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The Internationalization of State-Owned Firms

2022· book-chapter· en· W4311918075 on OpenAlexaff
Álvaro Cuervo-Cazurra, Cheng Li

Bibliographic record

VenueOxford University Press eBooks · 2022
Typebook-chapter
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsWestern University
Fundersnot available
KeywordsInternationalizationIndependence (probability theory)BusinessState ownershipState ownedState (computer science)Market economyEmerging marketsInternational tradeEconomicsFinance

Abstract

fetched live from OpenAlex

Abstract We analyze the impact of state ownership on firm internationalization. We propose and explain four drivers of the variation in the internationalization of state-owned enterprises (SOEs) from the same country: 1) Industry, in which SOEs created to provide public services are less likely to internationalize, while those created to facilitate industrial upgrading are more likely to expand abroad; 2) type of state ownership, in which SOEs owned by lower-level governments like municipalities are less likely to internationalize, while those owned by higher-level governments such as the central administration are more likely to go abroad; 3) level of state ownership, in which SOEs with higher state ownership are less likely to expand overseas, while those with lower state ownership are more likely to internationalize; and 4) managerial independence, in which SOEs with lower managerial independence are less likely to internationalize, while those with higher independence are more likely to expand abroad.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.019
GPT teacher head0.178
Teacher spread0.159 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2022
Admission routes1
Has abstractyes

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