Beyond the Z-score: A novel measure of bank stability for effective policymaking

This article looks beyond Z-score and proposes a novel methodological framework to build an all-encompassing indicator of bank stability for individual banks using the optimisation-based ‘benefit-of-the-doubt (BoD)’ approach. Unlike other available approaches, this approach is totally data-driven and generates endogenous weights to aggregate sub-indicators of bank stability and dimensions. Further, the final outcomes are not limited to a scalar measure of bank stability. The unique optimal weights offer valuable policy-relevant insights and highlight the most precarious areas of stability, which demand the immediate attention of the bank's management and the industry regulators for both micro-and macro-level policymaking. Using the data of Indian public sector banks operating in the year 2018, the study illustrates the proposed framework to obtain a holistic indicator of bank stability, defined on 14 ratio sub-indicators and 5 broad dimensions (soundness, asset quality, profitability, management efficiency, and liquidity) of bank stability.     

The Negative Impact of Attorneys on Mediation Outcomes: A Myth or a Reality?

Mediators often do not welcome the presence of attorneys at the mediation table. Because of the apparent contradictions between both professions, many mediators believe that the presence of attorneys is prejudicial to the mediation process. Using empirical data collected from workplace mediation cases, we have explored the actual impact of the presence of attorneys. Our results indicate that the presence of an attorney does not significantly affect the outcome of a mediation, with two exceptions. First, the presence of attorneys in a mediation process reduces the parties' level of satisfaction with the mediator. Second, the presence of an attorney would appear to hinder the level of reconciliation possible between the parties.     

China's new regulatory regime tailored for the sharing economy: The case of Uber under Chinese local government regulation in comparison to the EU,US, and the UK

Although Uber's arrival in China has resulted in disruptive competition for incumbent taxi companies, it offers an attractive alternative in China's supply-demand-imbalanced urban passenger transport system. China's regulatory regime for Uber has evolved in three stages: from the regulatory vacuum prior to 2015 to its official legalization in 2015–2016, and the enactment of numerous local regulations in 2016, with specific and more demanding requirements for Uber. This policy is a part of the Chinese approach to the gradual liberalization of the urban passenger transport market. Policymakers should consider ‘fair competition’ as the guiding principle to balance the interests of sharing firms and incumbent service providers, as well as between different sharing firms. The core value of this principle lies in the benefits it provides for consumers and the way it engenders a pro-competitive market environment. The labor protection arrangements for sharing firms’ laborers should be more flexible and diversified. In order to recognize whether an Uber-Driver is an employee or independent contractor, a new standard taking into account a range of factors should be established through collective negotiations between the participants of the sharing economy, and dialogues between members of the judiciary, academics, and the policymakers. Further, consumer protection law and personal data protection provisions should apply when sharing firms misuse their distinctive algorithmic management model to compete unfairly to the detriment of consumers and other users. Ex ante regulatory measures designed to protect the personal data of users should be introduced for deployment in the context of the sharing economy. When enforcing these rules, a balance should be struck ensuring free data flow that is essential to sharing firms’ innovation and competition, and the need to ensure the level of data security required to underpin a well-functioning sharing society.     

From fragile to smart consumers: Shifting paradigm for the digital era

The use of digital technologies, functioning thanks to data processing, has been conquering many sectors of the world economy and it is possible that, in the near future, only a few markets will still be excluded from this industrial revolution. Therefore, even if one chose unreasonably to disregard the many innovations that the digital economy has brought about, its development seems quite inexorable, although it is true that this new stage in human progress raises some concerns. In particular, many worry about the millions of passive and powerless digital consumers who, facing a few huge and influential companies without any education or awareness, could succumb and find themselves poorer, victimized, and manipulated. The paper proposes to react to this state of affairs without further fueling the fear of the digital revolution and without the thought that regulation can be used only as a shield to protect fragile digital consumers. Rather, by taking inspiration from some regulatory actions undertaken by the European Union, the paper bears in mind that regulation can be used as a sword in the hands of consumers to finally assign them a lead role in digital markets. New rules to empower consumers and to make them take autonomous and independent decisions as to the management of their personal data as well as to the merits of digital firms can be envisaged. After all, one of the cultural roots of Western societies is that every individual should be enabled to be faber ipsius fortunae.     

Application of Enhanced Point Estimators to a Sample of In Vivo CT‐derived Facial Soft Tissue Thicknesses

Facial approximations based on facial soft tissue depth measurement tables often utilize the arithmetic mean as a central tendency estimator. Stephan et al. (J Forensic Sci 2013;58:1439) suggest that the shorth and 75‐shormax statistics are better suited to describe the central tendency of non‐normal soft tissue depth data, while also accommodating normal distributions. The shorth, 75‐shormax, arithmetic mean, and other central tendency estimators were evaluated using a CT ‐derived facial soft tissue depth dataset. Differences between arithmetic mean and shorth mean for the tissue depths examined ranged from 0 mm to +2.3 mm (average 0.6 mm). Differences between the arithmetic mean plus one standard deviation (to approximate the same data points covered by the 75‐shormax) and 75‐shormax values ranged from ?0.8 mm to +0.7 mm (average 0.2 mm). The results of this research suggest that few practical differences exist across the central tendency point estimators for the evaluated soft tissue depth dataset.     

