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Record W2995489336 · doi:10.5604/01.3001.0013.6219

Національна ідентичність як сфера сакрального у творах канадських авторів українського походження

2019· article· en· W2995489336 on OpenAlexaboutno aff
Тетяна Шадріна

Bibliographic record

VenueStudia Ucrainica Varsoviensia · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicUkrainian Cultural and Linguistic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsUkrainianFatherlandValue (mathematics)National identityMythologyIdeologySociologyContext (archaeology)Identity (music)AestheticsHistoryLawPolitical scienceLiteratureLinguisticsPhilosophyArtArchaeology

Abstract

fetched live from OpenAlex

The article is devoted to the study of value systems which determine the sacred dimension of the socio-cultural experience of the people. Sacramental is considered not in the religious context, but as the highest value that lies outside the understanding. Sacramental is an indicator of the state of culture. The change in the social environment, ideological orientations (which is inherent to immigrants at one time or another) causes a change in sacred values. It is proved that, having fallen into an inocultural environment, a person strives to preserve their national identity, which helps to get „rooted” in the new place. It also provides preserving their unique image in the alien socio-cultural environment and guarantees a sense of security, stability, cultural uprooting. In the works of Canadian authors of Ukrainian origin, the sacred space of the individual’s personal existence is determined by the higher spiritual values created by his own people; and hence – is formed due to the sensation of religious representations, the fatherland’s land of Ukraine, the native language, elements of national culture and history, common national myths, historical memory.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.996
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0040.001
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0200.006

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 head0.030
GPT teacher head0.330
Teacher spread0.300 · 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
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
Published2019
Admission routes1
Has abstractyes

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