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Record W3010902413 · doi:10.1515/openps-2020-0001

Using Czechoslovakia and Yugoslavia to predict the outcome of the dissolution of states: factors that lead to internal conflict and civil war

2020· article· en· W3010902413 on OpenAlexaff
Thomas J. Kennedy

Bibliographic record

VenueOpen Political Science · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicPost-Soviet Geopolitical Dynamics
Canadian institutionsMcGill University
Fundersnot available
KeywordsPoliticsGovernment (linguistics)Territorial integrityPolitical scienceSpanish Civil WarSettlement (finance)CzechInternal conflictPolitical economyLawSociologyBusinessSovereignty

Abstract

fetched live from OpenAlex

Abstract During the process of the dissolution of countries, there exist multiple critical junctures that lead to the partition of the territory, where the different groups cannot find a consensus on who rules and how to organize the government. The outcome of these crossroad decisions and political dynamics, who are often set-up centuries ago, either lead to conflict or relative peace between the nations and peoples who express opprobrium towards each other. The most recent cases of the divorce of Yugoslavia and Czechoslovakia have many similitudes and are therefore appropriate to attempt to theoretically analyze the essential difference between these two types of partitions. The Yugoslav situation led to War between the nations of Croatia, Bosnia, Slovenia and Serbia, with an estimated 140,000 citizens of the former Yugoslav Republics killed, while the Czechoslovak case led to an innocuous settlement of differences and the creation of the Czech Republic and Slovakia, who joined the European Union ten years later and saw zero casualties. It is worthwhile to study the relationship between the dissolution of states and conflict using the Czechoslovak and Yugoslav cases for three main reasons. First, the similitude of the two instances enables one to identify variables that bring the outcome of having either peaceful relations or conflict between divorcing nations. Second, it is possible to compare the opposing disposition of variables with other countries that faced dissolution at one moment in history. Third, the sources and research for the two events are extensive, but very seldom put into conflict, since the causes for dissolution in both instances seem patent and explicit, contrasting significantly in scope and depth. This paper may be an occasion to disprove the notion that unworkable forces were at play here and demonstrate that the situation could have skewed in either direction, even though those structural forces are what lay the groundwork of the situation devolving into conflict.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.570
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.121
GPT teacher head0.403
Teacher spread0.282 · 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.

Study designObservational
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
Published2020
Admission routes1
Has abstractyes

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