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Record W7112645858

Key words: Lower Carniolan dialect group, South White Carniolan dialect, Srednji Radenci, Sodevci, Dečina, Prelesje, transitional speech, dialectology

2025· article· sl· W7112645858 on OpenAlexaboutno aff

Bibliographic record

VenueRepository of the University of Ljubljana (University of Ljubljana) · 2025
Typearticle
Languagesl
FieldArts and Humanities
TopicLinguistics and language evolution
Canadian institutionsnot available
Fundersnot available
KeywordsDialectologyKey (lock)White (mutation)Nova scotia
DOInot available

Abstract

fetched live from OpenAlex

Magistrsko delo obravnava južnobelokranjsko narečje, ki sinhrono spada v dolenjsko narečno skupino. Prispevek predstavlja na novo zbrano narečno gradivo v izbranih krajih ob reki Kolpi, za katera se ugotavlja genealoška povezanost s kajkavskim narečjem hrvaškega jezika. Na terenu zbrano narečno gradivo se primerja z govori, ki se na hrvaški strani slovensko-hrvaške državne meje uvrščajo v kajkavsko narečno skupino. V teoretičnem delu sem na kratko opisala zgodovinske raziskave o belokranjskih govorih, geografske podatke, ki so vplivale na spremembe v narečnem govoru na območju Bele krajine, značilnosti in razlike med govori ipd. V empiričnem delu sem opisala potek zbiranja in obdelave gradiva. Nato sledi kratka predstavitev posameznega govorca in vseh štirih krajev (Srednji Radenci, Sodevci, Dečina, Prelesje). Podan je jezikoslovni opis krajevnih govorov na osnovi obširnega gradiva, ki je bilo na novo zbrano. Podani so glavni glasoslovni kriteriji, ki utemeljujejo uvrstitev govorov med prehodne govore, dodana sta narečni inventar in distribucija ter tabelni prikaz glavnih issln. odrazov. Za primerjavo je dodano gradivo kontrolne točke Blaževci, ki se uvršča med vzhodnogoranske govore kajkavske narečne skupine. Na koncu so v povzetku zapisane sklepne ugotovitve narejene raziskave.

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), Science and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.163
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.003
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.165
Teacher spread0.158 · 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 designQualitative
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
Published2025
Admission routes1
Has abstractyes

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