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Record W4403072381 · doi:10.1002/iir.1554

Municipalities at the crossroads: Deciphering the nexus between municipal insolvencies and international investment mandates

2024· article· en· W4403072381 on OpenAlexvenueno aff
Qiang Ren, Jing Du

Bibliographic record

VenueInternational Insolvency Review · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicLocal Government Finance and Decentralization
Canadian institutionsnot available
Fundersnot available
KeywordsNexus (standard)Investment (military)BusinessInternational investmentPolitical scienceForeign direct investmentEngineeringLaw

Abstract

fetched live from OpenAlex

Abstract Navigating the convergence of domestic governance and international investment law presents multifaceted challenges in an ever‐globalizing world. The recent bankruptcy of the Birmingham City Council in September 2023, burdened by substantial debt from equal pay claims, serves as a poignant example, illustrating the potential widespread effects of local financial crises on international investment protections and obligations. The discourse explores the complexities arising from municipal insolvencies and the implications of such local fiscal policies on international investment obligations. The lens of international arbitral tribunals sheds light on the dilemmas faced when local realities vie with global responsibilities, especially concerning investor protections and Bilateral Investment Treaties. Decentralized states add another layer of intricacy, balancing regional policies with overarching international commitments. As the landscape of international investment law transforms, both state entities and investors must understand and adapt to the evolving interplay. The synthesis of these two realms is crucial in today's globalized era. Through proactive policy‐making, stakeholder dialogues, and a keen understanding of both local and global dynamics, a harmonious fusion of domestic objectives and international obligations can be achieved.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.947
Threshold uncertainty score0.916

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.070
GPT teacher head0.379
Teacher spread0.309 · 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 designNot applicable
Domainnot available
GenreReview

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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