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Record W1987554390 · doi:10.1287/mnsc.1030.0184

Industry Risk and Market Integration

2004· article· en· W1987554390 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueManagement Science · 2004
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMarket Dynamics and Volatility
Canadian institutionsMcGill University
FundersSocial Sciences and Humanities Research Council of CanadaMcGill UniversityGeorgia Institute of Technology
KeywordsDiversification (marketing strategy)Market integrationEconomic integrationInternational tradeMarket segmentationBusinessEuropean unionVertical integrationFinancial integrationIndustrial organizationEconomicsFinancial marketMarketingFinance

Abstract

fetched live from OpenAlex

Traditionally, integration has been studied at the country level. With increasing economic integration, industrial reorganization, and blurring of national boundaries (e.g., European Union (EU)), it is important to investigate global integration at the industry level. We argue that country-level integration (segmentation) does not preclude industry-level segmentation (integration). Indeed, our results suggest that a country is integrated with (segmented from) the world capital markets only if most of her industries are integrated (segmented). We also show that although global industry risk is small, it can be priced for certain industries. Industries that are priced differently from either the world or domestic markets represent incremental opportunities for international diversification.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.381
Threshold uncertainty score0.281

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 head0.015
GPT teacher head0.215
Teacher spread0.200 · 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