PERCEPTION OF A PLACE OF CULTURE FROM AN EDUCATIONAL PERSPECTIVE THE MUSEUM IN FRANCE, HIC ET NUNC
Bibliographic record
Abstract
In the perspective of education through culture, the museum fully plays its role.Acting as a guarantor of memory, a transmitter of meaning, and a facilitator of access for a public seeking sensitive experiences to live, the museum reiterates the debate on lifelong education.Given the considerable stakes involved, it seems relevant to show how the framework and time specific to informal and non-formal education promote cultural offerings.In this perspective, knowledge and learning in the digital age point to a paradigm shift.Concepts such as "perception," "creation," "operation" of cultural places, invite us to grasp the kaleidoscopic facets pointing towards the virtualization of the museum.Struggling to find its true place in digital culture, the museum requires a rethinking of the time-space configuration.The "here and now" tandem unfolds multiple levels of reading associating physical locations and presence with virtual sites.Our presentation will include a brief insight into the establishment and evolution of the museum institution in France, followed by an analysis of the "public -museum -cultural policy" relationship.Given that the virtualization of the museum raises numerous questions reflecting the major concern of the increasingly heterogeneous public's accessibility, some practical examples of digital databases will illustrate what we could call a culture of ubiquity.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.017 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".