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Conveying Ćeif: Three Croatian Folklore and Folklife Writings on Bosniak Coffee Culture

2020· article· en· W3110689821 on OpenAlexafffund
Dorian Jurić

Bibliographic record

VenueFOLKLORICA - Journal of the Slavic East European and Eurasian Folklore Association · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicPhilippine History and Culture
Canadian institutionsMcMaster University
FundersSocial Sciences and Humanities Research Council of CanadaMcMaster University
KeywordsFolkloreFolklifeBosnianContext (archaeology)FoodwaysHistoryPoliticsLiteratureCroatianFolkloristicsFolk cultureClassicsArtSociologyVisual artsLawArchaeologyPolitical scienceLinguisticsPhilosophy

Abstract

fetched live from OpenAlex

This article presents three short passages describing coffee and coffeehouse culture among Bosnian and Herzegovinian Muslims in the late nineteenth century. These texts are drawn from manuscripts collected by lay, Croatian folklore and folklife collectors who submitted them to two early collecting projects in Zagreb. The pieces are translated here for the first time into English and placed into historical and cultural context regarding the history of coffee culture in Bosnia and Herzegovina and the wider Ottoman Empire as well as the politics of folklore collection at the time. By using the Pan-Ottoman concept of ćeif as a theoretical lens, I argue that these early folklorists produced impressive folklife accounts of Bosniak foodways, but that these depictions inevitably enfolded both genuine interest and negative by-products of the wider politics of their era.

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)0.003
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0140.016
Scholarly communication0.0060.002
Open science0.0010.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.023
GPT teacher head0.234
Teacher spread0.211 · 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

Citations2
Published2020
Admission routes2
Has abstractyes

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