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Digital Paratext, Editorialization, and the Very Death of the Author

2014· book-chapter· en· W582821472 on OpenAlexaff
Marcello Vitali-Rosati

Bibliographic record

VenueAdvances in human and social aspects of technology book series · 2014
Typebook-chapter
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsContext (archaeology)EpistemologyCriticismParatextFunction (biology)SociologyHistoryLiteraturePhilosophyArt

Abstract

fetched live from OpenAlex

As shown by different scholars, the idea of “author” is not absolute or necessary. On the contrary, it came to life as an answer to the very practical needs of an emerging print technology in search of an economic model of its own. In this context, and according to the criticism of the notion of “author” made during the 1960–70s (in particular by Barthes and Foucault), it would only be natural to consider the idea of the author being dead as a global claim accepted by all scholars. Yet this is not the case, because, as Rose suggests, the idea of “author” and the derived notion of copyright are still too important in our culture to be abandoned. But why such an attachment to the idea of “author”? The hypothesis on which this chapter is based is that the theory of the death of the author—developed in texts such as What is an Author? by Michel Foucault and The Death of the Author by Roland Barthes—did not provide the conditions for a shift towards a world without authors because of its inherent lack of concrete editorial practices different from the existing ones. In recent years, the birth and diffusion of the Web have allowed the concrete development of a different way of interpreting the authorial function, thanks to new editorial practices—which will be named “editorialization devices” in this chapter. Thus, what was inconceivable for Rose in 1993 is possible today because of the emergence of digital technology—and in particular, the Web.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.587
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.007
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.263
Teacher spread0.255 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2014
Admission routes1
Has abstractyes

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