Welfare regimes and change in the employment structure: Britain, Denmark and Germany since 1990

Welfare states are often reduced to their role as providers of social protection and redistribution. In 1990, Esping-Andersen argued that they also affect employment creation and the class structure. We analyse the stratification outcomes for three welfare regimes - Britain, Germany and Denmark - over the 1990s and 2000s. Based on individual-level surveys, we observe a disproportionate increase among professionals and managers, and a decline among production workers and clerks. The result is clear-cut occupational upgrading in Denmark and Germany. In Britain, high and low-end service jobs expanded, resulting in a polarized version of upgrading. Growth in low-end service jobs - and thus polarization - is no precondition for full employment. Both Britain and Denmark halved their low-educated unemployment rate between 1995 and 2008. Yet low-end service jobs expanded only in Britain, not in Denmark. The cause is the evolution of labour supply: rising educational attainment means that fewer low-educated workers look for low-skilled jobs.

Study to establish an evaluation system for State of Iowa Merit Employment System classifications on the basis of comparable worth, 1984

This final report establishes an evaluation system for the State of Iowa Merit Employment System classifications on the basis of comparable worth. Included in the report are summaries of the project's objectives, methods, analyses, findings, and recommendations.

Study to establish an evaluation system for State of Iowa Merit Employment System classifications on the basis of comparable worth, Statistical Supplement, 1984

This is the statistical supplement to the final report of the study to establish an evaluation system for State of Iowa Merit Employment System classifications on the basis of comparable worth.

EEG windowed statistical wavelet scoring for evaluation and discrimination of muscular artifacts

EEG recordings are usually corrupted by spurious extra-cerebral artifacts, which should be rejected or cleaned up by the practitioner. Since manual screening of human EEGs is inherently error prone and might induce experimental bias, automatic artifact detection is an issue of importance. Automatic artifact detection is the best guarantee for objective and clean results. We present a new approach, based on the time–frequency shape of muscular artifacts, to achieve reliable and automatic scoring. The impact of muscular activity on the signal can be evaluated using this methodology by placing emphasis on the analysis of EEG activity. The method is used to discriminate evoked potentials from several types of recorded muscular artifacts—with a sensitivity of 98.8% and a specificity of 92.2%. Automatic cleaning ofEEGdata are then successfully realized using this method, combined with independent component analysis. The outcome of the automatic cleaning is then compared with the Slepian multitaper spectrum based technique introduced by Delorme et al (2007 Neuroimage 34 1443–9).

Public Employment Relations Board Performance Plan, FY2015

Agency Performance Plan, Public Employment Relations Board

Coherency and sharpness measures by using ICA algorithms. An investigation for Alzheimer’s disease discrimination

In this paper, we present a comprehensive study of different Independent Component Analysis (ICA) algorithms for the calculation of coherency and sharpness of electroencephalogram (EEG) signals, in order to investigate the possibility of early detection of Alzheimer’s disease (AD). We found that ICA algorithms can help in the artifact rejection and noise reduction, improving the discriminative property of features in high frequency bands (specially in high alpha and beta ranges). In addition to different ICA algorithms, the optimum number of selected components is investigated, in order to help decision processes for future works.

Investigation of ICA algorithms for feature extraction of EEG signals in discrimination of Alzheimer disease

In this paper we present a quantitative comparisons of different independent component analysis (ICA) algorithms in order to investigate their potential use in preprocessing (such as noise reduction and feature extraction) the electroencephalogram (EEG) data for early detection of Alzhemier disease (AD) or discrimination between AD (or mild cognitive impairment, MCI) and age-match control subjects.

Sectoral and occupational employment growth in Spain 1995-2005

Between 1995 and 2005, the Spanish economy grew at an annual average rate higher than 3,5%. Total employment increased by more than 4.9 millions. Most of this growth was in occupations related with university degrees (more than 890,000, 18% of the total employment increase) and vocational qualifications (more than 855,000, 17.5% of the total employment increase). From a sectoral perspective, the main part of this increase took place in “Real estate, renting and business activities” (K sector in NACE rev.1), “Construction” (F sector) and “Health and social sector” (N sector). This paper analyses this employment growth in an Input-output framework, by means of a structural decomposition analysis (SDA). Two kinds of results have been obtained. From a sectoral perspective we decompose employment growth into Labour requirements change, technical change and demand change. From an occupational perspective, we decompose the employment growth in substitutions effect, labour productivity effect and demand effect. The results show that, in aggregated terms, the main part of this growth is attributable to demand growth, with a small technical improvement. But the results also show that this aggregated behaviour hides important sectoral and occupational variation. The purpose of this paper is to contribute to the ongoing debate over productivity growth and what has been called the “growth model” for the Spanish economy.

The 10 Step Equal Pay Self-Audit for Employers

This publication is a 10-step audit for employers to see if they are paying their female employees as much as their male employees

Pathways for Academic Career and Employment (PACE) Program, FY 2014 Report,

The pathways for academic career and employment program (PACE) is established to provide funding to community colleges for the development of projects that will lead to gainful, quality, in-state employment for members of target populations by providing them with both effective academic and employment training to ensure gainful employment and customized support services.