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Record W2103142816 · doi:10.3138/utlj.2717

Victim impact statements at sentencing: Towards a clearer understanding of their aims

2014· article· en· W2103142816 on OpenAlexvenueaboutno aff
Marie Manikis

Bibliographic record

VenueUniversity of Toronto Law Journal · 2014
Typearticle
Languageen
FieldHealth Professions
TopicMedical Malpractice and Liability Issues
Canadian institutionsnot available
Fundersnot available
KeywordsCLARITYNormativeLegislatureOrder (exchange)CraftLawPolitical scienceLaw and economicsSociologyPsychologyHistoryBusiness

Abstract

fetched live from OpenAlex

The aims of victim impact statements (VIS) can be classified into two main categories – instrumental and expressive. These different sorts of aims are associated with different, and often conflicting, sentencing objectives. This article argues that the VIS regime in Canada remains a legal no man’s land, with neither its role nor its aims being clearly defined and articulated. Indeed, recent appellate court decisions have shown a number of inconsistencies and conflicts in the instrumental and expressive purposes that VISs in Canada are meant to serve. Further, it is also argued, the proposed legislative amendments under Bill C-32 are not very promising, since this scheme also fails to clearly articulate the aims and rationales behind the statements and behind the proposed changes. It is shown, throughout the article, that VIS regime guidelines and parameters can take different shapes and forms, depending on the aims retained. Moreover, while a dualist scheme that reconciles instrumental and expressive aims may be possible, clarity would be necessary in order to craft adequate parameters. Certainly, more protective measures are necessary if instrumental aims are to be retained. Finally, having laid out the conceptual and foundational grounds required to understand the possible aims of VISs and how these different aims can shape the relevant parameters, the article proceeds by laying out an initial, more normative, proposal for a VIS multi-functional model inspired by evidence-based findings.

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)0.001
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.303
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0130.000

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 head0.087
GPT teacher head0.401
Teacher spread0.315 · 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 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

Citations19
Published2014
Admission routes2
Has abstractyes

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