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Record W1525667309

Spoliation of Electronic Evidence: Sanctions Versus Advocacy

2011· article· en· W1525667309 on OpenAlex
Charles W. Adams

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicDigital and Cyber Forensics
Canadian institutionsnot available
Fundersnot available
KeywordsSanctionsFederal Rules of Civil ProcedurePolitical scienceBusinessInternet privacyLawLaw and economicsCivil procedureComputer scienceEconomics
DOInot available

Abstract

fetched live from OpenAlex

This Article proposes that courts should refrain from imposing adverse inference jury instructions as sanctions for the spoliation of evidence. This proposal bears some similarity to the approach taken twenty years ago by the 1993 amendments to Rule 11, which constrained courts' ability to sanction. Instead of imposing an adverse jury instruction as a sanction for spoliation of evidence, courts should allow evidence of spoliation to be admitted at trial if a reasonable jury could find that spoliation had occurred and if the spoliation was relevant to a material issue. If a court allows the introduction of evidence of spoliation at trial, it should also allow argument by attorneys on whether the jury should infer that the spoliated evidence was unfavorable to the spoliator. This does not require an adverse inference instruction. Instead, the court should rely on attorney advocacy and the good sense of jurors to decide whether spoliation has occurred, and if so, how the proof of spoliation should affect the outcome of the trial. Following this introduction, the Article examines how courts have traditionally dealt with the spoliation of evidence. Next the Article discusses the current law on inferences and presumptions under the Federal Rules of Evidence. Then the Article provides an analysis of two landmark decisions from 2010 on the spoliation of evidence and adverse inferences. In Pension Committee of the University of Montreal Pension Plan v. Banc of America Securities, LLC, Judge Scheindlin imposed an adverse inference instruction as a sanction for certain parties' grossly negligent conduct. The instruction included a presumption that the spoliated evidence was both relevant and would have been favorable to the innocent parties. In Rimkus Consulting Group, Inc. v. Cammarata, Judge Rosenthal also imposed an adverse inference instruction as a sanction, but she based the sanction on evidence that the spoliation was intentional. In addition, she framed the jury instruction as an inference rather than a presumption. After the analysis of Pension Committee and Rimkus, the Article urges courts to rely on attorney advocacy rather than sanctions to address the spoliation of evidence in most cases. A brief conclusion follows.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.823
Threshold uncertainty score0.152

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.064
GPT teacher head0.257
Teacher spread0.193 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Quick stats

Citations2
Published2011
Admission routes1
Has abstractyes

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