The myths big media peddle to demand deregulation

This article argues that big media in Australia promote three myths about rural and regional news in Australia as part of their case to deregulate the industry. These myths are that geography no longer matters in local news; that big media are the only ones who can save regional news; and that people in regional Australia can access less news that their city counterparts.

Leaning too far? PISA, policy and Australia's ‘top five’ ambitions

 Australia has declared its ambition to be within the ‘top five’ in the Programme for International Student Assessment (PISA) by 2025. So serious is it about this ambition, that the Australian Government has incorporated it into the Australian Education Act, 2013. Given this focus on PISA results and rankings, we go beyond average scores to take a close look at Australia’s performance in PISA, examining rankings by different geographical units, by item content and by test completion. Based on this analysis and using data from interviews with measurement and policy experts, we show how uninformative and even misleading the ‘average performance scores’, on which the rankings are based, can be. We explore how a more nuanced understanding would point to quite different policy actions. After considering the PISA data and Australia’s ‘top five’ ambition closely, we argue that neither the rankings nor such ambitions should be given much credence.

Congestion pricing and active transport - evidence from five opportunities for natural experiment

Congestion pricing schemes have been implemented in cities worldwide as a means of addressing externalities associated with inefficient price signals in transport systems. Limited evidence exists however on the secondary impacts of these schemes, which may include both environmental and health benefits associated with a resultant reduction in motor vehicle usage. There is increasing recognition that transport behaviours may play a role as opportunistic population level targets to reduce physical inactivity. Yet limited evidence currently exists on the effectiveness of transport interventions, such as congestion pricing schemes, for improving physical activity levels.This study aims to examine the physical activity effects of congestion pricing, with the health benefits of physical activity well established. Congestion pricing schemes implemented internationally were considered as 'natural experiments' and evidence of modal shift from vehicle to active forms of transport or physical activity effect was reviewed. Twelve studies were included from a search of peer-reviewed and 'grey' literature, with overall evidence for a physical activity or modal shift effect considered weak. The quality of the available evidence was also considered to be low.This is not to say that congestion pricing schemes may not have important secondary physical activity related health benefits. Instead, this review highlights the paucity of evidence that has been collected from real-world implementation of congestion pricing schemes. Given the growing recognition of the importance of distal mediators and determinants of health and the need for an 'all-of-government' approach more and better quality evidence of effectiveness of transport interventions for a broad range of outcomes, including health, is required. Significant barriers to the collection of such evidence exist, with strategies for overcoming some of these barriers identified. Only with a better understanding of the full range of potential health impacts can transport policy be fully utilised as a tool for population health.

Corporate social responsibility programs of big food in Australia: a content analysis of industry documents

OBJECTIVE: To examine Corporate Social Responsibility (CSR) tactics by identifying the key characteristics of CSR strategies as described in the corporate documents of selected 'Big Food' companies. METHODS: A mixed methods content analysis was used to analyse the information contained on Australian Big Food company websites. Data sources included company CSR reports and web-based content that related to CSR initiatives employed in Australia. RESULTS: A total of 256 CSR activities were identified across six organisations. Of these, the majority related to the categories of environment (30.5%), responsibility to consumers (25.0%) or community (19.5%). CONCLUSIONS: Big Food companies appear to be using CSR activities to: 1) build brand image through initiatives associated with the environment and responsibility to consumers; 2) target parents and children through community activities; and 3) align themselves with respected organisations and events in an effort to transfer their positive image attributes to their own brands. IMPLICATIONS: Results highlight the type of CSR strategies Big Food companies are employing. These findings serve as a guide to mapping and monitoring CSR as a specific form of marketing.

Investor protection, firm informational problems, big N auditors, and cost of debt around the world

This paper examines the effects of investor protection, firm informational problems (proxied by firm size, firm age, and the number of analysts following), and Big N auditors on firms' cost of debt around the world. Using data from 1994 to 2006 and over 90,000 firm-year observations, we find that the cost of debt is lower when firms are audited by Big N auditors, especially in countries with strong investor protection. Second, we find that firms with more informational problems (i.e., higher information asymmetry problems) benefit more from Big N auditors in terms of lower cost of debt only in countries with stronger investor protection.

A secure cloud computing based framework for big data information management of smart grid

Smart grid is a technological innovation that improves efficiency, reliability, economics, and sustainability of electricity services. It plays a crucial role in modern energy infrastructure. The main challenges of smart grids, however, are how to manage different types of front-end intelligent devices such as power assets and smart meters efficiently; and how to process a huge amount of data received from these devices. Cloud computing, a technology that provides computational resources on demands, is a good candidate to address these challenges since it has several good properties such as energy saving, cost saving, agility, scalability, and flexibility. In this paper, we propose a secure cloud computing based framework for big data information management in smart grids, which we call 'Smart-Frame.' The main idea of our framework is to build a hierarchical structure of cloud computing centers to provide different types of computing services for information management and big data analysis. In addition to this structural framework, we present a security solution based on identity-based encryption, signature and proxy re-encryption to address critical security issues of the proposed framework.

