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Record W2530416497 · doi:10.1002/mde.2967

The lessons Quebec offers to Greece and Europe

2018· article· en· W2530416497 on OpenAlexaboutno aff
Michael Mitsopoulos, Theodore Pelagidis

Bibliographic record

VenueManagerial and Decision Economics · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicContemporary and Historical Greek Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIndependence (probability theory)PoliticsConvergence (economics)European unionPolitical scienceRoot (linguistics)Political economyPerceptionEconomyEconomicsDevelopment economicsEconomic policyLawEconomic growth

Abstract

fetched live from OpenAlex

An assessment of the importance of Greece's potential Grexit during the recent crisis is made. Subsequently, the case of the independence movement of Quebec is examined to argue that once perceptions about the separation from a Union take root, they may propagate themselves for long periods of time entrenching an uncertainty that leads to concrete economic damage. Therefore, the need to accelerate “convergence in institutions” among the Union members is highlighted, as is the need to acknowledge that political developments in Greece are in line with the predictions of a growing literature on the causes and impact of political risks.

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)0.002
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: Empirical · Consensus signal: none
Teacher disagreement score0.086
Threshold uncertainty score0.248

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.007
Scholarly communication0.0060.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0080.000

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 head0.035
GPT teacher head0.288
Teacher spread0.253 · 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
GenreEmpirical

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

Citations2
Published2018
Admission routes1
Has abstractyes

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