The Preservation Obligation: Regulating and Sanctioning Pre-Litigation Spoliation in Federal Court
Bibliographic record
Abstract
The issue of discovery misconduct, specifically as it pertains to the prelitigation duty to preserve and sanctions for spoliation, has garnered much attention in the wake of decisions by two prominent jurists whose voices carry great weight in this area. In Pension Committee of University of Montreal Pension Plan v. Banc of America Securities LLC, Judge Shira A. Scheindlin-of the Zubulake v. UBS Warburg LLC2 e-discovery casespenned a scholarly and thorough opinion setting forth her views regarding the triggering of the duty to preserve potentially relevant information pending litigation and the standards for determining the appropriate sanctions for various breaches of that duty. Not long afterwards, Judge Lee H. Rosenthal, Chair of the Judicial Conference Committee on the Rules of Practice and Procedure (the Standing Committee) and former Chair of the Civil Rules Advisory Committee, issued an opinion in Rimkus Consulting Group, Inc. v. Cammarata, describing her understanding of many of the same issues touched on in Pension Committee. Both of these opinions have come at a time when the legal community is looking for better and more consistent guidance regarding the preservation obligations attendant to prospective litigation in the federal courts. Unfortunately, although other courts may draw some guidance from these two opinions, the fact is that variation among district courts and among the circuits will persist as long as policing pre-litigation preservation obligations remains largely the product of common law regulation via the inherent power of the courts.
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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 | 0.030 | 0.052 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.014 | 0.019 |
| Scholarly communication | 0.019 | 0.011 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.016 | 0.009 |
| 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".