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In his story Sarrasine Balzac, describing a castrato disguised as a woman, writes the following sentence: ‘This was woman herself, with her sudden fears, her irrational whims, her instinctive worries, her impetuous boldness, her fussings, and her delicious sensibility.’ Who is speaking thus? Is it the hero of the story bent on remaining ignorant of the castrato hidden beneath the woman? Is it Balzac the individual, furnished by his personal experience with a philosophy of Woman? Is it Balzac the author professing ‘literary’ ideas on femininity? Is it universal wisdom? Romantic psychology? We shall never know, for the good reason that writing is the destruction of every voice, of every point of origin. Writing is that neutral, composite, oblique space where our subject slips away, the negative where all identity is lost, starting with the very identity of the body writing. No doubt it has always been that way. As soon as a fact is narrated no longer with a view to acting directly on reality but intransitively, that is to say, Vnally outside of any function other than that of the very practice of the symbol itself, this disconnection occurs, the voice loses its origin, the author enters into his own death, writing begins. The sense of this phenomenon, however, has varied; in ethnographic societies the responsibility for a narrative is never assumed by a person but by a mediator, shaman or relator whose ‘performance’—the mastery of the narrative code—may possibly be admired but never his ‘genius’. The author is a modern Vgure, a product of our society insofar as, emerging from the Middle Ages with English empiricism, French rationalism and the personal faith of the Reformation, it discovered the prestige of the individual, of, as it is more nobly put, the ‘human person’. It is thus logical that in literature it should be this positivism, the epitome and culmination of capitalist ideology, which has attached the greatest importance to the ‘person’ of the author. The author still reigns in histories of literature, biographies of writers, interviews, magazines, as in the very consciousness of men of letters anxious to unite their person and their work through diaries and memoirs. The image of literature to be found in ordinary culture is tyrannically centred on the author, his person, his life, his tastes, his passions, while criticism still consists for the most part in saying that Baudelaire’s work is the failure of Baudelaire the man, Van Gogh’s

We introduce the author-topic model, a generative model for documents that extends Latent Dirichlet Allocation (LDA; Blei, Ng, & Jordan, 2003) to include authorship information. Each author is associated with a multinomial distribution over topics and each topic is associated with a multinomial distribution over words. A document with multiple authors is modeled as a distribution over topics that is a mixture of the distributions associated with the authors. We apply the model to a collection of 1,700 NIPS conference papers and 160,000 CiteSeer abstracts. Exact inference is intractable for these datasets and we use Gibbs sampling to estimate the topic and author distributions. We compare the performance with two other generative models for documents, which are special cases of the author-topic model: LDA (a topic model) and a simple author model in which each author is associated with a distribution over words rather than a distribution over topics. We show topics recovered by the author-topic model, and demonstrate applications to computing similarity between authors and entropy of author output.

In less than 2 months, the artificial intelligence (AI) program ChatGPT has become a cultural sensation. It is freely accessible through a web portal created by the tool’s developer, OpenAI. The program—which automatically creates text based on written prompts—is so popular that it’s likely to be “at capacity right now” if you attempt to use it. When you do get through, ChatGPT provides endless entertainment. I asked it to rewrite the first scene of the classic American play Death of a Salesman , but to feature Princess Elsa from the animated movie Frozen as the main character instead of Willy Loman. The output was an amusing conversation in which Elsa—who has come home from a tough day of selling—is told by her son Happy, “Come on, Mom. You’re Elsa from Frozen . You have ice powers and you’re a queen. You’re unstoppable.” Mash-ups like this are certainly fun, but there are serious implications for generative AI programs like ChatGPT in science and academia.

The production, reception and discussion of fanfiction is a major aspect of contemporary global media. Thus far, however, the genre has been subject to relatively little rigorous qualitative or quantitative study-a problem that Judith M. Fathallah remedies here through close analysis of fanfiction related to Sherlock, Supernatural, and Game of Thrones. Her large-scale study of the sites, reception, and fan rejections of fanfic demonstrate how the genre works to legitimate itself through traditional notions of authorship, even as it deconstructs the author figure and contests traditional discourses of authority. Through a process she identifies as the 'legitimation paradox', Fathallah demonstrates how fanfic hooks into and modifies the discourse of authority, and so opens new spaces for writing that challenges the authority of media professionals.

BACKGROUND: We recently described "Author-ity," a model for estimating the probability that two articles in MEDLINE, sharing the same author name, were written by the same individual. Features include shared title words, journal name, coauthors, medical subject headings, language, affiliations, and author name features (middle initial, suffix, and prevalence in MEDLINE). Here we test the hypothesis that the Author-ity model will suffice to disambiguate author names for the vast majority of articles in MEDLINE. METHODS: Enhancements include: (a) incorporating first names and their variants, email addresses, and correlations between specific last names and affiliation words; (b) new methods of generating large unbiased training sets; (c) new methods for estimating the prior probability; (d) a weighted least squares algorithm for correcting transitivity violations; and (e) a maximum likelihood based agglomerative algorithm for computing clusters of articles that represent inferred author-individuals. RESULTS: Pairwise comparisons were computed for all author names on all 15.3 million articles in MEDLINE (2006 baseline), that share last name and first initial, to create Author-ity 2006, a database that has each name on each article assigned to one of 6.7 million inferred author-individual clusters. Recall is estimated at ~98.8%. Lumping (putting two different individuals into the same cluster) affects ~0.5% of clusters, whereas splitting (assigning articles written by the same individual to >1 cluster) affects ~2% of articles. IMPACT: The Author-ity model can be applied generally to other bibliographic databases. Author name disambiguation allows information retrieval and data integration to become person-centered, not just document-centered, setting the stage for new data mining and social network tools that will facilitate the analysis of scholarly publishing and collaboration behavior. AVAILABILITY: The Author-ity 2006 database is available for nonprofit academic research, and can be freely queried via http://arrowsmith.psych.uic.edu.

Information published in medical journals helps shape diagnostic and therapeutic decisions. For a journal to be of value, it must publish authoritative, up-to-date information that is free of commercial influence. For nearly two decades, the editors of the New England Journal of Medicine, along with the editors of other journals, have set policies to ensure that the financial associations of authors are disclosed and that published articles are not influenced by those financial associations.1–9 These important editorial policies have raised awareness about conflict of interest in medical research and have helped prevent bias — and the appearance of bias . . .

This article offers an analysis of the impact of professional social-media engagement upon authors. Authors primarily use Facebook, Twitter and there is growing use of Pinterest. Authors use social-media platforms primarily for marketing, publicity and making contact with readers. They tend to adopt a multi-layered approach to self-presentation and the lines between their ‘public’ and ‘private’ identities are blurred. The research reveals a limited author-reader community, but a much stronger online author–author community, founded upon practical support and encouragement. There are implications for the publishing industry as authors believe their publishers lack social-media expertise. The commercial benefits of maintaining a social-media presence are unclear for many authors.