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Record W2781533112 · doi:10.7146/pas.v32i78.102953

Fra bakteriernes perspektiv. Positioner i forholdet mellem litteratur og naturvidenskab belyst gennem Mark Twains “3,000 Years Among the Microbes” og Christian Böks “The Xenotext Experiment”

2018· article· en· W2781533112 on OpenAlexaboutno aff
Jens Lohfert Jørgensen

Bibliographic record

VenuePassage - Tidsskrift for litteratur og kritik · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicCybernetics and Technology in Society
Canadian institutionsnot available
Fundersnot available
KeywordsTypologyPerspective (graphical)History of religionsCharacter (mathematics)PoetryPhilosophyLiteratureSociologyEpistemologyArtReligious studiesAnthropologyVisual arts

Abstract

fetched live from OpenAlex

Jens Lohfert Jørgensen: “From the Perspective of Bacteria. Position in the Relationship Between Literature and Science Illustrated by Mark Twain’s 3,000 Years Among the Microbes and Christian Bök’s The Xenotext Experiment”This article discusses how literature administers scientific notions about bacteria based on two curious examples: Mark Twain’s uncompleted novel 3,000 Years Among the Microbes (1905) and the Canadian experimental poet Christian Bök’s work The Xenotext Experiment (2007-). There are some noteworthy correspondences between the works’ engagement with bacteria: They both attempt to establish a microbial perspective (Twain by using a cholera bacterium as narrator, Bök by trying to make a bacterium produce a poem), they both use this engagement to experiment with literary form, and they are both closely related to the natural sciences. On the backdrop of these correspondences, the article sketches out a typology of five modal positions in the relationship between literature and science: Mediating, satirical, allegorical, ontological, ludic. The typology has a local character, but can form a starting point of the discussion of further modal positions.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.252
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0030.003
Scholarly communication0.0020.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.011
GPT teacher head0.226
Teacher spread0.214 · 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.

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
Published2018
Admission routes1
Has abstractyes

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