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Record W1994897098 · doi:10.2478/muso-2014-0009

Belarusian Traditional Culture in the Legacy of Oskar Kolberg

2014· article· en· W1994897098 on OpenAlexaboutno aff
Anastasiya Niakrasava

Bibliographic record

VenueMusicology Today · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicPolish Historical and Cultural Studies
Canadian institutionsnot available
Fundersnot available
KeywordsEthnographyMusicaloskarSubject (documents)HistoryQuarter (Canadian coin)HistoriographyArt historyArtVisual artsLibrary scienceArchaeologyComputer science

Abstract

fetched live from OpenAlex

Abstract The article examines the subject of Belarusian musical and ethnographic materials collected by Oskar Kolberg. The materials on Belarusian folk culture, which were collected by the researcher throughout his whole life, were published almost 80 years after his death in Volume 52 Belarus–Polesie, while some of them are also to be found in Volume 53 Lithuania. Thus, the geography of these materials extends far beyond the borders of contemporary Belarus. However, individual regions of the country are not equally represented. Using the works of his predecessors, Kolberg compiled information about the culture and ethnography of Belarus and supplemented it with his own research. The author of this article divides the materials used to compile Volume 52 into two unequal groups: publications of other authors and the personal field notes of Kolberg (together with the materials sent to him by correspondents). The latter group, which constitutes more than a quarter of all the materials and is essential for assessing the Belarusian achievements of the Polish ethnographer, has been analysed in the article. The abundance of Kolberg’s own transcriptions of music in the volume makes his work into one of the key sources in 19th-century Belarusian musical historiography The author also puts forward a hypothesis concerning the Belarusian beginnings of Kolberg’s entire collecting activity.

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 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 score0.747
Threshold uncertainty score0.397

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.047
GPT teacher head0.275
Teacher spread0.229 · 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 teacher head, 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
Published2014
Admission routes1
Has abstractyes

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