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Record W3148435590

OECD 국가의 서비스업 경쟁력 비교분석과 한국에의 시사점

2007· article· ko· W3148435590 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEU학 연구 · 2007
Typearticle
Languageko
FieldBusiness, Management and Accounting
TopicEmployee Welfare and Language Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGermanIndex (typography)LicenseBusinessService (business)RecreationEconomyRegional scienceEconomicsGeographyPolitical science
DOInot available

Abstract

fetched live from OpenAlex

Using Trade Specification Index (TSI) and Revealed Comparative Advantage (RCA) Index, we investigate patterns of trade in services in twelve OECD countries during 1990-2002 and classify those twelve countries into four model-types: British model, American model, French model, and German model. First, Finance, Insurance and Communications are core competitive sectors in British model (UK, Canada, Ireland, Switzerland). Second, the core sectors of American model cover not only finance like British model but also travel, royalties & license fees, and personal, cultural & recreational services. Third, French model (France, Italy and Australia) depends highly on travel service. Finally, German model (Germany, Japan, Korea and Sweden) demonstrates weak competitiveness in services sectors relative to manufacturing industries. They commonly possess competitiveness in transportation service.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.425
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.009

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 head0.013
GPT teacher head0.244
Teacher spread0.231 · 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