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Record W4205467494 · doi:10.26881/jk.2021.12.14

Od „nie-miejsca” do „heterotopii”. Zagrożenie jako czynnik zmieniający status przestrzeni w "Dżumie" Alberta Camusa

2021· article· en· W4205467494 on OpenAlexaboutno aff
Karol Rawski

Bibliographic record

VenueJednak Książki Gdańskie Czasopismo Humanistyczne · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicCentral European Literary Studies
Canadian institutionsnot available
Fundersnot available
KeywordsUtterancePlague (disease)VoiceHistoryPsychologyTheologyLinguisticsPhilosophyAncient history

Abstract

fetched live from OpenAlex

Words can create reality which is why they sometimes arouse fear in people, especially when they are denominations of threatening forces, unfavourable to men.
 In my article, I would like to discuss the problem of pestilence and the utterance hereof in Albert Camus’ Plague. Why did Dr. Rieux hesitate to clearly utter the threat? Why did other characters in the novel have no problem voicing “epidemic” out loud? And above all, what are the consequences of uttering a disease? How the word “plague” destroyed the existing spatial status of Oran as a non-place; how it became a gate to building a new spatial status structure based on a heterotopic labyrinth, which, from the moment of utterance of this terrible term, was completely subjugated to the plague. How does the word escape the doctor’s room? What is the role of the figure of window in the process of the name overcoming barriers and passing from the level of language to the level of reality? And finally, whether the rhythm analysis can become an answer, deafening and counteracting the still resounding threat contained in the word.

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: none
Teacher disagreement score0.734
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.019
GPT teacher head0.291
Teacher spread0.272 · 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
Published2021
Admission routes1
Has abstractyes

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