16 ◽  
Author(s):  
Elina Apsite-Berina ◽  
Girts Burgmanis ◽  
Zaiga Krisjane
Keyword(s):  
Regional Development ◽  
Return Migration ◽  
Statistical Data ◽  
Return Migrants ◽  
Main Research ◽  
Key Concepts ◽  
Working Age ◽  
Research Questions ◽  
Sustainable Regional Development ◽  
And Migration

This study is devoted to the research of human resources as a main source of sustainable regional development in Latvia. It is focused on two key concepts of human capital and migration. The aim of the study is to explore return migration geographies by looking at young return migrants as a resource and preconditions for sustainable regional development essential to Latvia.Return migration to the regions of Latvia is examined by two main research questions. What are the most recent return migrant characteristics in Latvia? How does return migration of young Latvians translates into regional geographies of return migration?Drawing on most recent available statistical data we elaborate on the return migration trends in Latvia, look at particular geographies of return migrants to the regions of Latvia. Findings show that return migrants are working age accompanied with their offspring’s, majority not married and return from another European country to the capital and other largest cities and surrounding municipalities. Even more, only ethnicity and country of previous residence serve as return migration predictor.  

scholarly journals Tourist Traffic In The Aconcagua Massif Area

2015 ◽  
Vol 34 (3) ◽  
pp. 65-76 ◽  
Author(s):  
Aneta Marek ◽  
Małgorzata Wieczorek
Keyword(s):  
Statistical Data ◽  
Age Groups ◽  
Spatial Perspective ◽  
The Usa ◽  
Temporal And Spatial

Abstract The aim of the article is an analysis of tourist traffic in the Aconcagua massif, one of the most popular peaks of the Seven Summits. On the basis of statistical data, the tourist traffic was analysed in a temporal and spatial perspective. The applied data made it possible to capture the dynamics of visits in the period 2000/2001 – 2012/2013 and with a breakdown into months, which helped analyse the tourist traffic in this area. In each of the analysed periods, January dominates. Data concerning the origin of tourists according to countries and continents, their age, gender and type of mountaineering activity were also taken into account. Most tourists came from Argentina, the USA and Germany. These are people of age groups 21–30 (33%) and 31–40 (31%). Men account for over 75% of visitors. The favourite mountaineering activity is climbing (about 60%). Aconcagua has invariably been a very popular peak among tourists and climbers. It is a place for training and acclimatisation for alpinists, participating in Himalayan expeditions and climbers collecting peaks of the Seven Summits.

Study on Prediction of the Peasants’ Income Based on SVM

2014 ◽  
Vol 687-691 ◽  
pp. 5169-5172
Author(s):  
Li Na Zhang ◽  
Bo Yang
Keyword(s):  
Social Factors ◽  
Index System ◽  
Statistical Data ◽  
Influence Factors ◽  
Prediction Method ◽  
Svm Model ◽  
The Index System ◽  
Relationship Of ◽  
System Designs ◽  
Computing Speed

China is a big agricultural country, effective prediction of peasants’ income is very important. This study mainly uses the SVM theory to predict the peasants’ income. By analyzing the influence factors of peasants’ income, establishes the index system, that is corresponding relationship of peasants’ income and factors of social influence, According to this index system, designs the prediction method of peasants’ income based on SVM. Bases on the statistical data of social factors and peasants’ income between 1990-2012 in china, to train the SVM model, at the same time, the kernel function and parameters of SVM used were setting and compared. The experimental results show that the accuracy of RBF function is 90.7%, the time is 98ms, has higher accuracy and faster computing speed.

scholarly journals Rediscovering the Geographic Space through the Geographical Space

1998 ◽  
pp. 13
Author(s):  
Delfina Trinca Fighera
Keyword(s):  
Geographic Space ◽  
Geographical Space

Este artigo pretende discutir a técnica enquanto expressáo das relações entre o Homem e o espaço por ele ocupado, por ele transformado. Buscando nos aproximar de uma visão geográfica das ações do Homem sobre a Natureza, tentam os entender a construção do "presente" e sua configuração nos tempos atuais

Assessment in Authentic Environments

2012 ◽  
pp. 32-57
Author(s):  
Thomas C. Hammond ◽  
R. Curby Alexander ◽  
Alec M. Bodzin
Keyword(s):  
Social Studies ◽  
Student Learning ◽  
Learning Outcomes ◽  
Instructional Strategy ◽  
Value Added ◽  
Student Learning Outcomes ◽  
Validity And Reliability ◽  
Research Questions ◽  
Conducting Research ◽  
K 12

The TPACK framework provides researchers with a robust framework for conducting research on technology integration in authentic environments, i.e., intact classrooms engaged in standards-aligned instruction. Researchers who wish to identify the value added by a promising technology-supported instructional strategy will need to assess student learning outcomes in these environments; unfortunately, collecting valid and reliable data on student learning in classroom research is extremely difficult. To date, few studies using TPACK in K-12 classrooms have included student learning outcomes in their research questions, and researchers are therefore left without models to guide their development, implementation, and analysis of assessments. This chapter draws upon the literature and our own research and assessment experiences in technology-integrated, standards-aligned classroom instruction to give examples and advice to researchers as they develop, analyze, and write up their observations of student learning outcomes. In particular, we focus on standard items, specifically multiple choice items, as an accepted (if limited) method for assessing student understanding. We seek to fill an existing gap in the literature between assessment advice for educational psychologists (who typically work outside of classroom settings) and advice given to teachers (who have lower thresholds for issues such as validity and reliability). Classroom researchers will benefit from this advice to develop, validate, and apply their own objective assessments. We focus on the content areas of science and social studies, but this advice can be applied to others as well.

