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The emergence of the gig economy, with the growth of technology and increased use of digital solutions, has been transforming the nature of work and its organisation in different ways. The differences in technical infrastructure, access to the internet, availability of cloud computing, and ownership of digital devices influence how countries manage this transition. Besides promoting economic growth and employment opportunities, the expansion of gig work offers wider possibilities for addressing some of the structural problems that the Indian economy has faced in recent years. In this chapter, we review the nature of the gig economy in the context of informalisation, flexibility, and vulnerability associated with gig work. In many contexts, gig workers are neither formal nor informal; they are independent contractors, enjoying no benefits as formal or informal workers do. We explore the links between gig workers and those workers engaged in the informal economy; both operate with a certain degree of flexibility but are vulnerable to many risks associated with occupation, health, and social problems. The discussion also highlights the importance of making gig work more inclusive by extending its flexible employment options to more women, persons with disabilities, and those from marginalised backgrounds and utilising the gig economy in formalising the economy in general.

This study aims to develop a machine learning model to detect structure fire fatalities using a dataset comprising 11,341 cases from 2011 to 2019.

Exploratory data analysis (EDA) was conducted prior to modelling, in which ten machine learning models were experimented with.

The main fatal structure fire risk factors were fires originating from bedrooms, living areas and the cooking/dining areas. The highest fatality rate (20.69%) was reported for fires ignited due to bedding (23.43%), despite a low fire incident rate (3.50%). Using 21 structure fire features, Random Forest (RF) yielded the best detection performance with 86% accuracy, followed by Decision Tree (DT) with bagging (accuracy = 84.7%).

Limitations of the study are pertaining to data quality and grouping of categories in the data pre-processing stage, which could affect the performance of the models.

The study is the first of its kind to manipulate risk factors to detect fatal structure classification, particularly focussing on structure fire fatalities. Most of the previous studies examined the importance of fire risk factors and their relationship to the fire risk level.

The study aims to apply catastrophe theory to the analysis of accidental dwelling fire injuries in terms of age band, gender and contributory factors in order to inform fire prevention activities.

The study employed a case study in a UK Fire and Rescue service concerning analysis of the circumstances of accidental dwelling fire injuries, and the characteristics and behaviours associated with utilising frequency analysis, percentages, ratios and catastrophe theory modelling.

Overall, males were more likely to be injured in an accidental dwelling fire compared to females by a ratio of 1.68 to 1, and those in the age band 50–64 appeared to be at maximum risk. A total of 15.4% of the accidental dwelling fire injuries involved consumption of alcohol or drugs, and 5.9% involved falling asleep.

The circumstances of accidental dwelling fire injury can be analysed to identify patterns concerning when a catastrophic change relating to ordinary use of domestic objects results in an accidental dwelling fire injury.

A catastrophe theory view can aid the understanding of how ordinary use of domestic objects results in an accidental dwelling fire injury.

Since fire injuries have both a social and economic cost, understanding how such fire injuries occur can aid fire prevention through appropriately targeted fire prevention activities.

The study made use of a catastrophe theory view to analyse the circumstances under which accidental dwelling fire injuries occurred using fire injury data from a UK fire and rescue service.

This paper aims to explore and conceptualize the emotional labor of racial minorities and women in the gig economy.

The paper draws on current research on gig workers' engagement in emotional labor and accounts of unfair practices in the gig economy. It calls out the presence of bias in algorithmic systems used within the gig economy as a means of control and gig worker management. The negative impact of such bias on a specific gig worker demographic is theorized.

Through a review of research on the nature of work in the gig economy, the paper suggests an unspoken mandate exists for gig workers to engage in emotional labor practices. Specifically, the nature of gig work in terms of algorithmic control, coupled with gig work dependence, often creates a need for gig workers to engage in emotional labor. This need is heightened for racial and ethnic minorities and women gig workers.

As gig platforms increasingly rely on algorithms for management and gig workers face biases, this paper offers valuable insights that contribute to a comprehensive understanding of the gig economy's impact on worker well-being. The paper discusses the need for more profound research into the nature of work in the gig economy and the life experiences of gig workers.

This paper has significant implications for organizations and gig workers. Understanding the relationships proposed in this paper can inform organizational strategies to enhance the well-being of gig workers and improve their overall work experiences, potentially leading to increased satisfaction and reduced turnover. Additionally, the paper recommends strategies gig workers can utilize to achieve positive outcomes.

