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Record W4312474467 · doi:10.22378/kio.2022.2.149-165

Bakhchisarai coffee houses in the middle of the 19th –early 20th centuries

2022· article· en· W4312474467 on OpenAlexaboutno aff
Elviz E. Osmanov

Bibliographic record

VenueCrimean Historical Review · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicNight-time city culture
Canadian institutionsnot available
Fundersnot available
KeywordsAnnexationQuarter (Canadian coin)Ancient historyTurkishEmpirePeninsulaGeographyEconomic historyNegotiationMiddle classHistoryEconomyPolitical scienceArchaeologyPoliticsLaw

Abstract

fetched live from OpenAlex

Bakhchisarai, one of the oldest cities in Crimea, was founded in the first quarter of the 16th century. The public buildings of Bakhchisarai in the 16th–18th centuries: Turkish baths, fountains and coffee houses played an important role in the life of a Muslim. In the Crimea, coffee became widespread during the period of the Crimean Khanate, becoming one of the traditional drinks in the region. Coffee houses were a place of rest for the townspeople in the evenings. Coffee houses were of two types: for merchants in a convenient area and for a lower class. The city of Bakhchisarai turned into a district town in the Tauride province after the annexation of the Crimea to the Russian Empire. On the widespread distribution of coffee establishments on the territory of the peninsula in the nineteenth and early twentieth centuries are evidenced by a large number of sources. For the inhabitants of the city, coffee houses played a significant role in social and cultural life until the middle of the 20th century, being a kind of a club, a place of meetings and negotiations. This article analyzes the dynamics of growth and development of coffee establishments in Bakhchisarai, based on archival data and published materials. The purpose of this publication is a detailed examination of the issues of construction, reconstruction and rental of premises intended for coffee shops as commercial and industrial establishments in the city in the late 19th and early 20th centuries, based on the materials of the funds of Bakhchisarai City Council. The author comes to the conclusion that successes were achieved in solving the economic issues of Bakhchisarai during the specified period of time thanks to the activities of the City Council and private initiative.

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)0.001
metaresearch head score (Gemma)0.001
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.902
Threshold uncertainty score0.897

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.095
GPT teacher head0.300
Teacher spread0.205 · 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
Published2022
Admission routes1
Has abstractyes

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