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Record W4313432547 · doi:10.33137/ijournal.v8i1.39906

The Neodiluvian Age

2022· article· en· W4313432547 on OpenAlexvenueno aff
James P. Mackey

Bibliographic record

VenueThe iJournal Student Journal of the Faculty of Information · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsnot available
Fundersnot available
KeywordsCapital (architecture)Product placementCultural capitalNew mediaDistribution (mathematics)Digital mediaPrecarityThe InternetProduct (mathematics)SociologyMedia industryAdvertisingPopular mediaBusinessMedia studiesPublic relationsPolitical scienceSocial scienceHistoryGender studiesComputer scienceLaw

Abstract

fetched live from OpenAlex

This paper examines the “new/old media” dichotomy as a product of capital’s control over cultural labour. It argues that any meaningful distinction can only be drawn between their distribution methods rather than their content. Any perceived differences in the content of new and old media exist only in the minds of audiences and creators rather than in the text of the media. In this way, these differences constitute a phantom divide. The development of internet-based advertisement models takes advantage of these novel distribution methods but also homogenizes new media, compressing all forms into mere “content.” This compression is then exploited by capital holders to limit worker rights and labour costs. I argue that the phantom divide is a major contributing factor to the precarity of cultural labour in the digital age, substituting traditionally valuable celebrity for tenuously valued “efame,” and trampling workplace benefits afforded to labourers in traditional media industries.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.009
Scholarly communication0.0050.005
Open science0.0000.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.002

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 head0.034
GPT teacher head0.314
Teacher spread0.280 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2022
Admission routes1
Has abstractyes

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