Forensic Analysis of Digital Dynamic Signatures: New Methods for Data Treatment and Feature Evaluation

This study explored digital dynamic signatures containing quantifiable dynamic data. The change in data content and nature necessitates the development of new data treatment approaches. A SignPad Omega digitizing tablet was used to assess measurement reproducibility, as well as within‐writer variation and the occurrence of correctly simulated features. Measurement reproducibility was found to be high except for pressure information. Within‐writer variation was found to be higher between days than on a same day. Occurrence of correct simulation was low for features such as signature size, trajectory length, and total signature time. Feature discrimination factors combining within‐writer variability and the occurrence of correctly simulated features were computed and show that signature size, trajectory length, and signature time are the features that perform the best for discriminating genuine from simulated signatures. A final experiment indicates that dynamic information can be used to create connections between simulation cases.     

Using Cluster Analysis and ICP‐MS to Identify Groups of Ecstasy Tablets in Sao Paulo State,Brazil

The variations found in the elemental composition in ecstasy samples result in spectral profiles with useful information for data analysis, and cluster analysis of these profiles can help uncover different categories of the drug. We provide a cluster analysis of ecstasy tablets based on their elemental composition. Twenty‐five elements were determined by ICP‐MS in tablets apprehended by Sao Paulo's State Police, Brazil. We employ the K‐means clustering algorithm along with C4.5 decision tree to help us interpret the clustering results. We found a better number of two clusters within the data, which can refer to the approximated number of sources of the drug which supply the cities of seizures. The C4.5 model was capable of differentiating the ecstasy samples from the two clusters with high prediction accuracy using the leave‐one‐out cross‐validation. The model used only Nd, Ni, and Pb concentration values in the classification of the samples.     

iCLIC Data Mining and Data Sharing workshop: The present and future of data mining and data sharing in the EU

Held at Southampton University's Highfield campus and hosted by iCLIC, an interdisciplinary core on Law, the Internet and Culture, the Data Mining and Data Sharing workshop brought together attendees and speakers from industry, government, academia and a range of disciplines alike. The workshop comprised two sessions, each with a keynote and an associated panel. The first session was chaired by Eleonora Rosati and dealt with copyright and database rights, data mining and data sharing. The second session, chaired by Sophie Stalla-Bourdillon, focussed on data protection, data mining and data sharing. The following report covers both sessions, associated panel discussions and the subsequent question and answer sessions.     

An initial evaluation of the Global Review Form as an approach to measuring individual change

Background: Routine assessment of individual change in forensic mental health services is increasingly recognised as important. However, existing tools have been criticised and their periodic use make them unsuited to directly measure the impact of interventions. This paper describes the initial evaluation of the Global Review Form (GRF) as a framework for measuring change over time. Specifically, measurement properties, feasibility and usefulness in routine practice are examined. Method: 28 male service users in three distinct areas of an adult secure service (low secure, locked rehabilitation and high relational support housing) were rated over a 20-week period by their multidisciplinary teams. Findings: The GRF showed promising construct validity and appropriate stability and sensitivity to change across time. It enabled measurement and understanding of individual change over time. Staff feedback suggested the GRF is a useable and practical outcome measuring tool. Conclusions: The GRF shows promise for use as a routine outcome monitoring tool within forensic mental health services.     

Validating TrueAllele® DNA mixture interpretation

Abstract: DNA mixtures with two or more contributors are a prevalent form of biological evidence. Mixture interpretation is complicated by the possibility of different genotype combinations that can explain the short tandem repeat (STR) data. Current human review simplifies this interpretation by applying thresholds to qualitatively treat STR data peaks as all‐or‐none events and assigning allele pairs equal likelihood. Computer review, however, can work instead with all the quantitative data to preserve more identification information. The present study examined the extent to which quantitative computer interpretation could elicit more identification information than human review from the same adjudicated two‐person mixture data. The base 10 logarithm of a DNA match statistic is a standard information measure that permits such a comparison. On eight mixtures having two unknown contributors, we found that quantitative computer interpretation gave an average information increase of 6.24 log units (min = 2.32, max = 10.49) over qualitative human review. On eight other mixtures with a known victim reference and one unknown contributor, quantitative interpretation averaged a 4.67 log factor increase (min = 1.00, max = 11.31) over qualitative review. This study provides a general treatment of DNA interpretation methods (including mixtures) that encompasses both quantitative and qualitative review. Validation methods are introduced that can assess the efficacy and reproducibility of any DNA interpretation method. An in‐depth case example highlights 10 reasons (at 10 different loci) why quantitative probability modeling preserves more identification information than qualitative threshold methods. The results validate TrueAllele^® DNA mixture interpretation and establish a significant information improvement over human review.