Pay Transparency: Conceptualization and Implications for Employees, Employers, and Society as a Whole

Pay transparency refers to the degree to which pay communication policies and practices governing employee pay knowledge facilitate or restrict the sharing of pay-related information. While relatively few enterprises have adopted transparent pay-communication practices, a variety of institutional factors, such as government regulations and social norms, are driving employers to provide their employees with greater pay knowledge. Consensus has emerged around the existence of three main dimensions or forms of pay transparency, namely pay-outcome transparency, pay-process transparency, and pay-communication transparency. Research findings indicate that pay-outcome transparency, which relates to the degree to which pay rate information is disclosed by the employer, has both beneficial and problematic consequences, depending on the outcome. For example, while pay-outcome transparency has been consistently found to be associated with enhanced individual task performance and reduced gender-based pay discrepancies, it has also been associated with higher levels of envy, diminished helping, heightened levels of counterproductive work behavior, and pay compression (which could elicit negative sorting effects). In contrast, pay-process transparency, which relates to the degree to which employees are informed about the parameters underlying reward-related decisions, has been found to have largely beneficial consequences and few unintended negative consequences. Finally, while it is least studied, pay-communication transparency, capturing the degree to which restrictions are placed on employees’ ability to share pay knowledge with others, is positively associated with employee perceptions of employer fairness and trustworthiness and can have significant implications for employee retention.

EP.TH.15Review of cholecystectomies laparoscopic & open plus conversion rate in a five year period

Aim Look & audit our practice of cholecystectomy & try to identify areas that require improvement Method Look at all cholecystectomies, laparoscopic & open in 5 years from January 2014 till December 2018, we looked at demographics, number of operations per year, conversion & re-admission rate, information collected from electronic note record Results male to female ratio similar to national figures, number of laparoscopic operations (2422 in that period, 61 cases converted, conversion rate 2.5%) going up steadily over the 5 years while open & conversion rate are dropping significantly, early re-admission rate higher than national figure, reasons for conversion determined & analysed Reasons for doing it open from the start also determined, commonest cause for conversion in our trust is: previous surgery/adhesions, obscure anatomy & severe inflammation of gall bladder . Commonest cause of re-admission is pain followed by wound complications collections retained stone & bile leak. Number of open cholecystectomies was 22 in 2104 dropping to only 2 in 2018. 3 deaths occurred in the group giving rise to a mortality of 0.12% Conclusion Majority of cases attempted laparoscopically & most patients discharged home within 48 hours, our conversion rate is low = 2.5% with consultants with higher number of operation having less conversions, ours re-admission rate is high mainly for pain, our mortality is low. We recommend looking closer at re-admissions to see how that number could be reduced.

Causal Information Rate

Information processing is common in complex systems, and information geometric theory provides a useful tool to elucidate the characteristics of non-equilibrium processes, such as rare, extreme events, from the perspective of geometry. In particular, their time-evolutions can be viewed by the rate (information rate) at which new information is revealed (a new statistical state is accessed). In this paper, we extend this concept and develop a new information-geometric measure of causality by calculating the effect of one variable on the information rate of the other variable. We apply the proposed causal information rate to the Kramers equation and compare it with the entropy-based causality measure (information flow). Overall, the causal information rate is a sensitive method for identifying causal relations.

Noncontact Heart Rate Measurement Using a Webcam, Based on Joint Blind Source Separation and a Skin Reflection Model: For a Wide Range of Imaging Conditions

Remote photoplethysmography (rPPG) can be used for noncontact and continuous measurement of the heart rate (HR). Currently, the main factors affecting the accuracy and robustness of rPPG-based HR measurement methods are the subject’s skin tone, body movement, exercise recovery, and variable or inadequate illumination. In response to these challenges, this study is aimed at investigating a rPPG-based HR measurement method that is effective under a wide range of conditions by only using a webcam. We propose a new approach, which combines joint blind source separation (JBSS) and a projection process based on a skin reflection model, so as to eliminate the interference of background illumination and enhance the extraction of pulse rate information. Three datasets derived from subjects with different skin tones considering six environmental scenarios are used to validate the proposed method against three other state-of-the-art methods. The results show that the proposed method can provide more accurate and robust HR measurement for all three datasets and is therefore more applicable to a wide range of scenarios.

