Workplace discrimination and spinal cord injury: The national EEOC ADA research project

This article provides data from the National EEOC ADA Research Project comparing several aspects of employment discrimination experienced by individuals with Spinal Cord Injury (SCI) to that of a group of individuals with other physical, sensory or neurological impairments (GENDIS). Compared with GENDIS, the SCI group was younger with more males and fewer minorities. The SCI group had a significantly higher proportion of resolved complaints involving Hiring, Promotion and Reinstatement and a lower proportion of issues involving Discharge, Reasonable Accommodation, Harassment, Discipline and Intimidation. Allegations of discrimination against people with SCI occurred more often in the Services and Public Administration industries, more often among small employers, and more often among employers located in the South. EEOC findings of No Cause in which full investigation fails to support the alleged violation are significantly less common in SCI than in GENDIS. SCI employers were more likely to accept those remedies proposed by the EEOC. Implications and recommendations regarding these findings are provided. © 2005 - IOS Press and the authors. All rights reserved

Subversion of Religious Canon in Pullman’s His Dark Materials

In 2000 the final volume of the fantasy trilogy His Dark Materials was published in London. Although it was only after New Line Cinema announced the film adaptation that it attracted world wide attention, it is undeniable that Pullman’s work made an immense contribution not only to children’s literature, but to British literature in general. The fact that Pullman was the first children’s author to receive The Whitbread Award, as well as the sales of more than 15 million, speak in favour of the significance his work. However, because of his public outbursts against the boycotters of his works, Pullman came under strident criticism. Unconventional usage of traditional religious and Church-related concepts as literary devices brought into question his integrity as an author and designated him as a fervent atheist. The central aim of this paper is to show how Pullman uses various religious concepts, which are mainly related to Christian tradition and doctrines. The resonant imagery of His Dark Materials carries numerous canonical references, primarily from the Bible, but also from Milton’s Paradise Lost and the works of William Blake. Pullman employs different strategies throughout the volumes to introduce these, somewhat dogmatic, precepts; they are either rewritten in a way that casts new light upon the matters they relate to or are presented unaltered per se, but in a completely new context that enables a different, allegorical reading of the canonical item. This paper opens with a short explication of the religious canon, followed by examples of its subversion in His Dark Materials. Special emphasis is placed on the transfer and modification of the traditional Christian religious concepts into fantasy fiction context and a relatively critical replica of the Catholic Church in His Dark Materials

Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data

Abstract: Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machine learning (ML) approaches incited us to apply them to classify healthy and diseased people according to their genomic information. The Immunochip dataset containing 18,227 CD patients and 34,050 healthy controls enrolled and genotyped by the international Inflammatory Bowel Disease genetic consortium (IIBDGC) has been re-analyzed using a set of ML methods: penalized logistic regression (LR), gradient boosted trees (GBT) and artificial neural networks (NN). The main score used to compare the methods was the Area Under the ROC Curve (AUC) statistics. The impact of quality control (QC), imputing and coding methods on LR results showed that QC methods and imputation of missing genotypes may artificially increase the scores. At the opposite, neither the patient/control ratio nor marker preselection or coding strategies significantly affected the results. LR methods, including Lasso, Ridge and ElasticNet provided similar results with a maximum AUC of 0.80. GBT methods like XGBoost, LightGBM and CatBoost, together with dense NN with one or more hidden layers, provided similar AUC values, suggesting limited epistatic effects in the genetic architecture of the trait. ML methods detected near all the genetic variants previously identified by GWAS among the best predictors plus additional predictors with lower effects. The robustness and complementarity of the different methods are also studied. Compared to LR, non-linear models such as GBT or NN may provide robust complementary approaches to identify and classify genetic markers