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Record W6987611795

Third progress report: the situation in the regions requires an ambitious cohesion policy. inforegio news. Newsletter No. 135, June 2005

2005· other· en· W6987611795 on OpenAlexaboutno aff

Bibliographic record

VenueArchive of European Integration (AEI) (University of Pittsburgh) · 2005
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)Member statesEuropean unionEu countriesCohesion (chemistry)Real gross domestic product
DOInot available

Abstract

fetched live from OpenAlex

Third progress report: the situation in the regions requires an ambitious cohesion policyOn 17 May, Danuta Hbner presented the 'Third progress report on cohesion' ( 1 ).It presents an update on the situation of the regions in the enlarged EU in terms of incomes, employment and productivity.Sixty-four regions, representing more than a quarter of the EU population, have a GDP per head that is less than 75 % of the Community average.The enlarged Union shows considerable differences in wealth: in 2003, levels of GDP per head ranged from 41 % of the EU average in Latvia to 215 % in Luxembourg.Ireland is the second most prosperous country with a GDP that is 132 % of the EU average.In all the new Member States, the GDP per head is less than 90 % of the EU-25 average; in Bulgaria, Estonia, Latvia, Lithuania, Poland and Romania it is less than half of this level.In 2002, levels of GDP per head ranged from 189 % of the EU-25 average in the 10 most prosperous regions to 36 % in the 10 least prosperous ones.More than a quarter of the Union' s population, in 64 regions, have a GDP per head below 75 % of the average.In the new Member States this applies to 90 % of the population, except in the regions of Prague, Bratislava and Budapest and in Cyprus and Slovenia.In the EU-15, this concerns just 13 % of the population, these low income regions being concentrated in southern Greece, Portugal, southern parts of Spain and Italy and the new Lnder in Germany.http://europa.eu.int/comm/ enlargement/pas/phare/ publist.htm

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 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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.130
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.002
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.016
GPT teacher head0.241
Teacher spread0.225 · 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 teacher head, not a consensus.

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

Citations0
Published2005
Admission routes1
Has abstractyes

Explore more

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