Bibliographic record
Abstract
Marianne Thyssen staat als nieuwe Eurocommissaris, bevoegd voor o.a. werkgelegenheid en sociale zaken, voor vele uitdagingen. De scepsis rond het gewicht van haar bevoegdheidspakket wegnemen, zou daarvan de minste moeten zijn. De toestand waarin de Europese Unie zich bevindt maakt haar bevoegdheden vanzelf uiterst belangrijk. Ook al beschikt zij niet over de hefbomen om op haar eentje Europa een meer sociaal gelaat te geven, als belangrijke teamspeler kan zij de Commissie wel in die richting doen opschuiven. Vanuit Metis en Poliargus verwachten we dat ze deze taak op zich neemt en wij zullen dit de komende jaren ook opvolgen. We selecteerden dé vijf prioritaire uitdagingen waarop zij het verschil kan maken. Indien zij daarin slaagt, krijgt zij van ons binnen vijf jaar grootste onderscheiding.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.041 | 0.013 |
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".