Transfer pricing and multinational financial institutions : the case for replacing arm’s length price with a unitary approach

The international tax system, designed a century ago, has not kept pace with the modern multinational entity rendering it ineffective in taxing many modern businesses according to economic activity. One of those modern multinational entities is the multinational financial institution (MNFI). The recent global financial crisis provides a particularly relevant and significant example of the failure of the current system on a global scale. The modern MNFI is increasingly undertaking more globalised and complex trading operations. A primary reason for the globalisation of financial institutions is that they typically ‘follow-the-customer’ into jurisdictions where international capital and international investors are required. The International Monetary Fund (IMF) recently reported that from 1995-2009, foreign bank presence in developing countries grew by 122 per cent. The same study indicates that foreign banks have a 20 per cent market share in OECD countries and 50 per cent in emerging markets and developing countries. Hence, most significant is that fact that MNFIs are increasingly undertaking an intermediary role in developing economies where they are financing core business activities such as mining and tourism. IMF analysis also suggests that in the future, foreign bank expansion will be greatest in emerging economies. The difficulties for developing countries in applying current international tax rules, especially the current traditional transfer pricing regime, are particularly acute in relation to MNFIs, which are the biggest users of tax havens and offshore finance. This paper investigates whether a unitary taxation approach which reflects economic reality would more easily and effectively ensure that the profits of MNFIs are taxed in the jurisdictions which give rise to those profits. It has previously been argued that the uniqueness of MNFIs results in a failure of the current system to accurately allocate profits and that unitary tax as an alternative could provide a sounder allocation model for international tax purposes. This paper goes a step further, and examines the practicalities of the implementation of unitary taxation for MNFIs in terms of the key components of such a regime, along with their their implications. This paper adopts a two-step approach in considering the implications of unitary taxation as a means of improved corporate tax coordination which requires international acceptance and agreement. First, the definitional issues of the unitary MNFI are examined and second, an appropriate allocation formula for this sector is investigated. To achieve this, the paper asks first, how the financial sector should be defined for the purposes of unitary taxation and what should constitute a unitary business for that sector and second, what is the ‘best practice’ model of an allocation formula for the purposes of the apportionment of the profits of the unitary business of a financial institution.

Why disaster survivors speak to reporters

Practice-led journalism research techniques were used in this study to produce a ‘first draft of history’ recording the human experience of survivors and rescuers during the January 2011 flash flood disaster in Toowoomba and the Lockyer Valley in Queensland, Australia. The study aimed to discover what can be learnt from engaging in journalistic reporting of natural disasters, using journalism as both a creative practice and a research methodology. (Lindgren and Phillips, 2011, 75). The willingness of a very high proportion of severely traumatised flood survivors to participate in the flood research was unexpected but made it possible to document a relatively unstudied question within the literature about journalism and trauma – when and why disaster survivors will want to speak to journalists. The study reports six categories of reasons interviewees gave for their willingness to speak to the media: for their own personal recovery; their desire for the public to know what had happened; that lessons need to be learned from the disaster; their sense of duty to make sure warning systems and disaster responses are improved in future; the financial disinterest of reporters in listening to survivors; and the timing of the request for an interview. In addition, traumatised flood survivors found both the opportunity to speak to the media and the journalistic outputs of the research cathartic in their recovery.

Why not the best schools? The Australia Report

"The Australia Report is part of a set of six country reports that support Why not the best schools? It contains seven case studies of successful schools in Australia and examines the reasons for their success. Through interviews with principals, other school leaders and analysis of school reports, the reports examine how these schools achieved transformation and success by actively developing and building strength in four kinds of capital: intellectual, social, financial and spiritual ? and aligning them to their mission through outstanding governance. Why Not the Best Schools?: The Australia Report is part of a set of six country reports that support Why Not the Best Schools? by Brian Caldwell and Jessica Harris (ACER Press 2008). Why Not the Best Schools? draws on the findings of the International Project to Frame the Transformation of Schools conducted in Australia, China, England, Finland."--Libraries Australia

The impact of OCR accuracy on automated cancer classification of pathology reports

Objective To evaluate the effects of Optical Character Recognition (OCR) on the automatic cancer classification of pathology reports. Method Scanned images of pathology reports were converted to electronic free-text using a commercial OCR system. A state-of-the-art cancer classification system, the Medical Text Extraction (MEDTEX) system, was used to automatically classify the OCR reports. Classifications produced by MEDTEX on the OCR versions of the reports were compared with the classification from a human amended version of the OCR reports. Results The employed OCR system was found to recognise scanned pathology reports with up to 99.12% character accuracy and up to 98.95% word accuracy. Errors in the OCR processing were found to minimally impact on the automatic classification of scanned pathology reports into notifiable groups. However, the impact of OCR errors is not negligible when considering the extraction of cancer notification items, such as primary site, histological type, etc. Conclusions The automatic cancer classification system used in this work, MEDTEX, has proven to be robust to errors produced by the acquisition of freetext pathology reports from scanned images through OCR software. However, issues emerge when considering the extraction of cancer notification items.

