Are employment effects of gender discrimination important? Some evidence from Great Britain

Interpreting the unexplained component of the gender wage gap as indicative of discrimination, the empirical literature to date has tended to ignore the potential impact wage discrimination may have on employment. Employment effects may arise if discrimination lowers the female offered wage and the labour supply curve is upward sloping. The empirical analysis employs the British Household Panel Study and finds evidence of both wage and associated employment effects.

Identify disorders in health records using Conditional Random Fields and Metamap: AEHRC at ShARe/CLEF 2013 eHealth Evaluation Lab Task 1

The Australian e-Health Research Centre (AEHRC) recently participated in the ShARe/CLEF eHealth Evaluation Lab Task 1. The goal of this task is to individuate mentions of disorders in free-text electronic health records and map disorders to SNOMED CT concepts in the UMLS metathesaurus. This paper details our participation to this ShARe/CLEF task. Our approaches are based on using the clinical natural language processing tool Metamap and Conditional Random Fields (CRF) to individuate mentions of disorders and then to map those to SNOMED CT concepts. Empirical results obtained on the 2013 ShARe/CLEF task highlight that our instance of Metamap (after ltering irrelevant semantic types), although achieving a high level of precision, is only able to identify a small amount of disorders (about 21% to 28%) from free-text health records. On the other hand, the addition of the CRF models allows for a much higher recall (57% to 79%) of disorders from free-text, without sensible detriment in precision. When evaluating the accuracy of the mapping of disorders to SNOMED CT concepts in the UMLS, we observe that the mapping obtained by our ltered instance of Metamap delivers state-of-the-art e ectiveness if only spans individuated by our system are considered (`relaxed' accuracy).

The effect of employment while in high school on educational attainment : a conditional difference-in-differences approach

Using American panel data from the National Education Longitudinal Study of 1988, this article investigates the effect of working during grade 12 on attainment.We employ, for the first time in the related literature, a semiparametric propensity score matching approach combined with difference-in-differences. We address selection on both observables and unobservables associated with part-time work decisions, without the need for instrumental variable. Once such factors are controlled for, little to no effects on reading and math scores are found. Overall, our results therefore suggest a negligible academic cost from part-time working by the end of high school.

Towards discrimination of challenging conditions for UGVs with visual and infrared sensors

This work aims to contribute to reliability and integrity in perceptual systems of autonomous ground vehicles. Information theoretic based metrics to evaluate the quality of sensor data are proposed and applied to visual and infrared camera images. The contribution of the proposed metrics to the discrimination of challenging conditions is discussed and illustrated with the presence of airborne dust and smoke.

A stochastic neighborhood conditional autoregressive model for spatial data

A spatial process observed over a lattice or a set of irregular regions is usually modeled using a conditionally autoregressive (CAR) model. The neighborhoods within a CAR model are generally formed deterministically using the inter-distances or boundaries between the regions. An extension of CAR model is proposed in this article where the selection of the neighborhood depends on unknown parameter(s). This extension is called a Stochastic Neighborhood CAR (SNCAR) model. The resulting model shows flexibility in accurately estimating covariance structures for data generated from a variety of spatial covariance models. Specific examples are illustrated using data generated from some common spatial covariance functions as well as real data concerning radioactive contamination of the soil in Switzerland after the Chernobyl accident.

A sequential Monte Carlo framework for adaptive Bayesian model discrimination designs using mutual information

In this paper we present a unified sequential Monte Carlo (SMC) framework for performing sequential experimental design for discriminating between a set of models. The model discrimination utility that we advocate is fully Bayesian and based upon the mutual information. SMC provides a convenient way to estimate the mutual information. Our experience suggests that the approach works well on either a set of discrete or continuous models and outperforms other model discrimination approaches.

Spreadsheet Conditional Formatting Illuminates Investigations into Modular Arithmetic

Modular arithmetic has often been regarded as something of a mathematical curiosity, at least by those unfamiliar with its importance to both abstract algebra and number theory, and with its numerous applications. However, with the ubiquity of fast digital computers, and the need for reliable digital security systems such as RSA, this important branch of mathematics is now considered essential knowledge for many professionals. Indeed, computer arithmetic itself is, ipso facto, modular. This chapter describes how the modern graphical spreadsheet may be used to clearly illustrate the basics of modular arithmetic, and to solve certain classes of problems. Students may then gain structural insight and the foundations laid for applications to such areas as hashing, random number generation, and public-key cryptography.

Calculation of the oxygen isotope discrimination factor for studying plant respiration

Measurement of discrimination against 18O during dark respiration in plants is currently accepted as the only reliable method of estimating the partitioning of electrons between the cytochrome and alternative pathways. In this paper, we review the theory of the technique and its application to a gas-phase system. We extend it to include sampling effects and show that the isotope discrimination factor, D, is calculated as –dln(1 + δ)/dlnO*, where δ is isotopic composition of the substrate oxygen and O*=[O2]/[N2] in a closed chamber containing tissue respiring in the dark. It is not necessary to integrate the expression but, if the integrated form is used, the resultant regression should not be constrained through the origin. This is important since any error in D will have significant effects on the estimation of the flux of electrons through the two pathways.

Constitutive Regulation of the Firm: occupational health and safety, dismissal, discrimination and sexual harassment

As many other chapters in this book have noted, until recently labour lawyers have tended not to draaw on regulatory scholarship. In this chapter we look at certain areas of labour law through a particular kind of regulatory lens - regulation that requires firms to reconstitute their management processes and procedures, perhaps even their organisational cultures. In particular, we examine the kinds of regulatory demands made on firms by legal rules in four areas of labour law: (i) occupational health and safety (OHS)regulation; unfair dismissal law; equal opportunity (EO) and (iv) sexual harassment law.