The evolving work landscape, driven by the gig economy, necessitates a thorough understanding of new work dynamics. This paper sheds light on the often-overlooked diversity within the gig workforce, mainly focusing on the unique experiences of women and racial and ethnic minorities.

Psychosocial problems, including social isolation and loneliness, are prevalent in rural communities and can impact the use of health services and health outcomes. Current approaches to managing patients with predominantly psychosocial issues may not be the most appropriate. Social prescribing (SP) is a relatively new way of linking patients with sources of non-medical support within the community. Emerging literature suggests that community-based, non-medical activities are an effective and preferred approach to managing psychosocial problems. However, there is little evidence describing the attitudes of general practitioners (GPs) towards formal SP pathways.

This research will occur in a general practice in a rural area of Tasmania, Australia. The project will deliver an education module to rural GPs to highlight the benefits of SP and provide a streamlined pathway for referring patients to community support hubs. Existing community organisations will act as “link workers” to connect patients with suitable community activities. GPs will complete a baseline and follow-up survey to measure their perception of SP and the acceptability, feasibility and appropriateness of such an intervention.

The acceptability, feasibility and appropriateness of the pathway will be assessed using published measures. Free-text responses to open-ended questions will be used to complement the quantitative data. A hybrid effectiveness-implementation method will be used to gather information about the rate of uptake and quality of the SP referral process and identify barriers and facilitators of the process in a real-world setting.

While qualitative data for SP programmes is predominantly positive, quantitative data is lacking. Although the planned project is relatively short, it will provide a basis for future SP programme implementation and guide the approach to data collection and implementation assessment.

The barriers to and facilitators of introducing a SP programme in a rural general practice setting may be used to guide the development and implementation of future large-scale SP interventions. This research is both timely and relevant as the problem of social isolation and loneliness, especially in rural areas of Australia, is becoming more well-recognised as a driver of poor health and unnecessary health service usage.

Using SP to address psychosocial risks may reduce healthcare burden and costs. Few SP programmes have been delivered and formally assessed in Australia, and the best way to implement SP locally remains unclear. By delivering a SP intervention in a rural setting and assessing GPs’ responses, future SP projects will be better able to design and integrate social and medical care services.

The rapid spread of the COVID-19 pandemic upended societies across the world, with billions forced into lockdowns. As countries contemplated instating and rolling back lockdown measures, and considered the impact of pandemic fatigue on policy measures, and furthermore to prepare for the improved management of future pandemics, this study examines the effectiveness of policy measures in limiting the spread of infections and fatalities.

The methodological approach in the study centres on a fixed effects panel regression analysis and employs the COVID-19 Government Response Stringency Index, which comprises eight containment measures and three health campaigns, with progressive degrees of stringency, in order to investigate the efficacy of government policies.

Findings suggest that some government policies were effective at reducing implicit mortality rates, infection cases and fatalities during the first four months of the COVID-19 pandemic. Solid stringency measures to reduce mortality rates include public gathering restrictions on more than 100 attendees, and international travel limits for developed countries and islands. Fatalities can further be reduced through the closing of public transport, whereas infection cases also experience benefits from public information campaigns. Comparable results are observed in a robustness test across 12 months.

Some non-pharmaceutical policies are shown to be more effective than others at reducing the spread of infections, fatalities and mortality rates, and support policymakers to manage future pandemics more effectively.

The purpose of this paper is to examine whether mandatory disclosure of information accompanying the sale of real estate achieves its aim of informed purchasers.

Using a case study approach focused on mandatory disclosure in South Australia data was collected from interviews and focus groups with key personnel in the property industry involved in the production of information required to fulfil vendors’ disclosure obligations.

The authors found that purchasers are ill-served by a long and complex form of mandatory disclosure with a short time frame that prevents the use of the information provided. Without good form design and increased digital affordances provided by the cadastral and conveyancing systems, mandatory disclosure is insufficient to ensure minimisation of information asymmetry between vendor and purchaser.

To the best of the authors’ knowledge, this is the first Australian qualitative study that examines the utility of mandatory vendor disclosure in real estate sales and the first to consider the impact of the digitalisation of cadastral and conveyancing systems upon the efficacy of mandatory disclosure regimes.