Quantitative Legal Research

2020 ◽  
pp. 383-466
Author(s):  
P. Ishwara Bhat
Keyword(s):  
Data Analysis ◽  
Sample Size ◽  
Quantitative Data ◽  
Policy Making ◽  
Statistical Data ◽  
Central Tendency ◽  
Legal Research ◽  
Political Implications ◽  
Research Questions ◽  
Law Commission

Study of statistical data becomes inevitable because of the far-reaching socio-economic dimensions, demographic factors, and political implications of law’s operation. Quantitative legal research (QLR) insists on scientific measurement of the phenomena and appropriate generalization based on data analysis. The growing importance of QLR can be found in the policy making and implementing function of legislature, judiciary, and administration, and in the works of the Law Commission, policy researchers, and legal academicians. Designing of QLR entails framing of research questions, hypothesis formulation, and testing of the hypothesis in light of the statistical data collected. The sample size should be statistically appropriate and collection, organisation, presentation, analysis, and interpretation of data in QLR needs to be systematic. Analysing quantitative data by focusing on proportion, central tendency, and deviation enables to observe trends.

Does Student Sorting Invalidate Value-Added Models of Teacher Effectiveness? An Extended Analysis of the Rothstein Critique

2011 ◽  
Vol 6 (1) ◽  
pp. 18-42 ◽  
Author(s):  
Cory Koedel ◽  
Julian R. Betts
Keyword(s):  
Teacher Effectiveness ◽  
Value Added ◽  
Classroom Teaching ◽  
First Year ◽  
Value Added Models ◽  
Value Added Model ◽  
Extended Analysis ◽  
Research Questions ◽  
Value Added Modeling ◽  
Student Sorting

Value-added modeling continues to gain traction as a tool for measuring teacher performance. However, recent research questions the validity of the value-added approach by showing that it does not mitigate student-teacher sorting bias (its presumed primary benefit). Our study explores this critique in more detail. Although we find that estimated teacher effects from some value-added models are severely biased, we also show that a sufficiently complex value-added model that evaluates teachers over multiple years reduces the sorting bias problem to statistical insignificance. One implication of our findings is that data from the first year or two of classroom teaching for novice teachers may be insufficient to make reliable judgments about quality. Overall, our results suggest that in some cases value-added modeling will continue to provide useful information about the effectiveness of educational inputs.

Strategic benchmarking of service pricing based on the value added

2016 ◽  
Vol 23 (4) ◽  
pp. 754-767 ◽  
Author(s):  
Carlos Renato Trento ◽  
Timóteo Stüker ◽  
Giancarlo Medeiros Pereira ◽  
Miriam Borchardt ◽  
Cláudia V. Viegas
Keyword(s):  
Value Added ◽  
Spare Parts ◽  
Pricing Policy ◽  
Content Type ◽  
Customer Expectations ◽  
Goods And Services ◽  
Case Research ◽  
Service Pricing ◽  
Research Questions ◽  
New Goods

Purpose – The purpose of this paper is to investigate opportunities to move benchmarking studies toward a strategic level. The authors benchmarked how service prices are defined based on the value added for the customer. Design/methodology/approach – A multi-case research investigated how manufacturers can increase their service revenues; how corporate reputation can be analyzed to enhance financial and market performance; how customer satisfaction and price acceptance are related; and how benchmark studies can move to a more strategic level based on a conjoint analysis of value and price. Findings – Price’s benchmarking studies must combine the customers’ value demands; the customer expectations associated to each value demand; the competitor prices; and the revenue alternatives that a supplier can explore (e.g. sale of new goods, services for new goods, services for non-new goods, and repair parts). The combination of these elements reveals several opportunities for revenue generation. This combination may also help to explain the existence of different prices for similar goods and services. The authors referred to this as a flexible pricing policy. Flexible pricing may help manufacturers maximize revenues, and win and maintain customers. Research limitations/implications – The following research questions are suggested for future studies: What other elements should be considered in strategic benchmarking studies? What other elements can influence a flexible pricing policy for goods, spare parts, and services? In what contexts can a flexible pricing policy be applied? How should flexible pricing practices be benchmarked? Practical implications – A strategic benchmarking study must first identify the customers’ value demands. It is then necessary to analyze customer expectations associated to each value demand. As shown, customers may have different expectations for the same product or service. Similar expectations must be grouped together in order to allow a well-structured benchmark. Originality/value – The authors’ findings suggest interesting points to be observed by the manufacturers who supply integrated solutions with a long life cycle.

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