MétaCan
Menu
Back to cohort
Record W2128003957 · doi:10.1177/1049732313507753

Purposing and Repurposing Harms

2013· article· en· W2128003957 on OpenAlexaffabout
Karen‐Lee Miller

Bibliographic record

VenueQualitative Health Research · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicSexual Assault and Victimization Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsHarmCriminologyPsychologyCriminal justiceRepurposingCompensation (psychology)Economic JusticeSocial psychologyPolitical scienceLaw

Abstract

fetched live from OpenAlex

The purpose of the victim impact statement (VIS) is to inform judges of victims' crime-related physical, psychological, and financial harms. Findings from interviews with Canadian sexual assault victims, advocates, victim services workers, and prosecutors (N = 37) demonstrated that harm descriptions were manipulated by victims and others in keeping with, and contrary to, VIS design. Victims and prosecutors purposed the VIS to inform court outcomes through harms claims and struggles over those claims. The repurposing of harms claims occurred through practices of strategic disclosure, intended to effect changes in others' behaviors, and harm peddling, the circulation of the VIS in nonsentencing arenas. Victims, adversaries, and criminal justice professionals engaged in harm peddling to obtain compensation, child custody, and parole delay. Implications of purposing and repurposing harms claims include novel opportunities and legal pitfalls for victims, varied responses by judges, and an expansion of social control over victims and offenders.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.053
metaresearch head score (Gemma)0.129
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.053
Threshold uncertainty score0.282

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0530.129
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.002
Science and technology studies0.0100.008
Scholarly communication0.0030.004
Open science0.0030.008
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.625
GPT teacher head0.659
Teacher spread0.034 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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

Citations12
Published2013
Admission routes2
Has abstractyes

Explore more

Same venueQualitative Health ResearchSame topicSexual Assault and Victimization StudiesFrench-language works237,207