Elephant: the file system that never forgets
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
Modern file systems associate the deletion of a file with the release of the storage associated with that file, and file writes with the irrevocable change of file contents. We propose that this model of file system behavior is a relic of the past, when disk storage was a scarce resource. We believe that the correct model should ensure that all user actions are revocable. Deleting a file should change only the name space and file writes should overwrite no old data. The file system, not the user should control storage allocation using a combination of user specified policies and information gleaned from file-edit histories to determine which old versions of a file to retain and for how long. The paper presents the Elephant file system, which provides users with a new contract: Elephant will automatically retain all important versions of the users' files. Users name previous file versions by combining a traditional pathname with a time when the desired version of a file or directory existed. Elephant manages storage at the granularity of a file or groups of files using user-specified retention policies. This approach contrasts with checkpointing file systems such as Plan-9 AFS, and WAFL, that periodically generate efficient checkpoints of entire file systems and thus restrict retention to be guided by a single policy for all files within that file system. We also report on the Elephant prototype, which is implemented as a new Virtual File System in the FreeBSD kernel.
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 | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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