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Record W2950758213 · doi:10.1017/nps.2018.27

Bridging Past and Present Traumas: The Emergence of Kosovo Serb Ethnoscape in the Dynamic Interaction between the Enclaved Environment and History Textbooks’ Content

2019· article· en· W2950758213 on OpenAlexaff
Émilie Fort

Bibliographic record

VenueNationalities Papers · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicEducator Training and Historical Pedagogy
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsDialogicNarrativeIdentity (music)Context (archaeology)Relation (database)SociologyContent (measure theory)SerbianLiteratureHistoryAestheticsArtLinguisticsPedagogyPhilosophyArchaeologyComputer science

Abstract

fetched live from OpenAlex

Abstract This article deals with the use of history textbooks imported from Serbia in the specific context of Kosovo Serb enclavement. It provides a content analysis of history textbooks used by Kosovo Serb pupils in Kosovo in terms of their contribution to Kosovo Serb collective identity building. This article focuses on the interaction between the enclaved environment within which Kosovo Serbs have lived since 1999 and the narratives contained in the history textbooks, to highlight how this interaction influences the way Kosovo Serbs consider their identity. First, I start by showing that history textbooks used by Kosovo Serbs in Kosovo emphasize religious identity. Next, I argue that dialogic relation between past and present, understood through the dynamic interaction between the enclaved environment and history textbook narratives, contributes to the emergence of enclaves as ethnoscapes.

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)0.006
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 score0.011
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0090.016
Scholarly communication0.0070.005
Open science0.0010.011
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.118
GPT teacher head0.336
Teacher spread0.217 · 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

Citations1
Published2019
Admission routes1
Has abstractyes

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