Emotional textual analysis as a semiotic action–research method to work with emotions within organisations

This article aims to contribute to the special issue for the twentieth anniversary of the Organisational and Social Dynamics journal presenting a semiotic action–research method called emotional textual analysis (ETA). ETA, developed in Italy by the Studio of Psychosociology and the Chair of Clinical Psychology at Sapienza University of Rome, is an explorative abductive method that consents to analyse how the organisation symbolically interacts with its context. In ETA methodology the interdependence between the organisational system and the client system is considered as the product of socially shared emotional cultures. This article describes the theoretical and methodological foundation of the ETA method and presents the results of a recent action–research project carried out by the authors within a National Health System organisation. In the conclusion, the added value of using ETA to work with organisations facing contextual changes in the current historical period is discussed.

Revisiting Security Council action on terrorism: New threats; (a lot of) new law; same old problems?

The devastating events of 9/11 triggered the adoption of Resolution 1373 (2001) by the UN Security Council, a contentious development which was much debated and was widely seen as presaging a new type of activity by the Security Council – legislating for all UN member states. And yet, in the counter-terrorism sphere at least, the Council’s legislative activity in the years following 9/11 was relatively modest. Both quantitatively and qualitatively, that activity has been far exceeded by the Council’s response to the emergence of ISIL in 2014. This more recent activity is of interest beyond the confines of counter-terrorism, but has received far less scrutiny to date. This article will remedy this gap, revisiting, in light of the recent activity, the relative merits and disadvantages of making counter-terrorism law through Security Council resolutions. It makes two main contentions. The first is that – due to some factors which were anticipated in the early 2000s and many which were not – Security Council resolutions on terrorism constitute a distinctive category of international law-making and pose serious challenges for the application of organizing principles and processes of general international law. The second is that, for these reasons as well as doubts as to the necessity and efficacy of recent action, making counter-terrorism law through Security Council resolutions should be the exception rather than the norm.

University and Future-Oriented Cultures: Reflections on Cultivating Communities of Practice in the Basque Country

There are currently a number of preconceived ideas about the university and its possible fates within our socially latent future. Some of these assumptions can restrict our capacity to imagine much of the actual potential scenarios at present. Following the Integral Futures perspective, here we stress the relevance of its interior cultural development as a key factor when thinking about the futures of and for the university. Instead of defining specific foresight strategies, however, this paper suggests how some current university extension activities can facilitate a productive cultural basis to enhance their forethought capabilities. It specifically addresses the potential of cultivating Communities of Practice (CoPs), through which institutions are able to connect with wide-ranging cultural domains, from both the inner and outer worlds, and making organizational culture more prone to unbiased imagination. Such features are illustrated with recent action-research conducted at the University of the Basque Country, which will finally provide some guidance on how to seed future-oriented cultures in corresponding universities.

Detecting and Quantifying Natural Selection at Two Linked Loci from Time Series Data of Allele Frequencies with Forward-in-Time Simulations

Recent advances in DNA sequencing techniques have made it possible to monitor genomes in great detail over time. This improvement provides an opportunity for us to study natural selection based on time serial samples of genomes while accounting for genetic recombination effect and local linkage information. Such time series genomic data allow for more accurate estimation of population genetic parameters and hypothesis testing on the recent action of natural selection. In this work, we develop a novel Bayesian statistical framework for inferring natural selection at a pair of linked loci by capitalising on the temporal aspect of DNA data with the additional flexibility of modeling the sampled chromosomes that contain unknown alleles. Our approach is built on a hidden Markov model where the underlying process is a two-locus Wright-Fisher diffusion with selection, which enables us to explicitly model genetic recombination and local linkage. The posterior probability distribution for selection coefficients is computed by applying the particle marginal Metropolis-Hastings algorithm, which allows us to efficiently calculate the likelihood. We evaluate the performance of our Bayesian inference procedure through extensive simulations, showing that our approach can deliver accurate estimates of selection coefficients, and the addition of genetic recombination and local linkage brings about significant improvement in the inference of natural selection. We also illustrate the utility of our method on real data with an application to ancient DNA data associated with white spotting patterns in horses.

Estimation of Natural Selection and Allele Age from Time Series Allele Frequency Data Using a Novel Likelihood-Based Approach

Temporally spaced genetic data allow for more accurate inference of population genetic parameters and hypothesis testing on the recent action of natural selection. In this work, we develop a novel likelihood-based method for jointly estimating selection coefficient and allele age from time series data of allele frequencies. Our approach is based on a hidden Markov model where the underlying process is a Wright-Fisher diffusion conditioned to survive until the time of the most recent sample. This formulation circumvents the assumption required in existing methods that the allele is created by mutation at a certain low frequency. We calculate the likelihood by numerically solving the resulting Kolmogorov backward equation backward in time while reweighting the solution with the emission probabilities of the observation at each sampling time point. This procedure reduces the two-dimensional numerical search for the maximum of the likelihood surface, for both the selection coefficient and the allele age, to a one-dimensional search over the selection coefficient only. We illustrate through extensive simulations that our method can produce accurate estimates of the selection coefficient and the allele age under both constant and nonconstant demographic histories. We apply our approach to reanalyze ancient DNA data associated with horse base coat colors. We find that ignoring demographic histories or grouping raw samples can significantly bias the inference results.

