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Record W2593566833 · doi:10.1177/0022002717693048

Asset Complementarity, Resource Shocks, and the Political Economy of Property Rights

2017· article· en· W2593566833 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.

Bibliographic record

VenueJournal of Conflict Resolution · 2017
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicNatural Resources and Economic Development
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsEconomicsProperty rightsCommitIncentiveCredibilityPoliticsResource curseComplementarity (molecular biology)Economic systemValue (mathematics)Political economyMicroeconomicsPolitical science

Abstract

fetched live from OpenAlex

Collaboration between two groups that may invest their resources in a common productive activity has the potential to lead to conflict over the output of that activity. This article examines the stakes of such conflict as well as the willingness for parties to subject themselves to a third-party arbiter. The model highlights three determinants of conflict and of investment in credibility-enhancing institutions: the value of the output, the relative endowments of the parties, and the mutual benefits of collaboration. In particular, the analysis shows that complementarity between the groups’ resources lowers the stakes of political conflict and increases the incentives to commit. The model thus suggests a new mechanism through which we can understand the frequency of conflict and the poor institutions associated in countries with mineral resources. The model’s predictions also help us to understand how Mauritius avoided the resource curse and was able to develop sustainable economic growth.

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 categoriesnone
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 score0.876
Threshold uncertainty score0.282

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 studies0.0000.000
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 head0.050
GPT teacher head0.259
Teacher spread0.209 · 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