Preservation Is Knowledge: A community-driven preservation approach: Paper - iPRES 2012 - Digital Curation Institute, iSchool, Toronto
Bibliographic record
Abstract
In the beginning, SPAR, the National Library of France's repository, was designed as the OAIS softwarified.It was intended to be a "full OAIS", covering all preservation needs in one tidy system.Then as its potential revealed itself across the library, high hopes arose for a do-it-all digital curation tool.Yet in day to day preservation activities of the BnF, it turns out that SPAR's growth takes a practical approach to the essentials of preservation and the specific needs of communities.Renewed dialogue with producers and users has led to the addition of functions the digital preservation team would not have thought of.This is very clear in what has been created to ingest the BnF's web archives into SPAR, giving the community more information on their data, and in what is taking shape to deal with the BnF's administrative archives, adding new functionalities to the system.The difference between what preservations tools and what curation tools should be at the BnF will have to be examined over time, to ensure all the communities' needs are met while SPAR remains viable.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.012 | 0.025 |
| Scholarly communication | 0.029 | 0.019 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.017 | 0.003 |
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".