Third progress report: the situation in the regions requires an ambitious cohesion policy. inforegio news. Newsletter No. 135, June 2005
Bibliographic record
Abstract
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
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".