The Modal Future: A Theory of Future-Directed Thought and Talk

Provisional draft, pre-production copy of my book “The Modal Future” (forthcoming with Cambridge University Press)

Beyond problem identification: valuing methods in a ‘system usability practice’

Historically, usability evaluation methods (UEMs) have been evaluated on their capability for problem identification. However, the relevance of this approach has been questioned for applied usability work. To investigate alternative explanations of what is important for method use a grounded theory of usability practitioners was developed (9 interviews from the website domain and 13 in the safety-critical domain). The analysis proceeded in bottom-up and top-down stages. The bottom-up stages produced insight from the data in an exploratory and inductive manner. This highlighted the importance of contextual factors and the need for system descriptions: UEM adoption and adaptation cannot be fully understood devoid of context. The top-down stages used Distributed Cognition and Resilience Engineering conceptual frameworks as leverage for exploring the data in a deductive manner. These were chosen for their functional descriptions of systems. To illustrate the importance of context we describe three models: 1) where previous research has highlighted the downstream utility of UEMs we expand the metaphor to consider the landscape through which the stream flows, where the landscape represents the project’s context; 2) where information propagation and transformation in a project is influenced by social, information flow, artefact, physical and evolutionary factors; and 3) where the functional couplings between parts of the system of usability practice can be monitored and managed to positively resonate with each other, thereby improving the performance of the system overall. The concept of ‘Positive Resonance’ is introduced to describe how practitioners adapt to the context to maximise their impact under constrained resources. The functional couplings are described in a functional resonance model of HCI practice. This model is validated by interviewees and other practitioners outside of the study. This research shows that problem identification is limited for valuing UEMs. Instead, functional couplings of UEMs should be considered to improve system performance, which influence UEM adoption and adaptation in practice

Aspects of Linguistic Variation

This volume brings together papers on linguistic variation. It takes a broad perspective, covering not only crosslinguistic and diachronic but also intralinguistic and interspeaker variation, and examines phenomena ranging from negation and TAM over connectives and the lexicon to definite articles and comparative concepts in well- and lesser-known languages. The collection thus contributes to our understanding of variation in general

A comparison of the CAR and DAGAR spatial random effects models with an application to diabetics rate estimation in Belgium

When hierarchically modelling an epidemiological phenomenon on a finite collection of sites in space, one must always take a latent spatial effect into account in order to capture the correlation structure that links the phenomenon to the territory. In this work, we compare two autoregressive spatial models that can be used for this purpose: the classical CAR model and the more recent DAGAR model. Differently from the former, the latter has a desirable property: its ρ parameter can be naturally interpreted as the average neighbor pair correlation and, in addition, this parameter can be directly estimated when the effect is modelled using a DAGAR rather than a CAR structure. As an application, we model the diabetics rate in Belgium in 2014 and show the adequacy of these models in predicting the response variable when no covariates are available

A Statistical Approach to the Alignment of fMRI Data

Multi-subject functional Magnetic Resonance Image studies are critical. The anatomical and functional structure varies across subjects, so the image alignment is necessary. We define a probabilistic model to describe functional alignment. Imposing a prior distribution, as the matrix Fisher Von Mises distribution, of the orthogonal transformation parameter, the anatomical information is embedded in the estimation of the parameters, i.e., penalizing the combination of spatially distant voxels. Real applications show an improvement in the classification and interpretability of the results compared to various functional alignment methods