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Record W7067580602

Miejsce o wielu twarzach : oblicza uniwersytetu w literaturze współczesnej

2016· other· en· W7067580602 on OpenAlexaboutno aff

Bibliographic record

VenueJagiellonian University Repository (Jagiellonian University) · 2016
Typeother
Languageen
FieldBusiness, Management and Accounting
TopicIntellectual Capital and Performance Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsChristian ministryAction (physics)Spanish Civil WarCharacter (mathematics)Government (linguistics)Relation (database)
DOInot available

Abstract

fetched live from OpenAlex

The article shows the university as an institution, as well as a place where one gains experience, in the optics of contemporary autobiographical novels: Lost in translation by Eva Hoffman, "My zdies’ emigranty" by Manuela Gretkowska, and a novel "The Ministry of Pain" by Dubravka Ugresić, in which there are some signs of autobiographical inspirations. Even though the university is not a very important place for the action of the mentioned books, it is significant for the characters. For Hoffman, American universities (firstly Rice, then Cambridge) were the places, where she felt comfortable, not as a stranger (as she did most of her life
\nin Canada). For Gretkowska the university had only an official, institutional image: it constricted her scientific interests by the major she chose, so she needed to find some consensus in her life. The most complicated situation was the one of Tanja Lucić - the main character of "The Ministry of Pain". For her, official relations mixed up with the private ones, and personal problems connected with the civil war trauma, complicated her life and made the university a place of recovery after a difficult experience of losing the fatherland. The article sums up these very different points of view as an interesting collage of the university experiences.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), 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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.032
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.006

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 head0.006
GPT teacher head0.162
Teacher spread0.156 · 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
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
Published2016
Admission routes1
Has abstractyes

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