Defining ‘Community’ for Community Translation

Unlike community interpreting, community translation engages with the members of the community both at individual and group levels. This duality of the process makes the identification of the community as a socio-cultural entity and of its individual members all the more important. There have been several attempts to define the concept of ‘community’ in different professional and academic contexts. Mindful of the difficulty of defining community, the paper proposes three methods that can help community translators in visualizing the characteristics of the intended audience and in making informed translation decisions. The three methods, derived from user-centred translation, are scrutinized using a case study based on a real-life National Health Service (NHS) text.

Special Issue Editorial: ‘Community Voices: Perspectives in public service translation’

Editorial

IMP: Imperial Metagenomics Pipeline for high-throughput sequence data

We have developed an in-house pipeline for the processing and analyses of sequence data generated during Illumina technology-based metagenomic studies of the human gut microbiota. Each component of the pipeline has been selected following comparative analysis of available tools; however, the modular nature of software facilitates replacement of any individual component with an alternative should a better tool become available in due course. The pipeline consists of quality analysis and trimming followed by taxonomic filtering of sequence data allowing reads associated with samples to be binned according to whether they represent human, prokaryotic (bacterial/archaeal), viral, parasite, fungal or plant DNA. Viral, parasite, fungal and plant DNA can be assigned to species level on a presence/absence basis, allowing – for example – identification of dietary intake of plant-based foodstuffs and their derivatives. Prokaryotic DNA is subject to taxonomic and functional analyses, with assignment to taxonomic hierarchies (kingdom, class, order, family, genus, species, strain/subspecies) and abundance determination. After de novo assembly of sequence reads, genes within samples are predicted and used to build a non-redundant catalogue of genes. From this catalogue, per-sample gene abundance can be determined after normalization of data based on gene length. Functional annotation of genes is achieved through mapping of gene clusters against KEGG proteins, and InterProScan. The pipeline is undergoing validation using the human faecal metagenomic data of Qin et al. (2014, Nature 513, 59–64). Outputs from the pipeline allow development of tools for the integration of metagenomic and metabolomic data, moving metagenomic studies beyond determination of gene richness and representation towards microbial-metabolite mapping. There is scope to improve the outputs from viral, parasite, fungal and plant DNA analyses, depending on the depth of sequencing associated with samples. The pipeline can easily be adapted for the analyses of environmental and non-human animal samples, and for use with data generated via non-Illumina sequencing platforms.

A psychosocial approach to understanding pilot and controller acceptance of change in ATM, based on three CDA case studies

Next generation ATM systems cannot be implemented in a technological vacuum. The further ahead we look, the greater the likely impact of societal factors on such changes, and how they are prioritised and promoted. The equitable sustainability of travel behaviour is rising on the political agenda in Europe in an unprecedented manner. This paper examines pilot and controller attitudes towards Continuous Descent Approaches (CDAs). It aims to promote a better understanding of acceptance of change in ATM. The focus is on the psychosocial context and the relationships between perceived societal and system benefits. Behavioural change appeared more correlated with such benefit perceptions in the case of the pilots. For the first time in the study of ATM implementation, and acceptance of change, this paper incorporates the Seven Stages of Change model, based on the constructs of the Theory of Planned Behaviour. It employs a principal components (factor) analysis, and further explores the intercorrelations of benefit perceptions, known in psychology as the ‘halo effect’. Disbenefit perceptions may break down this effect, it appears. For implementers of change, this evidence suggests an approach in terms of reinforcing the dominant benefit(s) perceived, for sub-groups within which a halo effect is evident. In the absence of such an effect, perceived disbenefits, such as with respect to workload and capacity, should be off-set against specific, perceived benefits of the change, as far as possible. This methodology could be equally applied to other stakeholders, from strategic planners to the public. The set of three case studies will be extended beyond CDA trials. A set of concise guidelines will be published with a strong focus on practical advice, in addition to continued work enabling a better understanding of the expected, increasing psychosocial contributions to successful and unsuccessful efforts at ATM innovation and change.