Classification of pathology reports for cancer registry notifications

Objective: To develop a system for the automatic classification of pathology reports for Cancer Registry notifications. Method: A two pass approach is proposed to classify whether pathology reports are cancer notifiable or not. The first pass queries pathology HL7 messages for known report types that are received by the Queensland Cancer Registry (QCR), while the second pass aims to analyse the free text reports and identify those that are cancer notifiable. Cancer Registry business rules, natural language processing and symbolic reasoning using the SNOMED CT ontology were adopted in the system. Results: The system was developed on a corpus of 500 histology and cytology reports (with 47% notifiable reports) and evaluated on an independent set of 479 reports (with 52% notifiable reports). Results show that the system can reliably classify cancer notifiable reports with a sensitivity, specificity, and positive predicted value (PPV) of 0.99, 0.95, and 0.95, respectively for the development set, and 0.98, 0.96, and 0.96 for the evaluation set. High sensitivity can be achieved at a slight expense in specificity and PPV. Conclusion: The system demonstrates how medical free-text processing enables the classification of cancer notifiable pathology reports with high reliability for potential use by Cancer Registries and pathology laboratories.

Clinician-driven automated classification of limb fractures from free-text radiology reports

The aim of this research is to report initial experimental results and evaluation of a clinician-driven automated method that can address the issue of misdiagnosis from unstructured radiology reports. Timely diagnosis and reporting of patient symptoms in hospital emergency departments (ED) is a critical component of health services delivery. However, due to disperse information resources and vast amounts of manual processing of unstructured information, a point-of-care accurate diagnosis is often difficult. A rule-based method that considers the occurrence of clinician specified keywords related to radiological findings was developed to identify limb abnormalities, such as fractures. A dataset containing 99 narrative reports of radiological findings was sourced from a tertiary hospital. The rule-based method achieved an F-measure of 0.80 and an accuracy of 0.80. While our method achieves promising performance, a number of avenues for improvement were identified using advanced natural language processing (NLP) techniques.

Automatic classification of free-text radiology reports to identify limb fractures using machine learning and the SNOMED CT ontology

Objective To develop and evaluate machine learning techniques that identify limb fractures and other abnormalities (e.g. dislocations) from radiology reports. Materials and Methods 99 free-text reports of limb radiology examinations were acquired from an Australian public hospital. Two clinicians were employed to identify fractures and abnormalities from the reports; a third senior clinician resolved disagreements. These assessors found that, of the 99 reports, 48 referred to fractures or abnormalities of limb structures. Automated methods were then used to extract features from these reports that could be useful for their automatic classification. The Naive Bayes classification algorithm and two implementations of the support vector machine algorithm were formally evaluated using cross-fold validation over the 99 reports. Result Results show that the Naive Bayes classifier accurately identifies fractures and other abnormalities from the radiology reports. These results were achieved when extracting stemmed token bigram and negation features, as well as using these features in combination with SNOMED CT concepts related to abnormalities and disorders. The latter feature has not been used in previous works that attempted classifying free-text radiology reports. Discussion Automated classification methods have proven effective at identifying fractures and other abnormalities from radiology reports (F-Measure up to 92.31%). Key to the success of these techniques are features such as stemmed token bigrams, negations, and SNOMED CT concepts associated with morphologic abnormalities and disorders. Conclusion This investigation shows early promising results and future work will further validate and strengthen the proposed approaches.

ShARe/CLEF eHealth Evaluation Lab 2013, Task 3: Information retrieval to address patients' questions when reading clinical reports

This paper presents the results of task 3 of the ShARe/CLEF eHealth Evaluation Lab 2013. This evaluation lab focuses on improving access to medical information on the web. The task objective was to investigate the effect of using additional information such as the discharge summaries and external resources such as medical ontologies on the IR effectiveness. The participants were allowed to submit up to seven runs, one mandatory run using no additional information or external resources, and three each using or not using discharge summaries.

