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Record W2084172714 · doi:10.1111/1467-9396.00376

Market Segmentation, Market Integration, and Tacit Collusion

2003· article· en· W2084172714 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

VenueReview of International Economics · 2003
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsTacit collusionMarket segmentationCournot competitionMarket integrationCollusionMarket share analysisBusinessEconomicsFactor marketProduct marketIndustrial organizationMarket microstructureInternational economicsMicroeconomicsOrder (exchange)

Abstract

fetched live from OpenAlex

Moving from market segmentation to market integration (firms cannot discriminate among markets) is shown to have often anticompetitive effects in an infinitely repeated Cournot game. In particular, market integration between two countries leads both of them to experience anticompetitive effects when product markets are similar. The same conclusion holds when trade liberalization is modeled as a decrease in bilateral trade barriers followed by moving from market segmentation to market integration. The analysis also predicts that a less efficient country (like a country in transition) enjoys pro–competitive effects from market integration.

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 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: Review · Consensus signal: none
Teacher disagreement score0.895
Threshold uncertainty score0.996

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)0.0050.000

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 head0.028
GPT teacher head0.230
Teacher spread0.203 · 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