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Record W2137310528 · doi:10.1017/s0067237800020981

National and Other Identities in Bukovina in Late Austrian Times

2004· article· en· W2137310528 on OpenAlexaff
Fred Stambrook

Bibliographic record

VenueAustrian History Yearbook · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicHistorical Geopolitical and Social Dynamics
Canadian institutionsUniversity of WinnipegUniversity of Manitoba
Fundersnot available
KeywordsFoothillsNationalityGeographyPopulationEmpireSkyAncient historyArchaeologyHistoryCartographyDemographyImmigrationSociology

Abstract

fetched live from OpenAlex

Many years ago, Arthur J. May wrote, “Only the Bucovina provided a patch of blue in the beclouded nationality sky of Austria.” Without going into the comparative aspect of this assertion, the object of this study is to ascertain to what extent May's statement correctly reflects the complex relationships of the ethnoculrural or national groups in Bukovina. How blue was the sky really? Acquired by Austria in 1774–75, Bukovina prior to 1918 was a small Crownland in the northeastern corner of the Austrian Empire. It bordered on Hungary, Romania, the Russian Empire, and the Austrian province of Galicia. Its area was about 410,000 square kilometers, and its population in 1910 was just over 800,000. Some of the land was rolling and fairly fertile countryside, especially in the north and east, merging into the foothills that in turn gave way to the Carpathian Mountains in the south and west. Much of Bukovina was forested. The estates of the large landowners, sometimes with a palace or large manor house, stood in glaring contrast to the small landholdings of the peasantry and their cramped housing. The capital, Czernowitz (Chernivtsi), with a population in 1910 of around 87,000, was the only sizable city.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.004
Scholarly communication0.0040.003
Open science0.0000.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.034
GPT teacher head0.279
Teacher spread0.245 · 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 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

Citations9
Published2004
Admission routes1
Has abstractyes

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