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Record W2149890413 · doi:10.5210/fm.v19i2.4825

Life on automatic: Facebook's archival subject

2014· article· en· W2149890413 on OpenAlexaff
Liam Mitchell

Bibliographic record

VenueFirst Monday · 2014
Typearticle
Languageen
FieldComputer Science
TopicDigital Media and Philosophy
Canadian institutionsTrent University
Fundersnot available
KeywordsReinterpretationSubject (documents)Argument (complex analysis)IdeologyThe InternetSociologyOntologySocial mediaReading (process)World Wide WebTimelineEpistemologyComputer scienceMedia studiesInternet privacyAestheticsPoliticsPolitical scienceLawHistoryPhilosophy

Abstract

fetched live from OpenAlex

Facebook’s ideology rests on and results in a particular ontology: Mark Zuckerberg wants the site to help create an “open” and “connected” world. This article explains the implications of this world-changing mission by examining services that map the Facebook user’s path across the Internet (like Connect) and archive the user’s life (like Timeline). Reading these services through the psycho-ontological claims of Baudrillard and Derrida suggests that Facebook’s open, connected individual – the archival subject – is bent towards convenience and interest. Pairing these readings with a reinterpretation of Heidegger’s philosophy of technology in terms specific to Facebook, the article argues that the archival subject provides evidence of a view of the world characterized predominantly by an orientation toward browsing rather than use or control. Facebook should be analyzed in terms of this pre-theoretical understanding of the world – one that it both symptomatizes and institutes. In advancing this argument, the article calls attention to the broader (ontological) and more intensive (subjective) correlates of more traditional (politico-economic or ideological) criticisms of social media.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0150.024
Scholarly communication0.0130.009
Open science0.0010.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0060.001

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 head0.016
GPT teacher head0.217
Teacher spread0.200 · 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 designQualitative
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

Citations5
Published2014
Admission routes1
Has abstractyes

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