Reframing Cultural Heritage Digitization: Co-Creation, Inclusion, and the Quadruple Helix Approach
Bibliographic record
Abstract
This paper addresses the fragmented dynamics of stakeholder engagement in cultural heritage digitisation, particularly where minority and Indigenous representation is concerned. Drawing on co-creation theory, innovation ecosystems, and the Quadruple Helix framework, it introduces a model that treats engagement as an evolving process across civil society, academia, government, and industry—while recognising communities as autonomous knowledge actors. The model was tested through an analysis of 40 digitisation projects across Canada, Australia, the USA, and Croatia, selected for their focus on cultural self-representation, oral traditions, and community-led preservation. Findings highlight the significance of shared governance and sustained community leadership in embedding co-creation across decision-making and stewardship. The paper argues that genuine engagement requires a redistribution of power and epistemic authority, not just inclusion. The conclusion outlines implications for digital heritage policy, especially regarding data sovereignty and culturally appropriate infrastructure. Ongoing research will explore how the model can be applied across diverse contexts.
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 | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".