Digital Authenticity and Integrity: Digital Cultural Heritage Documents as Research Resources
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
This article presents the results of a survey addressing methods of securing digital content and ensuring the content's authenticity and integrity, as well as the perceived importance of authenticity and integrity. The survey was sent to 40 digital repositories in the United States and Canada between June 30 and July 19, 2003. Twenty-two institutions responded, the majority of which felt that ensuring authenticity and integrity represented a low priority compared to increasing access and preserving content. Technology for securing content and ensuring the authenticity and integrity of individual digital items has not yet been implemented at the majority of the responding institutions; however, the responses indicate that the number of institutions incorporating this type of technology will increase. The low level of concern and lack of implementation signify the need for additional research and interest in these issues, as the value of repository content for research purposes directly relates to the researcher's ability to trust the content's authenticity and integrity.
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 | 0.000 | 0.002 |
| Scholarly communication | 0.003 | 0.010 |
| Open science | 0.001 | 0.003 |
| 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