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Record W3003360091 · doi:10.1111/caje.12427

Is piracy sustainable?

2020· article· en· W3003360091 on OpenAlex

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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueCanadian Journal of Economics/Revue canadienne d économique · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicMaritime Security and History
Canadian institutionsMcMaster University
Fundersnot available
KeywordsProfit (economics)Deterrence theoryExternalityInternational tradeIncentiveBusinessEconomicsEconomyMicroeconomicsLawPolitical science

Abstract

fetched live from OpenAlex

Abstract We develop a model of international trade between three countries, one of which hosts pirates. When the number of pirate ships increases, the probability for one of the pirate ships (for one commercial ship) encountering a commercial (pirate) ship decreases (increases). Then, the commercial ships have an incentive to spend more on defence and pirate ships to invest less on attack. If pirates operate under free entry, they do not internalize the entry externality. Then, their number rises until it reaches a level such that their attack power has become negligible and the defence of the commercial ships has reached a high level. The economy settles in a full deterrence equilibrium. However, if the number of pirate ships is controlled by an authority, which maximizes piracy's profit, the economy settles in an equilibrium where piracy is active and commercial ships spend less on defence. Piracy is a substitute for trade. Piracy depends on the terms of trade of the pirate country and on the relative efficiency of the attack versus the defence.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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 score0.883
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.147
GPT teacher head0.203
Teacher spread0.056 · 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