'Saig in Machai Fothúaid': On the Application and Extent of ‘the Macha’ in North-west Armagh

The seventh-century Patrician documents in the Book of Armagh, and other early sources such as Bethu Phátraic, contain references to the toponym Macha, which has been identified by the Dictionary of the Irish Language with either the ecclesiastical centre of Ard Macha or the ‘royal seat’ of Emain Macha. This article examines the evidence for the name in the sources and illustrates that Macha applies primarily to the plain in which both Ard Macha and Emain Macha are located. It is to be identified with Mag Macha ‘the plain of Macha’, familiar to us from the Dindshenchus, and further evidence of the organic potential of a given toponym is witnessed in later sources where the plain is referred to as Mag/Machaire na hE(a)mna ‘the plain of Emain’ and Machaire Aird/Arda Macha ‘the plain of Armagh’. The extent of Macha is difficult to establish with certainty, but it seems very likely that it stretched north to the River Blackwater as well as south towards Slíab Fúait.

Perception of emotion: towards a realistic understanding of the task

A decade ago, perceiving emotion was generally equated with taking a sample (a still photograph or a few seconds of speech) that unquestionably signified an archetypal emotional state, and attaching the appropriate label. Computational research has shifted that paradigm in multiple ways. Concern with realism is key. Emotion generally colours ongoing action and interaction: describing that colouring is a different problem from categorizing brief episodes of relatively pure emotion. Multiple challenges flow from that. Describing emotional colouring is a challenge in itself. One approach is to use everyday categories describing states that are partly emotional and partly cognitive. Another approach is to use dimensions. Both approaches need ways to deal with gradual changes over time and mixed emotions. Attaching target descriptions to a sample poses problems of both procedure and validation. Cues are likely to be distributed both in time and across modalities, and key decisions may depend heavily on context. The usefulness of acted data is limited because it tends not to reproduce these features. By engaging with these challenging issues, research is not only achieving impressive results, but also offering a much deeper understanding of the problem.