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This first study of the major contributions by Sarah née Wallis, Mrs T(homas) Edward Bowdich, then Mrs R(obert) Lee (1791–1856) to new knowledge of natural history has focused on her book-length publications concerning West Africa, including its preparations in the field for her undertaking of The Fresh-Water Fishes of Great Britain. The nine chapters and their lessons therefore bring to serious critical attention Sarah's multiple contributions to cross-Channel natural history-making in her published works from 1825 until her death. They also inspire the recuperation of other women in the first half of the nineteenth century at work and publishing in science in at least two language cultures. Chapter findings individually and collectively, as gathered together below, then only magnify the main questions of this book. Why and how, indeed, has Sarah remained so firmly in the blind spots of expert Anglophone and Francophone critical inquiry in the disciplines covered in the introduction, and despite gender, transnational and interdisciplinary lenses? Her works plainly added to major discipline fields, and in the case of (modern) ichthyology and anthropology were in their vanguard. The imprimaturs of Cuvier and Humboldt affirmed their first-ranking, original qualities. Sarah's works also eminently proved the rule that a woman could exist, thrive and regularly publish (expert) natural history in the period. But her corpus also demonstrated why the best modern (inter-)disciplinary inquiry in the history, geography and cultures of nineteenth-century British, French and European science will fail to accommodate its expertly multi-genre, intermedial hybridity. Set assumptions govern and determine who and what constitutes ‘serious’ contribution to science of the period, also informing science and its histories today. The introduction highlighted the benchmarks that consolidate scientific endeavour in the first half of the nineteenth century by which Sarah cannot be seen. They are modelled by ‘genteel’ and national(istic) standards compounding the (professionalised) thrall of modern discipline distinctions imposed retrospectively upon ‘serious’ natural history and earlier ‘naturalists’ as its makers in consequence. The nine chapters individually and together challenge modern critics to pay much closer attention to pre-1850 context(s) for broad-church natural history on the one hand, and on the other hand to the latter's foundational basis for ‘new’ nineteenth-century scientific specialisms, such as ichthyology, anthropology and ethnography in which Sarah was a remarkable forerunner irrespective of her sex.
In light of the ‘“Accounts” of Direct Encounter’ discussed in Chapter 8, Sarah's generic classification of both her Anecdotes of the Habits and Instincts of Animals (1852) and Anecdotes of the Habits and Instincts of Birds, Reptiles and Fishes (1853) as ‘anecdotes’ was doubly unam-biguous. These companion volumes overtly adopted the term that she had strategically deployed in the revised Elements (ENH2), to replace the synonymous ‘amusing and instructive original accounts’ of its first edition. ‘Anecdotes’ therefore provided ‘proofs of sagacity or affection’ in the animals concerned and ‘proofs’ of the tellers’ expertise: ‘[f]ew of them exist in any other publication, unless they have been copied from this work’ (ENH2, iii–iv). Sarah's phrasing therefore exemplifies the first and second definition of ‘anecdotes’ in the OED: ‘1. Secret, or hitherto unpublished narratives or details of history. 2. The narrative of an interesting or striking incident or event’. Because many of the same underpinning expert authorities for the Elements (ENH; ENH2) informed her Anecdotes (AnecA; AnecBRF) as Appendices 8 and 9 clearly demonstrate for the first time, their names similarly endorsed the scientific objectives and expertise of her double-volume Anecdotes, yet also question its novelty. Its reader already familiar with the Elements (ENH; ENH2) in 1852–1853 or today might reasonably suppose that Sarah simply deleted its drier ‘textbook’ components and remixed the ‘anecdotes’ that she had already used in it for the same animal. The Anecdotes (AnecA; AnecBRF) were then adroit abridgements – the clearly reduced coverage of mammals in the first volume – and simple supplementation, for example concerning ‘reptiles’ in the second. On closer inspection (also clarified by comparing Appendices 8 and 9), Sarah's Anecdotes (AnecA; AnecBRF) offer no reheat of the anecdote materials used in the Elements (ENH; ENH2). Rather, the major importance of ‘anecdotes’ lies in their careful ‘selection’, as Sarah states in her three-page preface to the two-volume Anecdotes states in 1852 (reformatted in Figure 9.1 ). As this chapter sets out, expert (natural) selection seriously raises the stakes for the genre of the scientific anecdote itself in her pioneering hands in 1852–1853, and hence for natural science communication today.
The writing of history and, above all, literary criticism can, and must, always be understood as an attempt to find in the past aspects of human experience that can shed light on the meaning of our own times.
