Harnessing information from injury narrative in the 'big data' era: Understanding and applying machine learning for injury surveillance

Objective Vast amounts of injury narratives are collected daily and are available electronically in real time and have great potential for use in injury surveillance and evaluation. Machine learning algorithms have been developed to assist in identifying cases and classifying mechanisms leading to injury in a much timelier manner than is possible when relying on manual coding of narratives. The aim of this paper is to describe the background, growth, value, challenges and future directions of machine learning as applied to injury surveillance. Methods This paper reviews key aspects of machine learning using injury narratives, providing a case study to demonstrate an application to an established human-machine learning approach. Results The range of applications and utility of narrative text has increased greatly with advancements in computing techniques over time. Practical and feasible methods exist for semi-automatic classification of injury narratives which are accurate, efficient and meaningful. The human-machine learning approach described in the case study achieved high sensitivity and positive predictive value and reduced the need for human coding to less than one-third of cases in one large occupational injury database. Conclusion The last 20 years have seen a dramatic change in the potential for technological advancements in injury surveillance. Machine learning of ‘big injury narrative data’ opens up many possibilities for expanded sources of data which can provide more comprehensive, ongoing and timely surveillance to inform future injury prevention policy and practice.

Shifting centres: Pedagogical relations in the Era of Big Data

This paper presents a cautious argument for re-thinking both the nature and the centrality of the one-to-one teacher/student relationship in contemporary pedagogy. A case is made that learning in and for our times requires us to broaden our understanding of pedagogical relations beyond the singularity of the teacher/student binary and to promote the connected teacher as better placed to lead learning for these times. The argument proceeds in three parts: first, a characterization of our times as defined increasingly by the digital knowledge explosion of Big Data; second, a re-thinking of the nature of pedagogical relationships in the context of Big Data; and third, an account of the ways in which leaders can support their teachers to become more effective in leading learning by being more closely connected to their professional colleagues.

Using Big Data to manage safety-related risk in the upstream oil and gas industry: A research agenda

Despite considerable effort and a broad range of new approaches to safety management over the years, the upstream oil & gas industry has been frustrated by the sector’s stubbornly high rate of injuries and fatalities. This short communication points out, however, that the industry may be in a position to make considerable progress by applying “Big Data” analytical tools to the large volumes of safety-related data that have been collected by these organizations. Toward making this case, we examine existing safety-related information management practices in the upstream oil & gas industry, and specifically note that data in this sector often tends to be highly customized, difficult to analyze using conventional quantitative tools, and frequently ignored. We then contend that the application of new Big Data kinds of analytical techniques could potentially reveal patterns and trends that have been hidden or unknown thus far, and argue that these tools could help the upstream oil & gas sector to improve its injury and fatality statistics. Finally, we offer a research agenda toward accelerating the rate at which Big Data and new analytical capabilities could play a material role in helping the industry to improve its health and safety performance.

A big idea transmitted pathetically

'A big idea transmitted pathetically' was an exhibition comprising a series of drawing works. These works employ a feminist engagement with the ‘big ideas’ of conceptual art, and enact a ‘redrawing’ of these texts to replay and reveal the complexities of gender politics, representation and language. These works were developed and presented for Bus Projects, Melbourne in 2012.