The Contribution of Digital Preservation as a Digital Transformation Mechanism within the Scope of the Sustainable Development Objectives of the 2030 Agenda
Bibliographic record
Abstract
This study reports how institutions in a contemporary context experiencing significant digital transformations face several challenges to keep their memory alive for the next generations. In this context, digital preservation becomes essential for institutions to preserve their history. Also noteworthy are the Sustainable Development Goals established in the United Nations 2030 Agenda, which focus on sustainable development directly related to digital preservation. This article aims to analyze how humanity should consider Objectives 9, 11, 12 and 13 of the 2030 Agenda, whose objectives are interrelated with the theme of this research work. The methodology used was a bibliographic survey on the Web of Science, Google Scholar and Brapci databases, with a qualitative approach and categorical analysis. It is concluded that the interrelationship of digital preservation through the tool of digital certification in documents in institutions can be used as a mechanism for digital transformation within the scope of the Sustainable Development Goals (SDGs) of the 2030 Agenda.
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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 | 0.020 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.006 | 0.026 |
| Scholarly communication | 0.017 | 0.017 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".