Cartographie du paysage des politiques de savoirs ouverts — Présentation de l’analyse de recherches « Politique », disponible en libre accès via Open Scholarship Press
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
<p><span style="font-weight: 400">Cet article pr&eacute;sente </span><a href="https://en.wikibooks.org/wiki/Open_Scholarship_Press_Collections:_Policy"><span style="font-weight: 400">l&rsquo;analyse de recherches &laquo; Politique &raquo;</span></a><span style="font-weight: 400">, disponible en libre acc&egrave;s via </span><a href="https://en.wikibooks.org/wiki/Open_Scholarship_Press"><span style="font-weight: 400">Open Scholarship Press</span></a><span style="font-weight: 400">. </span><i><span style="font-weight: 400">L&rsquo;analyse de recherches </span></i><span style="font-weight: 400">&laquo; </span><i><span style="font-weight: 400">Politique </span></i><span style="font-weight: 400">&raquo; suit et refl&egrave;te l&rsquo;&eacute;volution des politiques li&eacute;es aux savoirs ouverts au Canada et ailleurs, en analysant les changements de politiques et leur pertinence pour les chercheurs, les professionnels de l&rsquo;information, les biblioth&eacute;caires, le corps professoral et les d&eacute;cideurs. Issue de l&rsquo;Open Scholarship Policy Observatory, cette ressource adopte une perspective canadienne et s&rsquo;int&eacute;resse aux sciences humaines et sociales (SHS), mais elle prend une vue d&rsquo;ensemble, consid&eacute;rant les savoirs ouverts comme un mouvement international et interdisciplinaire.</span></p>
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.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it