Bibliographic record
Abstract
The crisis of the EU is multifaceted and has visibly deepened during the last year. The British referendum on EU membership and the vote in favour of Brexit have only been the most explicit symptom of the disintegrative tendencies. The core-periphery rift in the euro area has continued. The arrival of a large number of refugees from the war-torn areas of the Middle East has resulted in acrimonious conflicts in the EU on the question who should take care of them. The way in which the pro-free trade forces pushed through the Comprehensive Economic and Trade Agreement (CETA) with Canada showed utter disregard for the objections of democratically elected bodies (e.g. the Belgian regions of Wallonia and Brussels). Macroeconomically the euro area is still far from a sustained recovery and with the general weakening of the world economy and the uncertainties caused by the Brexit vote the fragility of the recovery has recently increased considerably. The European Central Bank continued and even reinforced its policy of very easy credit. However, there are signs that this policy may be reaching its limits. The EuroMemorandum 2017 critically analyses recent economic developments in Europe and emphasises the strong need for an alternative economic policy that is based on the principles of democratic participation, social justice and environmental sustainability.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 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 source (direct Gemma or distilled Codex), 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".