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Record W4293117476 · doi:10.4000/books.pupo.30928

“A Divergent Elsewhere”: Erasure and Layering in Tree of Codes by Jonathan Safran Foer and The Desert by Jen Bervin

2017· book-chapter· en· W4293117476 on OpenAlexaff
Gwen Le Cor

Bibliographic record

VenuePresses universitaires de Paris Nanterre eBooks · 2017
Typebook-chapter
Languageen
FieldSocial Sciences
TopicIntelligence, Security, War Strategy
Canadian institutionsSafran Electronics (Canada)
Fundersnot available
KeywordsLayeringErasureDesert (philosophy)Tree (set theory)GenealogyHistoryComputer scienceMathematicsLawBiologyPolitical scienceCombinatoricsBotanyProgramming language

Abstract

fetched live from OpenAlex

In an interview with the New York Times, Jonathan Safran Foer described Tree of Codes as a kind of unplugged work of art: “On the brink of the end of paper, I was attracted to the idea of a book that can’t forget it has a body.” A book, then, that refused to become an electrical current. This might seem a curiously paradoxical place to start with when focusing on the digital, yet, in the very conception of his work, Foer produced a hybrid object which not only challenges what a book is, but a...

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)0.004
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 score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.005
Scholarly communication0.0030.008
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0060.002

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 head0.014
GPT teacher head0.248
Teacher spread0.234 · 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
Published2017
Admission routes1
Has abstractyes

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