—Jan Kott, Shakespeare Our Contemporary (1964)
The seeds of books germinate in both well-lit and shadowy imaginative spaces. In this way, books exhibit an affinity with the dreams Sigmund Freud studied in The Interpretation of Dreams (1900), where he learned that identifying the “background thoughts” from which dream symbols emerge, particularly those intricate or bizarre images resistant to quick explanation, was hardly a simple task. The search for their origins led him to free association, a process in which a patient focuses on specific images, not on a complete dream narrative, and to the conclusion that “interpretation en detail and not en masse” better enables an investigator to uncover the overdetermined nature of dream images—their provenance in several sources, not just one. Like dreams, books often arise from an untidy jumble of places: an archive of prior cultural texts (scrivened, visual, aural); major social, scientific and historical developments; and the imprints of individual experiences, large and small, etched on a writer's memory. Some of these are transformative or, in the worst of cases, traumatic—a stunning success or mortifying failure, a once-in-a-century pandemic and a pitched medical battle to vanquish it—while others are tethered to the banalities of everyday life that, surprisingly, demand expression. Such is the case with From the “Troubles” to Trumpism.
As a student of Irish history and culture for over forty years, I have enjoyed numerous opportunities to visit Ireland and Northern Ireland, and written about both, most often discussing literature, drama and theatrical production. This engagement constitutes one source of the pages that follow but, again, there are others. One in particular motivates the political bristle of this book: recent socio-political discord in America, particularly that associated with the presidential election of 2020, the insurrection at the Capitol on January 6, 2021 and the shocking state of affairs (and indictments) prefatory to the 2024 elections.
There is an incisive exchange about history and collective memory in Bernard MacLaverty's Cal, a novel (and, later, film) set during the Troubles complete with Orange Lodge parades, deadly ambushes and the firebombing of Catholic homes. Over his career, MacLaverty has written several novels and short stories portraying in often excruciating detail the emotional toll of living through such violence, with Cal being, arguably, the most poignant. When discussing the novel, critics often point to similarities between the dilemma of its main characters and that of Shakespeare's “star-crossed” lovers Romeo and Juliet, as its protagonist Cal McCrystal (McCluskey in later printings), an unemployed, working-class Catholic, falls in love with Marcella Morton, the young widow of a Protestant policeman in whose murder Cal was complicit. In this “love across the barricades” story, as in Shakespeare's play, a sense of tragic foreboding is occasionally relieved by glimmers of possibility—for example, when Cal finds fulfilling work on the Morton family farm and makes a new home there to be near Marcella. His days of living on the dole may be over, and his new job hints at a better future. Unlike the protagonists of Romeo and Juliet whose fates are tied to family lineages and histories they cannot alter, Cal seems convinced that he possesses the agency to escape his connection to sectarian violence. Sadly, in the novel's closing scene, his arrest and imminent punishment destroy any possibility of a future with Marcella. But the question remains unanswered, to recall Haines's observation in James Joyce's Ulysses, of how “history is to blame” for Cal's fate. Perhaps it isn’t. Perhaps historical memory and the at times nefarious uses to which history is put are the culprits (Figure 6).
Unlike Cal, MacLaverty's later novel Grace Notes (1997) develops tensions between memory and aspiration that lead to a happier, even refulgent conclusion. The novel begins with a fledgling composer, Catherine McKenna, returning to Northern Ireland from Scotland to attend her father's funeral. At the cemetery where he is interred, she passes the grave of a boy she once knew who “gave his life for Ireland,” as an inscription beneath his name on his headstone clarifies. Reading the epitaph, Catherine wonders what musical composition might best represent the militant nationalism for which her former classmate sacrificed his life.
President [Lyndon B.] Johnson's attitude to Ireland and the Irish will be warm and friendly […] but of course without [the] usual depth of feeling.”
—Irish Ambassador Thomas J. Kiernan, quoted in Loftus, “The Politics of Cordiality” (2009)
Goldwater, a libertarian Westerner, doesn't deserve to have his pursuit of the Presidency equated with the weird, conspiracy-minded, racebaiting campaign of Donald J. Trump, the former reality-show performer, real-estate developer, and expert bully, who is about to claim his party's nomination and apparently wants to claim a piece of Goldwater's history as well.
—Jeffrey Frank, “Extreme Conventions,” The New Yorker ( June 21, 2016)
In the same spring that John Hume's seminal article appeared in the Irish Times (May 1964) advocating for nonviolent means of addressing a growing crisis in Northern Ireland, Wendell Berry published his first book of poetry. Accompanied by stunning illustrations, the book was comprised of a single elegy, “November Twenty Six Nineteen Sixty Three,” which first appeared the previous December in The Nation. At the same time, profound social change was occurring in Ireland, Northern Ireland and America that would redefine the relationships between all three—and between all three and Britain.
