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Record W3089121238 · doi:10.1353/jod.2020.0052

How a Dictator became Vulnerable

2020· article· en· W3089121238 on OpenAlexaff
Lucan A. Way

Bibliographic record

VenueJournal of democracy · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical and Contemporary Political Dynamics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDictatorPolitical scienceDevelopment economicsPsychologyPolitical economyEconomicsLawPolitics

Abstract

fetched live from OpenAlex

Following Belarus’s fraudulent presidential election on August 9, hundreds of thousands took to the streets, creating an unprecedented threat to the rule of Alyaksandr Lukashenka. Protest leaders have explicitly distinguished their new movement from the “color revolutions” that have taken place in other postcommunist countries. Rather than calling for major changes in geopolitical orientation, they have focused their demands on free and democratic elections together with a return to the constitutional status quo that existed before Lukashenka. The dictator himself has miscalculated by underestimating opposition-unifier Sviatlana Tsikhanouskaya. Even if Belarus’s antirevolutionary uprising fails to oust Lukashenka, it has destroyed the perception that he is invulnerable to opposition challenge. Belarusian democracy may well be on the horizon.

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)0.009
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.040
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.020
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0400.027
Scholarly communication0.0140.012
Open science0.0010.010
Research integrity0.0070.014
Insufficient payload (model declined to judge)0.0170.006

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 head0.040
GPT teacher head0.203
Teacher spread0.163 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations9
Published2020
Admission routes1
Has abstractyes

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