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Record W7001571095

Latviskās identitātes meklējumi 20.gadsimta 90.gadu prozā

2018· dissertation· lv· W7001571095 on OpenAlexaboutno aff

Bibliographic record

VenueE-resource repository of the University of Latvia (University of Latvia) · 2018
Typedissertation
Languagelv
FieldSocial Sciences
TopicEuropean Linguistics and Anthropology
Canadian institutionsnot available
Fundersnot available
KeywordsWork (physics)Identification (biology)Process (computing)
DOInot available

Abstract

fetched live from OpenAlex

Maģistra darbs analizē latviskās identitātes meklējumus 20. gadsimta 90. gadu prozā. Padomju Savienības sabrukums 1991.gadā iezīmēja politiski un ekonomiski nedrošu periodu. Šis periods rada identitātes krīzi. Tā laika rakstnieki reflektē par latvisko identitāti, vēsturi un nākotnes perspektīvām. Maģistra darbā analizēti rakstnieku Egīla Ermansona, Alberta Bela, Gundegas Repšes un Noras Ikstenas darbi. Maģistra darbs analizē kā jautājumi par latvisko identitāti, vēstures interpretācijām un nākotnes perspektīvām atspoguļojas 20. gadsimta 90 gadu prozā.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.077
Threshold uncertainty score0.258

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.005
Science and technology studies0.0030.001
Scholarly communication0.0040.002
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0770.022

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 spread0.215 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2018
Admission routes1
Has abstractyes

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