Distributed digital preservation: preserving open journal systems content in the PKP PN
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
Purpose This paper aims to discuss the public knowledge project (PKP) preservation network (PN), which provides free preservation services for eligible journals by collecting article content and preserving it in a network of (at the time of writing) eight “preservation nodes” using the LOCKSS system. The PKP PN was launched in June 2016. Design/methodology/approach This paper addresses the development and implementation of a free, distributed digital PN for open journal systems (OJS) content. It discusses challenges in developing the network, in particular relating to preserving content from a set of partners who have no formal business relationship with PKP. The paper examines data regarding journals that have opted in to the network to date and considers interface usability and other barriers facing those that have not joined. Findings Within 18 months of launch, more than 600 journals had opted to be preserved in the PKP PN. Many more journals are eligible to join the network; the paper explores potential strategies to increase participation and identifies and proposes methods to overcome technical and communication barriers. Originality/value This paper describes a highly collaborative, open-source preservation initiative which forms a unique part of the e-journal preservation landscape and preserves a particularly vulnerable portion of the scholarly record.
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 | 0.000 |
| Scholarly communication | 0.019 | 0.016 |
| 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 it