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Record W2970769854 · doi:10.1017/s0003055419000376

Investment in the Shadow of Conflict: Globalization, Capital Control, and State Repression

2019· article· en· W2970769854 on OpenAlexaff
Mehdi Shadmehr

Bibliographic record

VenueAmerican Political Science Review · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Conflict and Governance
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsEconomicsEconomic systemCapital (architecture)GlobalizationMarket economyExpropriationCollective actionCapital accumulationHarmShadow (psychology)Investment (military)Political economyPoliticsPolitical scienceHuman capital

Abstract

fetched live from OpenAlex

In conflict-prone societies, the fear of expropriation that accompanies a regime change reduces capital investment. These reductions in investments, in turn, harm the economy, amplifying the likelihood of regime change. This article studies the implications of these feedback channels on the interactions between globalization, capital control, state repression, and regime change. I show that processes that facilitate capital movements (e.g., globalization, economic modernization, and technologies that reduce transportation costs) amplify the likelihood of regime change in conflict-prone societies and strengthen the elite’s demand for a strong coercive state. In particular, to limit their collective action problem and manage the political risk of regime change, capitalists support a state that imposes capital control. We identify two conflicting forces, the Boix Effect and the Marx Effect, which determine when capital control and state repression become complements (Nazi Germany) or substitutes (Latin American military regimes) in right-wing regimes.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.915
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.004
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 head0.014
GPT teacher head0.345
Teacher spread0.331 · 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 designTheoretical or conceptual
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

Citations20
Published2019
Admission routes1
Has abstractyes

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