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Record W3175075103 · doi:10.1080/08865655.2021.1943495

Pandemic Borders of Post-Soviet De Facto States

2021· article· en· W3175075103 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Borderlands Studies · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicPost-Soviet Geopolitical Dynamics
Canadian institutionsnot available
FundersRussian Science Foundation
KeywordsDe factoPolitical sciencePandemicPoliticsState (computer science)PhenomenonH1n1 pandemicPolitical economyDevelopment economicsCoronavirus disease 2019 (COVID-19)LawSociologyEconomics

Abstract

fetched live from OpenAlex

The article focuses on the phenomenon of post-Soviet de facto borders (viz. the borders of Abkhazia, the Donetsk People’s Republic, the Lugansk People’s Republic, Nagorno-Karabakh, South Ossetia, and Transnistria) in the conditions of the COVID-19 pandemic. The author outlines similarities and differences of these de facto borders in comparison with internationally recognized ones and compares border policies implemented by individual post-Soviet de facto states. While de facto states utilized their borders to combat the pandemic largely in the same ways as recognized states did, their pandemic border regimes were less legitimate for the international community and thus de facto states were more dependent on cross-border relations with their “patrons,” having no other viable options. The author also argues that even de facto states with similar geographical and political conditions chose partially different policies for managing pandemic bordered restrictions.

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.

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)0.004
Version: codex-gemma-dda1882f352aValidation 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 score0.599
Threshold uncertainty score0.466

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.030
GPT teacher head0.373
Teacher spread0.344 · 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