Cultural Heritage, Information Science, and the Creative Process
Bibliographic record
Abstract
Abstract The creative process has recently garnered research attention in the field of information science. Multiple authors have proposed original research directions and methods relating to the creative process with the goals of preserving, curating, and disseminating cultural heritage. This body of research provides empirical grounds for the development of better tools for artistic practice and, at a theoretical level, brings another interdisciplinary perspective on the creative process. The field of information science investigates the creative process through the lens of different theoretical frameworks, stemming notably from psychology, sociology, and linguistics. Research areas include empirical studies on music information–seeking behavior, creative process modeling, digital humanities projects for repertoire analysis, performance documentation methodologies, preservation frameworks, and theoretical investigations of the relationship between creative processes and archival documents. Together, these studies provide new insights into the field of information science by re-examining established categories of inquiry, as well as methodologies and ontologies pertaining to the field. The relationship between cultural heritage, information science, and the creative process highlights the singularity of the creative process as an object of research and provides a new critical perspective on the domains within which it is being investigated.
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 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 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".