Who claims gifts as a tax deduction? An examination of tax deductible gift statistics

Many donors, particularly those contemplating a substantial donation, consider whether their donation will be deductible from their taxable income. This motivation is not lost on fundraisers who conduct appeals before the end of the taxation year to capitalise on such desires. The motivation is also not lost on Treasury analysts who perceive the tax deduction as “lost” revenue and wonder if the loss is “efficient” in economic terms. Would it be more efficient for the government to give grants to deserving organisations, rather than permitting donor directed gifts? Better still, what about contracts that lock in the use of the money for a government priority? What place does tax deduction play in influencing a donor to give? Does the size of the gift bear any relationship to the size of the tax deduction? Could an increased level of donations take up an increasing shortfall in government welfare and community infrastructure spending? Despite these questions being asked regularly, little has been rigorously established about the effect of taxation deductions on a donor’s gifts.

Ideas as "possessitives" : claims and counter claims in a playground dispute

In the shared space of a school playground, matters of ownership and possession are seriously attended to by children in their everyday encounters with others. The study reported here uses conversation analysis and an ethnomethodological approach to investigate a dispute between two children, aged four to six years, as they decide whose idea for the game will be used. Drawing on Sacks’ (1995a) notion of possession, and Sharrock’s (1974) paper “on owning knowledge”, this paper demonstrates how children draw on the phrase, “that’s my idea”, to claim ownership. Analysis of their video-recorded interaction shows how the children used physical actions, gaze and talk to invoke their own intellectual property as a commodity in the dispute. Whilst invoking ownership, analysis highlights that entitlement over people, objects and the decisions of the shared interactional space did not occur unproblematically. Material objects were used to counter claims to ideas, and it was the uptake of the game and the use of play objects by others that led to whether the idea of game category was upheld. This analysis enables adults a glimpse into the complex social organisation of children’s peer group.

Agreement between self-reported use of in vitro fertilization or ovulation induction, and medical insurance claims in Australian women aged 28–36 years

STUDY QUESTION: What is the self-reported use of in vitro fertilization (IVF) and ovulation induction (OI) in comparison with insurance claims by Australian women aged 28–36 years? SUMMARY ANSWER: The self-reported use of IVF is quite likely to be valid; however, the use of OI is less well reported. WHAT IS KNOWN AND WHAT THIS PAPER ADDS: Population-based research often relies on the self-reported use of IVF and OI because access to medical records can be difficult and the data need to include sufficient personal identifying information for linkage to other data sources. There have been few attempts to explore the reliability of the self-reported use of IVF and OI using the linkage to medical insurance claims for either treatment. STUDY DESIGN: This prospective, population-based, longitudinal study included the cohort of women born during 1973–1978 and participating in the Australian Longitudinal Study on Women's Health (ALSWH) (n = 14247). From 1996 to 2009, participants were surveyed up to five times. PARTICIPANTS AND SETTING: Participants self-reported their use of IVF or OI in two mailed surveys when aged 28–33 and 31–36 years (n = 7280), respectively. This study links self-report survey responses and claims for treatment or medication from the universal national health insurance scheme (i.e. Medicare Australia). MAIN RESULTS AND THE ROLE OF CHANCE: Comparisons between self-reports and claims data were undertaken for all women consenting to the linkage (n = 3375). The self-reported use of IVF was compared with claims for OI for IVF (Kappa, K = 0.83), oocyte collection (K = 0.82), sperm preparation (K = 0.83), intracytoplasmic sperm injection (K = 0.40), fresh embryo transfers (K = 0.82), frozen embryo transfers (K = 0.64) and OI for IVF medication (K = 0.17). The self-reported use of OI was compared with ovulation monitoring (K = 0.52) and OI medication (K = 0.71). BIAS, CONFOUNDING AND OTHER REASONS FOR CAUTION: There is a possibility of selection bias due to the inclusion criteria for participants in this study: (1) completion of the last two surveys in a series of five and (2) consent to the linkage of their responses with Medicare data. GENERALIZABILITY TO OTHER POPULATIONS: The results are relevant to questionnaire-based research studies with infertile women in developed countries. STUDY FUNDING/COMPETING INTEREST(S): ALSWH is funded by the Australian Government Department of Health and Ageing. This research is funded by a National Health and Medical Research Council Centre of Research Excellence grant.