Automated classification of limb fractures from free-text radiology reports using a clinician-informed gazetteer methodology

Background Timely diagnosis and reporting of patient symptoms in hospital emergency departments (ED) is a critical component of health services delivery. However, due to dispersed information resources and a vast amount of manual processing of unstructured information, accurate point-of-care diagnosis is often difficult. Aims The aim of this research is to report initial experimental evaluation of a clinician-informed automated method for the issue of initial misdiagnoses associated with delayed receipt of unstructured radiology reports. Method A method was developed that resembles clinical reasoning for identifying limb abnormalities. The method consists of a gazetteer of keywords related to radiological findings; the method classifies an X-ray report as abnormal if it contains evidence contained in the gazetteer. A set of 99 narrative reports of radiological findings was sourced from a tertiary hospital. Reports were manually assessed by two clinicians and discrepancies were validated by a third expert ED clinician; the final manual classification generated by the expert ED clinician was used as ground truth to empirically evaluate the approach. Results The automated method that attempts to individuate limb abnormalities by searching for keywords expressed by clinicians achieved an F-measure of 0.80 and an accuracy of 0.80. Conclusion While the automated clinician-driven method achieved promising performances, a number of avenues for improvement were identified using advanced natural language processing (NLP) and machine learning techniques.

Corporate sustainability reporting of major commercial banks in line with GRI : Bangladesh evidence

Purpose – This paper aims to examine the tendencies of sustainability reporting by major commercial banks in Bangladesh in comparison with global sustainability reporting indicators outlined in the GRI framework together with banks' predilection toward reporting 16 GRI financial service sector (FSS) specific performance indicators. Design/methodology/approach – Based on the GRI G3 guidelines, the paper investigated banks' reporting in five broad areas of sustainability, such as environment, labour practices and decent works, product responsibility, human rights and society. The 2008/2009 annual reports of 12 major commercial banks listed on Dhaka stock exchange were analysed and coded using a content-based technique. Findings – The results show that information on society is addressed most extensively with regard to extent of reporting. This is followed by the disclosures prepared on decent works and labour practices and environmental issues. Furthermore, the disclosures of product responsibility information and the information for human rights are rather scarce in banks' reporting; on the subject of FSS-specific disclosures, only seven items out of 16 are disclosed by all sample banks. Research limitations/implications – The findings of the study indicate that Bangladeshi commercial banks' social disclosures could develop in this style to become more holistic and over time (in association with the country's central bank involvement) to resemble a type of structured reporting to the point where they are properly labelled per se. Originality/value – The study contributes to the social disclosure literature, in particular in a developing countries banking sector context, seeing as it disseminates evidence of the standing on social disclosures practices at the level of GRI with developing countries' banks data.

Gambling on gambling in Baccarat : financial implications of raising bet limits and table differentials

The house advantage for Baccarat is known, hence the theoretical win can be determined. What is impractical to theoretically determine is the frequency and financial implications of extreme events, for example, prolonged winning streaks coupled with various betting patterns. The simulation herein provides such granularity. We explore the effect of following the „hot hand‟, that is, rapidly escalating bets when players are on a winning streak. To minimize their exposure, casino management sets a table bet maximum as well as a table differential. These figures can and do serve as a means to differentiate one casino from another. As the allowable bet maximum increases so does the total amount bet, which increases the theoretical winnings, thus suggesting that a high bet limit and differential is beneficial for the house. However, the greater are these amounts, the greater the number of shoes that end with players losing relative to a constant betting scenario (the number of times a player wins at all can drop from ~47% of the time to less than a quarter); but there will, on occasion, be more extreme payouts to players. This simulation is therefore intended to help casino managers set betting limits that maximize total winnings while bearing in mind both the likelihood and magnitude of negative outcomes to the casino.

Validity of family child care providers' proxy reports on children's physical activity

Background Interventions to promote physical activity (PA) in children attending family child care homes (FCCHs) require valid, yet practical, measurement tools. The aim of this study was to assess the validity of two proxy report instruments designed to measure PA in children attending FCCHs. Methods A sample of 37 FCCH providers completed the Burdette parent proxy report, modified for the family child care setting for 107 children 3.4±1.2 years of age. A second sample of 42 FCCH providers completed the Harro parent and teacher proxy report, modified for the family child care setting, for 131 children 3.8±1.3 years of age. Both proxy reports were assessed for validity using accelerometry as a criterion measure. Results Significant positive correlations were observed between provider-reported PA scores from the modified Burdette proxy report and objectively measured total PA (r=0.30; p<0.01) and moderate-to-vigorous PA (MVPA; r=0.34; p<0.01). Across levels of provider-reported PA, both total PA and MVPA increased significantly in a linear dose-response fashion. The modified Harro proxy report was not associated with objectively measured PA. Conclusion Proxy PA reports completed by family child care providers may be a valid assessment option in studies where more burdensome objective measures are not feasible.

Re-examining the financial returns from New Zealand's SOE sector : re-examining privatisation

This paper considers the potential for profit within state-owned enterprises [SOEs] as part of the privatisation debate, through an examination of New Zealand’s SOE sector from 2006 to 2010, extending and comparing findings of an earlier study from 2001 to 2005.