Structuring the Cultural Domain with an Upper Ontology of Culture
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
Study of cultural similarities and differences is an important research topic for many disciplines such as psychology, sociology, anthropology, archaeology, museology, communication, management and business. This presents many potential opportunities for Information Technology specialists to develop culturally-aware technology, but it also raises the risk of inconsistent approaches of the cultural domain. In this chapter, the authors present the fundamental concepts of the Upper Ontology of Culture (UOC), a formal conceptualization of the cultural domain they developed by identifying the common backbone of culture-related disciplines and activities. As a neutral, theory-driven, and interdisciplinary conceptualization, the UOC shall provide guidelines for the development of culturally-aware applications, for the consistent computerization of cultural data and their interoperability, as well as for the development of culture-driven automatic reasoning processes.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 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