In America on October 1, 1962, after the governor of Mississippi defied a Supreme Court order and a riot ensued that required the National Guard to subdue, James Meredith became the first African American to matriculate at the University of Mississippi. Some 250,000 civil rights marchers traveled to Washington the following August, where Martin Luther King Jr.'s “I Have a Dream” speech reverberated through the Lincoln Memorial. In the summer of 1964, the Civil Rights Act was passed, with the Voting Rights Act signed into law a year later. The impact of these events was enormous, and it was not confined to America.
In the evolving discourse on artificial intelligence (AI), the quest for strong AI (Searle, 1980) remains paramount. This chapter seeks to elucidate the foundational assumptions that underpin philosophers’ and computer scientists’ assertions about the prerequisites for achieving strong AI. The current trajectory in AI, notably within computer science, is increasingly influenced by Google Brain's white paper on the Transformer architecture (Vaswani et al. 2017), a groundbreaking deep-learning model that reshaped the scientific landscape of Natural Language Processing (NLP) and Machine Learning (ML). The Transformer architecture forms the backbone behind the development of Large Language Models (LLMs) such as OpenAI's ChatGPT and Google's BERT. The Transformer architecture emphasizes the importance of handling sequential data through self-attention mechanisms, reflecting the human ability to emphasize certain textual elements over others based on context. In this chapter, I refer to these LLMs as ‘Statistical AI’, since Transformer architecture relies heavily on statistical methods when modelling these self-attention mechanisms. LLMs have not only achieved immediate commercial success and cultural impact for the tech industry, but the world's leading computer scientists like Ilya Sutskever also believe that they could be ‘slightly conscious’ (Sutskever 2022).
Contrasting this prevalent view, the chapter turns to the critiques offered by philosophers Noam Chomsky and Robert Brandom. Chomsky's internalist critique underscores the limitations of purely statistical models in capturing authentic human linguistic practices. Statistical models of reasoning have great practical use cases but are irrelevant to science. They are not proper models of reasoning, for human linguistic practices do not require agents to look up probability tables of what word should be used in an utterance (Chomsky et al. 2023). Conversely, Brandom's externalist perspective emphasizes the need for AI to engage in autonomous discursive practices (ADPs). ADPs are practices that are regulated by norms that are implicit within the practice itself and not regulated by external factors (i.e. training data in an AI context). ADPs involve making inferences when deployed within the context of communication or actions with other agents, while also allowing for self-correction when compared to the norms the ADP is grounded on and even correcting norms themselves (Brandom 2006).
Wittgenstein's ideas are a common ground for developers of Natural Language Processing (NLP) systems and linguists working on Language Acquisition and Mastery (LAM) models (Mills 1993; Lowney et al. 2020; Skelac and Jandrić 2020). In recent years, we have witnessed a fast development of NLP systems capable of performing tasks as never before. NLP and LAM have been implemented based on deep-learning neural networks, which learn concept representation from rough data but are nonetheless very effective in tasks such as question answering, textual entailment and translation (Devlin et al. 2019; Kitaev, Cao, and Klein 2019; Wang et al. 2019). In this chapter, I will debate some Wittgensteinian concepts that impact the architectures of many NLP deep-learning systems. I will focus, in particular, on the attempt to build a specific kind of architecture to model a private language. The discussion, I think, helps extract philosophical assumptions leading the research and development of AI systems capable of language modelling. In this chapter, I will address some of the main features of NLP systems used for word embedding and one proposal to manipulate through a neural network a form of private language (Lowney et al. 2020).
In ‘The Private Language Argument’, I will reconstruct the complex path of the private language argument (PLA). In ‘Connectionist Language Models in NLP’, I will discuss connectionist language models and introduce notions about NLP systems’ architecture. An overview of this kind of model is helpful to introduce the work of Lowney et al. (2020). They submit that their model can respond to the issues raised by Wittgenstein in the famous PLA. This argument unexpectedly turned out to be relevant not only for the philosophy of language but also for NLP and LAM modellers. I will describe the language game concept in NLP, how it is embedded, and its role in inductive systems development. This central concept in Wittgenstein's work is relevant to describe the role of context in understanding the meanings of words. In ‘Wittgenstein and Connectionism’, I present the Wittgensteinian main concepts at play in the connectionist paradigm. I argue that the connectionist theoretical framework can better catch the dependency of word meaning on context.