Will Blockchain Technology Change How Well National Archives Preserve the Trustworthiness of Digital Records?: Preliminary Results of a Survey
Bibliographic record
Abstract
The purpose of this study is to examine the viewpoint of national archives on blockchain and distributed ledger technologies, discover their activities in relation to the application of these technologies, and analyse their thoughts on how these technologies can play a role in the preservation of records’ trustworthiness. A survey method was adopted in the study. The survey consisted of 18 questions about national archives’ attitude and actions in relation to application of blockchain and distributed ledger technologies. The survey was sent to the 194 national archives listed in the Directory of National Archives. Eighteen responses have been acquired which, while low, provides initial insights into how national archives are responding to these technologies. This study has three hypotheses. The first one is “blockchain technology will change archiving practices “, the second one is “the trustworthiness of digital records can be preserved better with blockchain technology”, and the last one is “national archives are reluctant to implement blockchain networks that use tradable crypto-assets”. According to the results obtained from the survey, the first hypothesis has not been verified. The second hypothesis is likely, as national archives that are keen to adopt blockchain and distributed ledger technologies, but a majority of the archives are hesitant to adopt these technologies for archiving, suggesting that the third and final hypothesis might also true, though the reasons for national archives’ reluctance to adopt these technologies could be more varied than originally hypothesized. This study is one of the first systemic analyses of the viewpoint and activities of national archives on blockchain and distributed technologies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.047 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".