Bringing The Poster Presentation Model into Classroom

Making students to speak English in a large classroom becomes a big challenge for teachers. On one hand, there is no enough time for all students speak equally. On the other hand, most students are lack of confidence and English competence. As a result, the students tend to be reluctant toward the speaking activities. There have been many research under the speaking classroom activities, however, modeling professional activity into classrooms has been rare. The recent action research on a Poster Presentation model aims to make students participate in the classroom activities actively by considering their characteristics. From the individual interview and classroom observations of the 17 passive students enrolled on the four Speaking for Academic Purposes classrooms at Sarjanawiyata Tamansiswa University, Indonesia, the researchers found that the Poster Presentation model with two rules applied, i.e. no talk no grade and interrelated questions motivated the students’ participation in the speaking classroom activities. However, the Poster Presentation model did not work on those who have never experienced in natural speaking practices before. Thus, managing the classroom using the present model brings double facets among students.

Are essay mills committing fraud? A further analysis of their behaviours vs the 2006 fraud act (UK)

Many strategies have been proposed to address the supply of bespoke essays and other assignments by companies often described as ‘Essay Mills’ with the act of supply and use being invariably described as ‘contract cheating’. These proposals increasingly refer to the law as a solution in common with other action. In this article, the lead author revisits work undertaken in 2016 as a result of recent legal and extra-legal developments to assess whether the UK Fraud Act (2006) might now be used to tackle some of the activities of the companies involved, by comparing their common practises, and their Terms and Conditions, with the Act. It was previously found that all sites have disclaimers regarding the use of their products but there were some obvious contradictions in the activities of the sites which undermined those disclaimers, for example plagiarism-free guarantees for the work. In this article, we ask and consider the question whether this is still the case having regard to the impact of a change in the law by the UK supreme court and recent action of the UK Advertising Standards Authority. We also consider whether a call for a new offence to be created which specifically targets the undesirable behaviours of these companies is still justified.

Maximum likelihood estimation of natural selection and allele age from time series data of allele frequencies

Temporally spaced genetic data allow for more accurate inference of population genetic parameters and hypothesis testing on the recent action of natural selection. In this work, we develop a novel likelihood-based method for jointly estimating selection coefficient and allele age from time series data of allele frequencies. Our approach is based on a hidden Markov model where the underlying process is a Wright-Fisher diffusion conditioned to survive until the time of the most recent sample. This formulation circumvents the assumption required in existing methods that the allele is created by mutation at a certain low frequency. We calculate the likelihood by numerically solving the resulting Kolmogorov backward equation backwards in time while re-weighting the solution with the emission probabilities of the observation at each sampling time point. This procedure reduces the two-dimensional numerical search for the maximum of the likelihood surface for both the selection coefficient and the allele age to a one-dimensional search over the selection coefficient only. We illustrate through extensive simulations that our method can produce accurate estimates of the selection coefficient and the allele age under both constant and non-constant demographic histories. We apply our approach to re-analyse ancient DNA data associated with horse base coat colours. We find that ignoring demographic histories or grouping raw samples can significantly bias the inference results.

Detecting and quantifying natural selection at two linked loci from time series data of allele frequencies with forward-in-time simulations

Recent advances in DNA sequencing techniques have made it possible to monitor genomes in great detail over time. This improvement provides an opportunity for us to study natural selection based on time serial samples of genomes while accounting for genetic recombination effect and local linkage information. Such genomic time series data allow for more accurate estimation of population genetic parameters and hypothesis testing on the recent action of natural selection. In this work, we develop a novel Bayesian statistical framework for inferring natural selection at a pair of linked loci by capitalising on the temporal aspect of DNA data with the additional flexibility of modelling the sampled chromosomes that contain unknown alleles. Our approach is based on a hidden Markov model where the underlying process is a two-locus Wright-Fisher diffusion with selection, which enables us to explicitly model genetic recombination and local linkage. The posterior probability distribution for the selection coefficients is obtained by using the particle marginal Metropolis-Hastings algorithm, which allows us to efficiently calculate the likelihood. We evaluate the performance of our Bayesian inference procedure through extensive simulations, showing that our method can deliver accurate estimates of selection coefficients, and the addition of genetic recombination and local linkage brings about significant improvement in the inference of natural selection. We illustrate the utility of our approach on real data with an application to ancient DNA data associated with white spotting patterns in horses.