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Record W2567563128 · doi:10.1353/vpr.2016.0043

The Decadent Archive and the Long History of New Media

2016· article· en· W2567563128 on OpenAlexvenueno aff

Bibliographic record

VenueVictorian periodicals review · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicDigital Humanities and Scholarship
Canadian institutionsnot available
Fundersnot available
KeywordsDecadenceModernityReading (process)HistoryMainstreamLiteratureReflexivityAssertionNew mediaDigital mediaMedia studiesArtSociologyAnthropologyComputer sciencePhilosophyEpistemology

Abstract

fetched live from OpenAlex

Responding to the assertion of this special issue, that our “new media moment” has a long history, this article looks at one particular moment in 1890s when theories of decadence within British Aestheticism led to experiments in the periodical press. These experiments were conscious attempts to investigate how print media influenced perceptions of both literary content and the cultural practices of modernity. Specifically, I argue that Leonard Smithers’s publication of the short-lived Savoy in 1896 offers an interesting model of self-aware critical reflection for our own contemporary experiments with the digital archive. I compare Smithers’s periodical with the example of The Yellow Nineties Online (www.1890s.ca), a digital archive with its own self-conscious approach that allows for a decadent space of self-reflexive conversation about media circulation in its printed past and digital future. Rather than reading our current new media moment as the end of a previous tradition, I propose that we in the humanities have an opportunity, similar to Smithers’s in the 1890s, to archive our own media moment with digital texts that tell their stories from a self-reflexive, ironic, and mutable decadent perspective.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.996
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0040.020
Scholarly communication0.0100.017
Open science0.0010.004
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0050.001

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 head0.046
GPT teacher head0.236
Teacher spread0.190 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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

Citations0
Published2016
Admission routes1
Has abstractyes

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