Data mining traditional Chinese medicine (TCM) lessons learnt from mining in law and allopathic medicine

Key decisions at the collection, pre-processing, transformation, mining and interpretation phase of any knowledge discovery from database (KDD) process depend heavily on assumptions and theorectical perspectives relating to the type of task to be performed and characteristics of data sourced. In this article, we compare and contrast theoretical perspectives and assumptions taken in data mining exercises in the legal domain with those adopted in data mining in TCM and allopathic medicine. The juxtaposition results in insights for the application of KDD for Traditional Chinese Medicine.

Acquisition modelling for heavy engineering assets in mining industry

Each year, organizations in Australian mining industry (asset intensive industry) spend substantial amount of capital (A$86 billion in 2009-10) (Statistics, 2011) in acquiring engineering assets. Engineering assets are put to use in operations to generate value. Different functions (departments) of an organization have different expectations and requirements from each of the engineering asset e.g. return on investment, reliability, efficiency, maintainability, low cost of running the asset, low or nil environmental impact and easy of disposal, potential salvage value etc. Assets are acquired from suppliers or built by service providers and or internally. The process of acquiring assets is supported by procurement function. One of the most costly mistakes that organizations can make is acquiring the inappropriate or non-conforming assets that do not fit the purpose. The root cause of acquiring non confirming assets belongs to incorrect acquisition decision and the process of making decisions. It is very important that an asset acquisition decision is based on inputs and multi-criteria of each function within the organization which has direct or indirect impact on the acquisition, utilization, maintenance and disposal of the asset. Literature review shows that currently there is no comprehensive process framework and tool available to evaluate the inclusiveness and breadth of asset acquisition decisions that are taken in the Mining Organizations. This thesis discusses various such criteria and inputs that need to be considered and evaluated from various functions within the organization while making the asset acquisition decision. Criteria from functions such as finance, production, maintenance, logistics, procurement, asset management, environment health and safety, material management, training and development etc. need to be considered to make an effective and coherent asset acquisition decision. The thesis also discusses a tool that is developed to be used in the multi-criteria and cross functional acquisition decision making. The development of multi-criteria and cross functional inputs based decision framework and tool which utilizes that framework to formulate cross functional and integrated asset acquisition decisions are the contribution of this research.

Ten truths about Australia's rush to mine and the mining workforce

The sky is falling because the much-vaunted mining ‘boom’ is heading for ‘bust’. The fear-mongering by politicians, the industry and the media has begun in earnest. On ABC TV's 7:30 program on 22 August 2012, Federal Opposition Leader Tony Abbott blamed the Minerals Resource Rent Tax and the Carbon Tax for making ‘a bad investment environment much, much worse’ for the mining industry. The following day, Australia's Resources and Energy Minister Martin Ferguson told us on ABC radio that ‘the resources boom is over’. This must be true because, remember, we were warned to ‘Get ready for the end of the boom’ (David Uren, Economics Editor for The Australian 19 May 2012) due to the ‘Australian resource boom losing steam’ (David Winning & Robb M. Stewart, Wall Street Journal 21 August 2012). Besides, there is ‘unarguable evidence’ that Australia's production costs are ‘too expensive’ and ‘too uncompetitive’: mining magnate Gina Rinehart said so in a YouTube video placed on the Sydney Mining Club's website on 5 September 2012. Can this really be so? What is happening to the mining boom and to the people who depend upon it?