Typology of alcohol consumers in five Australian nighttime entertainment districts

INTRODUCTION AND AIMS: Understanding how types of alcohol consumers differ is important for public policy targeted at reducing adverse events. The aims of the present study were to identify typologies of alcohol consumers in Australian nighttime entertainment districts based on risk factors for harm and to examine variation between the identified groups in drinking setting and harms. DESIGN AND METHODS: Street-intercept surveys were conducted with 5556 alcohol consumers in and around licensed venues in five Australian cities between November 2011 and June 2012. Latent class analysis identified groups based on age and sex, and blood alcohol concentration, pre-drinking, energy drink use and illicit drug use during that night. RESULTS: Four classes were identified: general patron group (33%), young pre-drinker group (27%), intoxicated male pre-drinker group (31%) and intoxicated illicit drug male group (9%). The proportion of the general patron group interviewed decreased over the night, while the other groups increased (particularly in regional cities). As compared with the general patron group, the remaining three groups reported increased odds of being involved in aggression and any alcohol-related injuries in the past 3 months, with highest rates of harm amongst the intoxicated illicit drug male group. DISCUSSION AND CONCLUSIONS: Alcohol consumers in nighttime entertainment districts are not a homogeneous group. One-third have a low likelihood of risky consumption practices; however, representation of this consumer class diminishes throughout the night. Elevated harms amongst groups characterised by certain risk factors (e.g. pre-drinking and illicit drug use) emphasise the importance of addressing these behaviours in public policy.

Aggregation on the fly: Reducing traffic for big data in the cloud

As a leading framework for processing and analyzing big data, MapReduce is leveraged by many enterprises to parallelize their data processing on distributed computing systems. Unfortunately, the all-to-all data forwarding from map tasks to reduce tasks in the traditional MapReduce framework would generate a large amount of network traffic. The fact that the intermediate data generated by map tasks can be combined with significant traffic reduction in many applications motivates us to propose a data aggregation scheme for MapReduce jobs in cloud. Specifically, we design an aggregation architecture under the existing MapReduce framework with the objective of minimizing the data traffic during the shuffle phase, in which aggregators can reside anywhere in the cloud. Some experimental results also show that our proposal outperforms existing work by reducing the network traffic significantly.

‘It should be a big responsibility’: Separated low-income mothers’ evaluation of child support arrangements and the conduct of fathers

The Australian Child Support Scheme was established as a means of ensuring adequate financial support for children of separated parents. However, within the financial transfer of child support exist notions of ‘trust’ and ‘fairness’ based on parents navigating their changed relationship post-separation. Previous research has explored the assessment and outcomes of child support for both payee and payer parents, however little attention has been given to how women evaluate the assessment and outcomes of child support. As such, this research aimed to explore payee mothers’ evaluation of their child support experiences based on the value of their child support assessment and the extent to which these payments were received. Following the methods of constructivist grounded theory, in-depth interviews were conducted with 20 low-income single mothers. Analysis revealed that payee mothers evaluated child support based on the moral assumptions and the rationalities they perceived were underlying payer fathers’ child support compliance. While payee mothers desired arrangements that reflected joint parental financial responsibility, in reality many experienced problematic child support payments, which may ultimately undermine payee parents’ confidence in the Child Support Scheme.

A general communication cost optimization framework for big data stream processing in geo-distributed data centers

With the explosion of big data, processing large numbers of continuous data streams, i.e., big data stream processing (BDSP), has become a crucial requirement for many scientific and industrial applications in recent years. By offering a pool of computation, communication and storage resources, public clouds, like Amazon's EC2, are undoubtedly the most efficient platforms to meet the ever-growing needs of BDSP. Public cloud service providers usually operate a number of geo-distributed datacenters across the globe. Different datacenter pairs are with different inter-datacenter network costs charged by Internet Service Providers (ISPs). While, inter-datacenter traffic in BDSP constitutes a large portion of a cloud provider's traffic demand over the Internet and incurs substantial communication cost, which may even become the dominant operational expenditure factor. As the datacenter resources are provided in a virtualized way, the virtual machines (VMs) for stream processing tasks can be freely deployed onto any datacenters, provided that the Service Level Agreement (SLA, e.g., quality-of-information) is obeyed. This raises the opportunity, but also a challenge, to explore the inter-datacenter network cost diversities to optimize both VM placement and load balancing towards network cost minimization with guaranteed SLA. In this paper, we first propose a general modeling framework that describes all representative inter-task relationship semantics in BDSP. Based on our novel framework, we then formulate the communication cost minimization problem for BDSP into a mixed-integer linear programming (MILP) problem and prove it to be NP-hard. We then propose a computation-efficient solution based on MILP. The high efficiency of our proposal is validated by extensive simulation based studies.