Power of the people or the expert? The influence of vox pop and expert statements on news-item evaluation, perceived public opinion, and personal opinion

Vox pops, interviews with ordinary people on the street, are one of the most common ways to represent public opinion in television news. Research found that they influence audience judgments more than static base-rate information such as poll results. However, little research has compared vox pops with vivified base-rate information. Most research studying vox pops assumed they are included in the news because of their apparent attractiveness and trustworthiness to audiences. Using a television news experiment comparing statistical base-rate information vivified by an expert with vox pop statements, this study shows that news items containing vox pop statements are perceived as being less attractive and trustworthy than items containing the expert statement. No difference is found between the two types of public opinion information in their influence on perceived public opinion, but vox pops do influence audiences’ personal opinion more strongly.

Binding Tax Rate Information (WIS) as an expression of the principle of trust in public authorities and the principle of legal certainty

Binding Rate Information (WIS) is a new tax law system institution, in force since 1st November 2019. It is a regulation introducing the possibility of obtaining a decision of the tax authority in the scope of taxing goods and services for the supply of goods, import of goods, intra-community acquisition of goods or provision of services. The issued decision is binding, and therefore provides protection for the taxpayer. In a way, this regulation is an expression of the principles of trust in public authorities and of legal certainty, which is extremely important in the field of tax law. The main research objectives of the article are the legal analysis of the new regulations regarding Binding Rate Information, and an attempt to show that the new WIS institution fully implements the principles of legal certainty and of trust in public authorities as expressed in art. 121 o.p. The author uses the dogmatic-legal method to analyze the legal texts as well as the views of doctrine and case-law.

Investigative advising: a job for Bayes

Background: Bayesian approaches to police decision support offer an improvement upon more commonly used statistical approaches. Common approaches to case decision support often involve using frequencies from cases similar to the case under consideration to come to an isolated likelihood that a given suspect either a) committed the crime or b) has a given characteristic or set of characteristics. The Bayesian approach, in contrast, offers formally contextualized estimates and utilizes the formal logic desired by investigators. Findings: Bayes’ theorem incorporates the isolated likelihood as one element of a three-part equation, the other parts being 1) what was known generally about the variables in the case prior to the case occurring (the scientific-theoretical priors) and 2) the relevant base rate information that contextualizes the evidence obtained (the event context). These elements are precisely the domain of decision support specialists (investigative advisers), and the Bayesian paradigm is uniquely apt for combining them into contextualized estimates for decision support. Conclusions: By formally combining the relevant knowledge, context, and likelihood, Bayes’ theorem can improve the logic, accuracy, and relevance of decision support statements.

Investigative advising: a job for Bayes

Background: Bayesian approaches to police decision support offer an improvement upon more commonly used statistical approaches. Common approaches to case decision support often involve using frequencies from cases similar to the case under consideration to come to an isolated likelihood that a given suspect either a) committed the crime or b) has a given characteristic or set of characteristics. The Bayesian approach, in contrast, offers formally contextualized estimates and utilizes the formal logic desired by investigators. Findings: Bayes’ theorem incorporates the isolated likelihood as one element of a three-part equation, the other parts being 1) what was known generally about the variables in the case prior to the case occurring (the scientific-theoretical priors) and 2) the relevant base rate information that contextualizes the evidence obtained (the event context). These elements are precisely the domain of decision support specialists (investigative advisers), and the Bayesian paradigm is uniquely apt for combining them into contextualized estimates for decision support. Conclusions: By formally combining the relevant knowledge, context, and likelihood, Bayes’ theorem can improve the logic, accuracy, and relevance of decision support statements.

A Cardiotocographic Classification using Feature Selection: A comparative Study

Cardiotocography is a series of inspections to determine the health of the fetus in pregnancy. The inspection process is carried out by recording the baby's heart rate information whether in a healthy condition or contrarily. In addition, uterine contractions are also used to determine the health condition of the fetus. Fetal health is classified into 3 conditions namely normal, suspect, and pathological. This paper was performed to compare a classification algorithm for diagnosing the result of the cardiotocographic inspection. An experimental scheme is performed using feature selection and not using it. CFS Subset Evaluation, Info Gain, and Chi-Square are used to select the best feature which correlated to each other. The data set was obtained from the UCI Machine Learning repository available freely. To find out the performance of the classification algorithm, this study uses an evaluation matrix of precision, Recall, F-Measure, MCC, ROC, PRC, and Accuracy. The results showed that all algorithms can provide fairly good classification. However, the combination of the Random Forest algorithm and the Info Gain Feature Selection gives the best results with an accuracy of 93.74%.