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Record W2787501143 · doi:10.7146/ntik.v2i3.25964

Faglitterære fortællinger : Hvad gør de, hvad kan de?

2013· article· da· W2787501143 on OpenAlexaff
Rune Eriksson

Bibliographic record

VenueNordisk Tidsskrift for Informationsvidenskab og Kulturformidling · 2013
Typearticle
Languageda
FieldArts and Humanities
TopicDiscourse Analysis in Language Studies
Canadian institutionsDomtar (Canada)
Fundersnot available
KeywordsHumanitiesPhilosophyArt

Abstract

fetched live from OpenAlex

Artiklen fokuserer på den litterære genre creative nonfiction. På dansk har denne genre endnu ikke noget navn, men på baggrund af otte danske værker inden for genren samt en diskussion af den amerikanske terminologi inden for området foreslås betegnelsen faglitterære fortællinger eller alternativt fortællende faglitteratur. Med de samme otte værker som cases undersøges dernæst, hvilke elementer genren typisk består af, samt hvilke hovedkvaliteter den har at tilbyde læserne. Med henblik på analysen af elementerne konstrueres en facetmodel, mens hovedkvaliteterne overfor læserne analyseres på baggrund af en teori om læseformer. Den første undersøgelse viser, at genren i udpræget grad fremtræder som en hybrid mellem skønlitteratur og faglitteratur, men at den i visse henseender er en radikal genre snarere end en hybrid. I forhold til læseren konkluderes det, at genren tilbyder såvel faktuel viden om verden som æstetiske (læse)oplevelser, men også at læseren, i kraft af hybridformen, må være i stand til at veksle mellem forskellige læsestrategier under læsningen. Afslutningsvis karakteriseres værkerne i forhold til velkendte type- og genrebestemmelser i faglitteratur og skønlitteratur.

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)0.001
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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.476
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0040.001
Scholarly communication0.0030.006
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.019
GPT teacher head0.267
Teacher spread0.248 · 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; both teacher heads agree on what is shown here.

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
Published2013
Admission routes1
Has abstractyes

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