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Record W4285090605 · doi:10.1186/s40878-022-00299-9

Transnational voting rights and policies in violent democracies: a global comparison

2022· article· en· W4285090605 on OpenAlexaff
Benjamin Nyblade, Elizabeth Iams Wellman, Nathan W. Allen

Bibliographic record

VenueComparative Migration Studies · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsSt. Francis Xavier University
Fundersnot available
KeywordsVotingEmigrationPolitical sciencePoliticsPolitical economyLawEconomics

Abstract

fetched live from OpenAlex

Abstract In recent decades more than one hundred countries have enfranchised their diasporas, allowing emigrants to vote from abroad. However, this widespread formal recognition of extraterritorial voting rights does not always lead to increased participation of emigrants in home country politics. Migrant-sending countries have complex relationships with their diasporas, and this relationship is particularly fraught for countries with endemic violence. This article leverages a new dataset documenting the adoption and implementation of extraterritorial voting rights and restrictions for 195 countries from 1950 to 2020 to demonstrate how transnational voting rights and policies in violent democracies differ from other regimes. While violent democracies extend transnational voting rights to their emigrants at rates comparable to other regime types, they are less likely to implement those rights, and when they do implement them, they are more likely to restrict them to insulate domestic politics from external influence.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.104
GPT teacher head0.430
Teacher spread0.326 · 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 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

Citations10
Published2022
Admission routes1
Has abstractyes

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