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Record W3111065790 · doi:10.21153/psj2020vol6no1art872

Social Media and Modernist Authority: The Hauntology of Facebook

2020· article· en· W3111065790 on OpenAlexaff
Will Best

Bibliographic record

VenuePersona Studies · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicContemporary Literature and Criticism
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCultArgument (complex analysis)GeniusBiographySocial mediaSociologySpace (punctuation)Exposition (narrative)AestheticsMedia studiesArtLiteraturePhilosophyComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

Highly biographical Modernist author profiles on Facebook seem to adopt or encourage a purely biographical, Genius Cult-esque understanding of the relationship between an author and that author's work. This is initially problematic, as authorial intent is a particularly complex issue of consideration for many of the authors currently haunting Facebook. This article thus establishes the paradoxical view on author-ity of three such authors -- T. S. Eliot, Marianne Moore, and James Joyce -- and examines how such Facebook profiles undermine and simplify the arguments made by these authors both through their critical and creative works. It then suggests that, by mere nature of being present on Facebook, these profiles may indeed engage in teasing out the very same paradox that these Modernists proposed in the first place, using Derrida's Hauntology to examine Facebook as a textual space both of biography and self-prosthesis. The argument ultimately seeks to propose that all Facebook users are indeed just such spectres haunting digital spaces.

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)0.004
metaresearch head score (Gemma)0.006
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: Other · Consensus signal: Other
Teacher disagreement score0.013
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.001
Science and technology studies0.0110.073
Scholarly communication0.0130.013
Open science0.0010.007
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0030.000

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 head0.196
GPT teacher head0.305
Teacher spread0.109 · 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
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

Citations0
Published2020
Admission routes1
Has abstractyes

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