MétaCan
Menu
Back to cohort
Record W4283170636 · doi:10.1017/nps.2021.92

Civic Dominion: Nation-Building in Post-Soviet Azerbaijan over 25 Years of Independence

2022· article· en· W4283170636 on OpenAlexaboutno aff
Laurence Broers, Ceyhun Mahmudlu

Bibliographic record

VenueNationalities Papers · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicSoviet and Russian History
Canadian institutionsnot available
Fundersnot available
KeywordsDominionIdeologyIndependence (probability theory)State-buildingNexus (standard)Nation-buildingEthosPolitical scienceTerritorial integrityQuarter (Canadian coin)State (computer science)Political economyEconomic historyPoliticsSociologyLawHistorySovereigntyArchaeology

Abstract

fetched live from OpenAlex

Abstract This article surveys nation-building in post-Soviet Azerbaijan over the country’s first quarter-century of restored independence. It examines the core dimensions of ethno-demographic and national minority issues, language policy, and the role of religion in the development of the state’s formal ideology Azerbaycançılıq (Azerbaijanism). The article highlights the nexus of nation-building and regime-building as a dominant trend over the last two decades, generating what we term “civic dominion”: the domination of a regime tradition, legitimated through the imagery and ideology of civic nationhood. Finally, the article considers the role of the Armenian-Azerbaijani conflict as a long-standing exception to the ostensibly civic ethos of post-Soviet Azerbaijani nation-building.

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 score0.063
Threshold uncertainty score0.124

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 studies0.0020.002
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0000.001
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 head0.016
GPT teacher head0.283
Teacher spread0.267 · 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

Citations14
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueNationalities PapersSame topicSoviet and Russian HistoryFrench-language works237,207