MétaCan
Menu
Back to cohort
Record W1835322988 · doi:10.1111/ecin.12431

DOES LIMITED PUNISHMENT LIMIT THE SCOPE FOR CROSS RETALIATION?

2017· article· en· W1835322988 on OpenAlex
Richard Chisik, Harun Onder

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEconomic Inquiry · 2017
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsPunishment (psychology)EconomicsIncentiveLimit (mathematics)Scope (computer science)Law and economicsMicroeconomicsComputer scienceMathematics

Abstract

fetched live from OpenAlex

This paper analyzes two prominent institutional rules in the international trading system: a limited cross‐retaliation rule characterized by the Understanding on Rules and Procedures Governing the Settlement of Disputes ( DSU ) Article 22.3 and a limited punishment rule characterized by the General Agreement on Tariffs and Trade ( GATT ) Article XXVIII . In general, both rules are designed to limit the countermeasures upon a violation; however, the former rule specifies the limits of composition in retaliation, whereas the latter one designates the limits of retaliation magnitude. We show that, albeit seemingly unrelated, the limited cross‐retaliation rule complements the limited punishment rule in permitting greater trade liberalization. Specifically, we show how the limited cross‐retaliation rule also helps limit the incentives to violate the trade agreement when the limited punishment rule prevails. ( JEL F13, K33, C73)

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.

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 categoriesScholarly communication, Insufficient payload (model declined to judge)
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 score0.680
Threshold uncertainty score1.000

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 studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.002

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 head0.147
GPT teacher head0.304
Teacher spread0.158 · 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