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Record W3009833761 · doi:10.17863/cam.48579

TAX DISPUTES IN INVESTOR-STATE ARBITRATION

2020· dissertation· en· W3009833761 on OpenAlexfundno aff
Rav Pratap Singh

Bibliographic record

VenueApollo (University of Cambridge) · 2020
Typedissertation
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Issues in Ukraine
Canadian institutionsnot available
FundersGovernment of CanadaCargillDuke Energy
KeywordsArbitrationState (computer science)BusinessLaw and economicsEconomicsInternational economicsPolitical scienceLawComputer science

Abstract

fetched live from OpenAlex

This thesis examines tax disputes adjudicated by investor-state tribunals. I argue that the nature of taxation – a compulsory levy – is unlike any other state regulatory measure such as an environmental or a public health measure. I suggest that tax-related investment disputes constitute a unique category of foreign investment disputes, and that investment tribunals should recognize them as such. Not all arbitral tribunals, however, acknowledge the distinct character of taxation which leads to inconsistent jurisprudence. Apart from the nature of tax, tax carve outs are another important factor that distinguish tax- related investment disputes from other investment disputes. I show that tax carve outs are included in IIAs in order to prevent overlap with tax treaties. Tax carve outs determine the scope of the tribunal’s jurisdiction, and limit the substantive obligations that are applicable to a state’s taxation measures; but since tax carve outs are worded differently and vary in scope, each arbitral tribunal needs to establish its jurisdiction carefully. While some tribunals have been careful to clearly demarcate their jurisdiction, others have been imprecise. An analysis of the arbitral awards reveals that the approaches of investment tribunals in tax- related investment disputes differ as to expropriation, fair and equitable treatment, and non- discrimination. For expropriation claims, some tribunals regard tax measures as a unique category and correctly set a high threshold for taxation measures to qualify as expropriation. With respect to non-discrimination and fair and equitable treatment claims, investment tribunals tend to assimilate tax measures to all other measures. These differences reflect not only the distinct nature of the obligations, but also tribunals’ failure to recognize that tax-related investment disputes constitute a unique category. In the future, it is likely that the lower threshold for fair and equitable treatment and non- discrimination will lead investors to rely primarily on these standards in tax-related investment disputes. Additionally, international tax law (ITL) has played a limited role in tax-related investment disputes. Investment tribunals, instead, prefer to rely on WTO jurisprudence in their analysis and findings. I argue that there are general principles of law in ITL which tribunals should include in their analysis.

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)0.016
metaresearch head score (Gemma)0.028
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: Other
Teacher disagreement score0.016
Threshold uncertainty score0.085

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.028
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.003
Science and technology studies0.0130.015
Scholarly communication0.0140.014
Open science0.0020.010
Research integrity0.0100.010
Insufficient payload (model declined to judge)0.0110.001

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 head0.017
GPT teacher head0.187
Teacher spread0.170 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

Explore more

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