Bibliographic record
Abstract
Thankyou for inviting me to be part of this event. A significant part of the role of the Policy Research Initiative is to help departments make the connections between research and policy, particularly on medium term issues that cut across the mandates of a number of organizations. Je voudrais d’abord dire que je ne suis pas ici pour une quelconque expertise de nature économique ou agricole, mais à cause de mon rôle au PRP en matière de recherche sur les politiques et de mon expérience antérieure au sein des Réseaux Canadiens de Recherche en Politiques Publiques, notamment dans la participation du public dans le processus d’élaboration de politiques sur des questions comme la gestion à long terme des déchets nucléaires, ce que Lars a pensé être pertinent avec le sujet de votre conférence: Qu'est-ce qui rend la recherche sur l'économie agricole pertinente pour des conseils stratégiques au niveau politique? Public involvement is becoming increasingly recognized as an essential part of policy analysis and decision making around the world by researchers and
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.320 | 0.160 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".