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
In the globalization process many cultural traditions around the world tend to disappear under the pressure of standardisation of practice and content. Cultural diversity seems to recede more and more. In a proactive position, UNESCO made a universal declaration on cultural diversity in 2001 that it would aim at heritage preservation.In the same effort of protection and enhancement of cultural diversity, museums are developing Internet material to preserve and disseminate cultural knowledge and heritage and to create interactive experiences between users and content. This has given birth to what some refer to as cybermuseology. But one can ask, do virtual museums present more than images of objects? Can the knowledge of localised cultural heritage and practices be transferred without losing the context it stems from, or what de B’béri (Cinema andSocial Discourse 64) defines as “the condition under which a society produces specific meaning”? More specifically, can information and communication technologies (ICT) transfer tacit knowledge, human experience, and tangible cultural heritage, and if so, what can we learn through this new process of cultural codification?This paper shall focus on explaining cybermuseology and then explore the process of knowledge codification and the links we can draw with heritage codification. In the last section I will discuss virtual experiences and try to determine how museums are using the virtual to protect and promote cultural diversity.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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