Crime talk, FIFO workers and cultural conflict on the mining boom frontier

Australia is experiencing an unprecedented expansion in mining due to intense demand from Asian economies thirsty for Australia’s non-renewable resources, with over $260 billion worth of capital investment currently in the pipeline (BREE 10). The scale of the present boom coupled with the longer term intensification of competitiveness in the global resources sector is changing the very nature of mining operations in Australia. Of particular note is the increasingly heavy reliance on a non-resident workforce, currently sourced from within Australia but with some recent proposals for projects to draw on overseas guest workers. This is no longer confined, as it once was, to remote, short term projects or to exploration and construction phases of operations, but is emerging as the preferred industry norm. Depending upon project location, workers may either fly-in, fly-out (FIFO) or drive-in, drive-out (DIDO), the critical point being that these operations are frequently undertaken in or near established communities. Drawing primarily on original fieldwork in one of Australia’s mining regions at the forefront of the boom, this paper explores some of the local impacts of new mining regimes, in particular their tendency to undermine collective solidarities, promote social division and fan cultural conflict.

Fast and robust stereo matching algorithms for mining automation

The mining environment, being complex, irregular, and time-varying, presents a challenging prospect for stereo vision. For this application, speed, reliability, and the ability to produce a dense depth map are of foremost importance. This paper evaluates a number of matching techniques for possible use in a stereo vision sensor for mining automation applications. Area-based techniques have been investigated because they have the potential to yield dense maps, are amenable to fast hardware implementation, and are suited to textured scenes. In addition, two nonparametric transforms, namely, rank and census, have been investigated. Matching algorithms using these transforms were found to have a number of clear advantages, including reliability in the presence of radiometric distortion, low computational complexity, and amenability to hardware implementation.

Fast and robust stereo matching algorithms for mining automation

The mining environment, being complex, irregular and time varying, presents a challenging prospect for stereo vision. The objective is to produce a stereo vision sensor suited to close-range scenes consisting primarily of rocks. This sensor should be able to produce a dense depth map within real-time constraints. Speed and robustness are of foremost importance for this investigation. A number of area based matching metrics have been implemented, including the SAD, SSD, NCC, and their zero-meaned versions. The NCC and the zero meaned SAD and SSD were found to produce the disparity maps with the highest proportion of valid matches. The plain SAD and SSD were the least computationally expensive, due to all their operations taking place in integer arithmetic, however, they were extremely sensitive to radiometric distortion. Non-parametric techniques for matching, in particular, the rank and the census transform, have also been investigated. The rank and census transforms were found to be robust with respect to radiometric distortion, as well as being able to produce disparity maps with a high proportion of valid matches. An additional advantage of both the rank and the census transform is their amenability to fast hardware implementation.

Suitability of non-parametric stereo matching algorithms for mining automation

The mining environment, being complex, irregular and time varying, presents a challenging prospect for stereo vision. For this application, speed, reliability, and the ability to produce a dense depth map are of foremost importance. This paper assesses the suitability of a number of matching techniques for use in a stereo vision sensor for close range scenes consisting primarily of rocks. These include traditional area-based matching metrics, and non-parametric transforms, in particular, the rank and census transforms. Experimental results show that the rank and census transforms exhibit a number of clear advantages over area-based matching metrics, including their low computational complexity, and robustness to certain types of distortion.

Fast and robust stereo matching algorithms for mining automation

The mining environment, being complex, irregular and time varying, presents a challenging prospect for stereo vision. For this application, speed, reliability, and the ability to produce a dense depth map are of foremost importance. This paper evaluates a number of matching techniques for possible use in a stereo vision sensor for mining automation applications. Area-based techniques have been investigated because they have the potential to yield dense maps, are amenable to fast hardware implementation, and are suited to textured scenes. In addition, two non-parametric transforms, namely, the rank and census, have been investigated. Matching algorithms using these transforms were found to have a number of clear advantages, including reliability in the presence of radiometric distortion, low computational complexity, and amenability to hardware implementation.

Challenging Mining Workforce Practices : Implications for Frontline Rural Communities

Global demand for minerals and energy products has fuelled Australia’s recent ‘resources boom’ and led to the rapid expansion of mining projects not solely in remote regions but increasingly in long-settled traditionally agriculture-dependent rural areas. Not only has this activity radically changed the economic geography of the nation but a fundamental shift has also occurred to accommodate the acceleration in industry labour demands. In particular, the rush to mine has seen the entrenchment of workforce arrangements largely dependent on fly-in, fly-out (FIFO) and drive–in, drive–out (DIDO) workers. This form of employment has been highly contentious in rural communities at the frontline of resource sector activities. In the context of structural sweeping changes, the selection of study locations informed by a range of indices of violence. Serendipitously we carried out fieldwork in communities undergoing rapid change as a result of expanding resource sector activities. The presence of large numbers of non-resident FIFO and DIDO workers was transforming these frontline communities. This chapter highlights some implications of these changes, drawing upon one particular location, which historically depended on agriculture but has undergone redefinition through mining.

