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Record W7014906110

Rights Review and the Institutional Roles in Sentencing: A Study of Harper-Era Mandatory Minimum Sentences

2022· dissertation· en· W7014906110 on OpenAlexaboutno aff

Bibliographic record

VenueThe Atrium (University of Guelph) · 2022
Typedissertation
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsCharterDiscretionJurisdictionGovernment (linguistics)LegislatureJudicial discretionCriminal justiceEconomic JusticePublic policy
DOInot available

Abstract

fetched live from OpenAlex

During the Harper-era (2006 to 2015), the federal government actively pursued a policy agenda focused on tough on crime criminal justice policy. Much of the Harper government’s criminal justice policy focused on sentencing, including the introduction of new and increasing of existing mandatory minimum sentences (MMS). Sentencing policy is unique as it brings together Parliament’s constitutional jurisdiction over sentencing, judicial discretion in sentencing those convicted of crimes, and the standards of Charter-protected legal rights of the criminal defendant. Existing literature on MMS criticizes these sentencing provisions for being vulnerable to Charter challenges, particularly under s. 12 of the Charter. Through the analysis of the parliamentary debates and committee hearings of the policymaking process for Harper government enacted MMS, and the subsequent legal decisions of these provisions being challenged in court on Charter standards, this study examines the role that the Charter played in the policymaking process of Harper government enacted MMS, how these policies have fared in Canadian courts, and the institutional roles in sentencing. This project finds that Parliament’s role in rights review is weak due to the strength of the executive. Additionally, courts have found these laws unconstitutional at a significantly higher rate than previous decades. Finally, despite the distinctive roles each institution has in sentencing, the results indicate a lack of respect for these roles from the legislature and the judiciary.

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)0.017
metaresearch head score (Gemma)0.042
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 score0.709
Threshold uncertainty score0.578

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.042
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0150.008
Scholarly communication0.0080.006
Open science0.0020.005
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0040.000

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 head0.017
GPT teacher head0.271
Teacher spread0.254 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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