Le transfert dans le cycle des politiques publiques : les experts européens et le programme d'analyse du génome humain
Bibliographic record
Abstract
C cia player in the human genome race.The HGAP can be considered the resuit of two transfers, the first one stemming from the French experience in genetic mapping and the second, from the network structure of a European proj ect on the yeast genome.Deliberation as a problem-solving approach is a useful means of fostering discussion and confronting ideas and points of view.Furthermore, it enables the development of a common perspective aimed at achieving the common good.We introduce here a typology of voluntary transfers that takes into account the object of the transfer (idea or program/policy) and the process invoÏved (network or market).This typology has the benefit of identifying the object's origin as well as the players associated with it.Contrary to previous studies on Europeanization that seek to highlight similarities between policies of Member States and those of the European Union, we have focused here on indirect Europeanization, that is, on the influence exerted by discourses and ideas emanating from the European Union on its Member States.Our findings show that the HGAP did not exert, even in an indirect manner, any lasting influence in france or in Belgium.
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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 | 0.014 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.000 |
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.
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".