Diversification for sustainable development in rural and regional Australia : how local community leaders conceptualise the impacts and opportunities from agriculture, tourism and mining

Although the multiple economic, environmental and social challenges threatening the viability of rural and regional communities in Australia are well-known, little research has explored how community leaders conceptualise the impact and opportunities associated with economic diversification from agriculture into alternative industries, such as tourism and mining. This qualitative research, utilising the Darling Downs in Queensland as a case study, documents how 28 local community leaders have experienced this economic diversification process. The findings reveal that local community leaders have a deep understanding about the opportunities and challenges presented by diversification, articulating a clear vision about how to achieve the best possible future for their region. Despite excitement about growth, there were concerns about preserving heritage, the increased pressure on local infrastructure and an ageing population. By documenting local leader’s insights, these findings may help inform planning for rural and regional communities and facilitate management of the exciting yet challenging process of growth and diversification

Spinning a sustainable yarn: assessing the claims of Australian companies’ eco-initiatives

In Australia, few fashion brands have intervened in the design of their products or the systems around their product to tackle environmental pollution and waste. Instead, support of charities (whether social or environmental) has become conflated with sustainability in the eyes of the public.However, three established Australian brands recently put forward initiatives which explicitly tackle the pre-consumer or post-consumer waste associated with their products. In 2011, Billabong, one of the largest surfwear companies in the world, developed a collection of board shorts made from recycled bottles that are also recyclable at end of life. The initiative has been promoted in partnership with Bob Marley’s son Rohan Marley, and the graphics of the board shorts reference the Rastafarian colours and make use of Marley’s song lyrics. In this way, the company has tapped into an aspect of surf culture linked to environmental activism, in which the natural world is venerated. Two mid-market initiatives, by Metalicus and Country Road, each have a social outcome that arguably aligns to the values of their middle-class consumer base. Metalicus is spear-heading a campaign for Australian garment manufacturers to donate their pre consumer waste – fabric off-cuts – to charity Open Family Australia to be manufactured into quilts for the homeless. Country Road has partnered with the Australian Red Cross to implement a recycling scheme in which consumers donate their old Country Road garments in exchange for a Country Road gift voucher. Both strategies, while tackling waste, tell an altruistic story in which the disadvantaged can benefit from the consumption habits of the middle-class. To varying degrees, the initiative chosen by each company feeds into the stories they tell about themselves and about the consumers who purchase their clothing. However, how can we assess the impact of these schemes on waste management in real terms, or indeed the worth of each scheme in the wider context of the fashion system? This paper will assess the claims made by the companies and analyse their efficacy, suggesting that a more nuanced assessment of green claims is required, in which ‘green’ comes in many tonal variations.

Retrieving information from microblog using pattern mining and relevance feedback

Retrieving information from Twitter is always challenging due to its large volume, inconsistent writing and noise. Most existing information retrieval (IR) and text mining methods focus on term-based approach, but suffers from the problems of terms variation such as polysemy and synonymy. This problem deteriorates when such methods are applied on Twitter due to the length limit. Over the years, people have held the hypothesis that pattern-based methods should perform better than term-based methods as it provides more context, but limited studies have been conducted to support such hypothesis especially in Twitter. This paper presents an innovative framework to address the issue of performing IR in microblog. The proposed framework discover patterns in tweets as higher level feature to assign weight for low-level features (i.e. terms) based on their distributions in higher level features. We present the experiment results based on TREC11 microblog dataset and shows that our proposed approach significantly outperforms term-based methods Okapi BM25, TF-IDF and pattern based methods, using precision, recall and F measures.