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Abstract In his two-part article ‘An Analysis of the Word Adjacency Network Method—Part 1—The evidence of its unsoundness’ and ‘Part 2—A true understanding of the method’ Digital Scholarship in the Humanities, 38: 347-78 (2022), Pervez Rizvi attempts to replicate the Word Adjacency Network (WAN) method for authorship attribution and show that it does not produce the new knowledge that we, its inventors, claim for it. In the present essay, we will show that Rizvi misrepresents fundamental aspects of the WAN method, that his attempted replication fails not because the method is flawed but because he erred in replicating it, and that Rizvi misunderstands key aspects of the mathematics of Information Theory that the method uses.

Since 2007 a number of investigators have compiled statistics on the length in words of speeches in plays by William Shakespeare and his contemporaries, focusing on a change to shorter speeches around 1600. In this article we take account of several potentially confounding factors in the variation of speech lengths in these works and present a model of this variation in the period 1538–1642 through Linear Mixed Models. We confirm that the mode of speech lengths in English plays changed from nine words to four words around 1600, and that Shakespeare’s plays fit this wider pattern closely. We establish for the first time: that this change is independent of authorship, dramatic genre, theatrical company, and the proportion of verse in a play’s dialogue; that the chosen time span can be segmented into pre-1597 plays (with high modes), 1597–1602 plays (with mixed high and low modes), and post-1602 plays (with low modes); that some additional secondary modes are evident in speech lengths, at 16 and 24 words, suggesting that the length of a standard blank verse line (around 8 words) is an underlying unit in speech length; and that the general change to short speeches also holds true when the data is viewed through the perspective of the median and the mean. The change in speech lengths is part of a collective drift in the plays towards liveliness and verisimilitude and is evidence of a hitherto hidden constraint on the playwrights: whether or not they were aware of the fact, playwrights as a group were conforming to a structure for the distribution of speech lengths peculiar to the era they were writing in. The authors hope that the full modelling of this variation in the article will help bring this change to the attention of scholars of Shakespeare and his contemporaries.

open access article

Welcome to this 'genetic edition' of Andrew Davies' 1994 BBC adaptation of George Eliot's Middlemarch. This multimedia resource, believed to be the first of its kind, uses XML textual encoding - following the principles of the Text Encoding Initiative (TEI) - to enable comparative analyses charting the journey of a literary adaptation from source novel to script and screen. Users can navigate from the Shooting Script backwards (to the novel) and forwards (to the Post-production Script), following diamond icons leading to Notes, intertextual references, a range of assets and additional extended Commentaries on key scenes and adaptive moments. In this way, the genetic edition demonstrates both the creative skills of the screen adaptor and script editor, and (via additional production history research) the collaborative nature of classic serial television adaptation. The 'genetic edition' has been created by an interdisciplinary team of researchers at De Montfort University, UK, in partnership with the British Library and in consultation with the George Eliot Archive. The project (2022-3) was funded by the Arts and Humanities Research Council.

free access article What goes into turning a literary classic into popular TV drama? That’s the question at the heart of a DMU research project funded by the Arts and Humanities Research Council (AHRC) in partnership with the British Library. ‘Transforming Middlemarch’ traces the journey from book to screen of George Eliot’s groundbreaking novel, drawing on the scripts, notes and correspondence of celebrated screenwriter Andrew Davies, who adapted Middlemarch for the BBC in a 6-part series starring Juliet Aubrey, Douglas Hodge, and Rufus Sewell first aired in 1994. 2022 marked the 150th anniversary of the first, serialised, publication of Middlemarch, set in a fictionalised Coventry at time of the great Reform Bill. So it was a timely choice from the extensive back catalogue of the prolific Davies, who donated his personal archive to DMU’s Special Collections in 2015. Middlemarch (1994) also marked a watershed for the BBC. In partnership with WGBH (Boston), Michael Wearing (Head of Drama) gambled what was then a risky £6m on a lavish production shot on film and set on location (in Rome and the Lincolnshire town of Stamford) that was big on period detail. In turn, it spawned a raft of BBC Education resources, a (then unusual) ‘making of…’ documentary, and lively arts show critics’ debates; and it boosted Stamford’s tourist trade with location tours and a repertoire of visitor souvenirs. Following its success, Davies’ next BBC heritage adaptation was Pride and Prejudice (best remembered for that scene of Mr Darcy’s dip in the lake which doesn’t appear in Jane Austen). The rest, as they say, is history. This article summarises the project’s process and previews this open-access literary adaptation web resource for the benefit of Learning on Screen affiliates.

