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The Text as a Scalable Structure

2007· article· en· W2476403185 on OpenAlexaff
Florentina Armaselu

Bibliographic record

VenueThe International Journal of the Book · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicMedia, Communication, and Education
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsComputer scienceNatural language processing

Abstract

fetched live from OpenAlex

Abstract: Inspired by the fictional construction of Stephenson (2000), an “anfractuous ” book able to answer reader’s questions by self-expansion and ramification, and functioning on the principle “tell me more about this subject”, our project deals with the construction of an interface allowing several levels of detail and implying different “scales ” of textual rep-resentation. By revisiting a number of traditional narrative paradigms, the paper will discuss some new possible ways of storytelling determined by this kind of textual development and exploration. Greenblatt (2004) suggests that in “Venus and Adonis”, Shakespeare uses a way of approaching or distancing the reader from a character or situation by increasing or decreasing his “physical and emotional proximity”. In some passages, we seem to be at a great distance from the two protagonists while in other, we can observe the tiniest details, as in a view evoking the “zoom in ” perspective. On the other hand, in his analysis of Evelyne Waugh’s “Vile Bodies”, Alan Palmer (2003) uses the term “behaviorist narrative ” defined

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.534
Threshold uncertainty score0.618

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.015
GPT teacher head0.339
Teacher spread0.324 · 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 teacher head, 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

Citations1
Published2007
Admission routes1
Has abstractyes

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