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Record W4393971281 · doi:10.7202/1104262ar

Troubling Records

2023· article· en· W4393971281 on OpenAlexvenueaboutno aff
Cheryl Regehr, Kaitlyn Regehr, Arija Birze, Wendy Duff

Bibliographic record

VenueArchivaria · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicDigital and Traditional Archives Management
Canadian institutionsnot available
Fundersnot available
KeywordsHistoryPolitical science

Abstract

fetched live from OpenAlex

Video records created by perpetrators and witnesses of violent crime are increasingly used as evidence in criminal investigations and court proceedings. When these records include the sexual assault, torture, and murder of individuals, they carry significant power to harm those exposed to them, but most importantly, through repeated viewing, they continue to harm those individuals whose suffering is immortalized therein. Using case study methods, including in-depth interviews with those centrally involved in the case, interviews with criminal justice professionals currently working with video evidence of violent crime, and a review of official documents and media reports, this article examines the tragic Canadian case of serial killers Paul Bernardo and Karla Homolka and the videos they recorded of their crimes. We observe that challenging decisions regarding the handling of video records of violent crime during the investigation process, the viewing of such records in court, and access to them by the public and press during the criminal justice process continue to be areas of concern and contestation, pitting principles of open justice against those of victim dignity and privacy. However, challenges regarding access to video records do not end with a trial and an ultimate verdict of guilt or innocence; rather, decisions continue to be made about the preservation or destruction, the storing and cataloguing, and access to archived material. In examining questions regarding the preservation and continued use of the records, we conclude that a responsible and ethical approach to these challenges is best achieved through what Caswell called a survivor-centred approach. We suggest that this approach should include recognizing the traumatic potentiality of records, providing safety and support to those affected, recognizing the potential of records to produce and perpetuate injustice, respecting the autonomy and decisions of survivors, and accepting and facilitating the right to be forgotten.

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.

How this classification was reachedexpand

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.938
Threshold uncertainty score0.998

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.003

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.

Opus teacher head0.056
GPT teacher head0.227
Teacher spread0.171 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreOther

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".

Quick stats

Citations3
Published2023
Admission routes2
Has abstractyes

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