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link By the mid-1920s, the top echelons of the film industry on both sides of the Atlantic, were almost entirely dominated by men, despite women becoming the majority consumers of cinema. Male studio bosses, producers, directors and publicists interpreted women’s tastes and expectations throughout the silent period. In 1926, the film critic Iris Barry insisted that cinema ‘exists for the purpose of pleasing women’ (Barry, 59) who formed a significant majority of the British population from the 1910s. Women were also central to the burgeoning consumer cultures surrounding cinema including magazines, novels, fashion, beauty and leisure and their tastes and patterns of consumption steered the expansion of the cinema industry. But despite their increasing economic power as consumers, Barry also lamented Hollywood’s insistence on driving women to romance and marriage rather than adventure and independence (ibid.: 61). This article considers how cinema’s masculine power base was forced to accommodate and address feminine cultures despite repeated excoriation of young female cinemagoers by Britain’s intellectual elites.

Lawrence Linnell (1870-1957): bobsleighing champion and the alpine resort of Davos and its other visitors from Leicester Leicestershire Historian, 48, 3-10

This study is one of the 21 projects funded by the Home Office for research on perpetrators of domestic abuse. It is interested in a specific form of domestic abuse known as Technology Facilitated Coercive Control (TFCC) and focussed on the digital communication between (alleged) perpetrators and victim/survivors held on mobile phones. The purpose of this feasibility study was twofold, i. to test the viability of an Artificial Intelligence (AI) programme to identify () perpetrators (including alleged perpetrators) of domestic abuse using digital communications held on mobile phones ii. to examine police and victim/survivor attitudes towards using AI in police investigations. Using digital conversations extracted from court transcriptions where TFCC was identified as a factor in the offending, the research team tested data sets built on different methods and techniques of AI. Natural Language Processing (NLP) tools, a subfield of AI, were also tested for their speed and accuracy in recognising abusive communication and identifying and risk assessing perpetrators of TFCC. Conscious of national concern about policing practices relating to Violence Against Women and Girls and that any AI programme would be futile without the co-operation of both the police and the public, two online surveys were devised to measure opinion. The first sought insight into the attitudes of victim/survivors, viewed as experts in domestic abuse, about using AI in police investigations. The second involved the police and questioned their views of using AI in this way.

This is an article commissioned by BBC History for their online magazine BBC History Extra. A historical review of the contemporary practice of sportswashing, by which dictatorial governments use sporting events to promote favourable images of themselves for domestic and international audience.

Consistency is an important issue in linguistic decision making with various consistency measures and consistency improving methods available in the literature. However, existing linguistic consistency studies omit the fact that words mean different things for different people, that is, decision makers’ personalized individual semantics (PISs) over their expressed linguistic preferences are ignored. Therefore, the aim of this article is to propose a novel consistency improving approach based on PISs in linguistic group decision making. The proposed approach combines the characteristics of personalized representation and integrates the PIS-based model in measuring and improving the consistency of linguistic preference relations. A detailed numerical and comparative analysis to support the feasibility of the proposed approach is provided. This work was supported in part by the NSF of China under Grant 71901182, Grant 71601133, and Grant 71871149; in part by Sichuan University under Grant sksyl201705 and Grant YJ201906; in part by Southwest Jiaotong University under Grant YJSY-DSTD201918; in part by the China Postdoctoral Science Foundation under Grant 2020M673283 and Grant 2682021ZTPY073; and in part by the Spanish State Research Agency under Project PID2019-103880RB-I00/AEI/10.13039/501100011033. National Natural Science Foundation of China (NSFC) 71901182 71601133 71871149 China Postdoctoral Science Foundation 2020M673283 2682021ZTPY073 Southwest Jiaotong University YJSY-DSTD201918 Sichuan University sksyl201705 YJ201906 Spanish Government PID2019-103880RB-I00