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Record W4405099170 · doi:10.22215/etd/2024-16173

Wealth Drain and Value Transfer: A Study of the Mechanisms, Harms, and Beneficiaries of the Sanctions Regime on Iran

2024· dissertation· en· W4405099170 on OpenAlexaff
Helyeh Doutaghi

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Sanctions and International Relations
Canadian institutionsCarleton University
Fundersnot available
KeywordsSanctionsPolitical scienceContext (archaeology)SovereigntyEconomic sanctionsPoliticsPolitical economyUnintended consequencesInternational lawInternational relationsValue (mathematics)Law and economicsDevelopment economicsLawEconomicsGeography

Abstract

fetched live from OpenAlex

This dissertation offers a critical examination of the practices and techniques of economic sanctions as 'slow and structural violence' in and through international law.These coercive measures have been constructed and deployed by the global North to impose de-development and facilitate wealth drain from the periphery to the imperial core.At its heart, this study challenges the conventional and reductionist understanding of economic sanctions as 'peaceful alternatives to war', and their systematically deliberate violence as 'unintended consequences'.Grounded in the context of the sanctions regime against Iran, my research traces its origins to 1950s-when Iran first asserted sovereignty over its natural resources-and examines the intensification of these sanctions after the 1979 Iranian revolution.I develop a critical account of sanctions, examining how these coercive measures operate as legal, political, and economic instruments of imperialism.This involves a comprehensive critical analysis of the violence inherent within the structures of these sanctions, offering a detailed examination of their mechanisms, justifications, harms, and beneficiaries.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.368
Threshold uncertainty score0.471

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.028
GPT teacher head0.239
Teacher spread0.212 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2024
Admission routes1
Has abstractyes

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