MétaCan
Menu
← Back to cohort
Record W4386884743 · doi:10.32920/24169035

The Evolution of Life Sentences For Second-Degree Murder: Parole Ineligibility and Time Spent in Prison

2023· preprint· en· W4386884743 on OpenAlexafffundabout
Debra Parkes, Jane B. Sprott, Isabel Grant

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsToronto Metropolitan UniversityUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPrisonLife imprisonmentSentenceTurning pointPsychologyMeaning (existential)CriminologyPolitical sciencePeriod (music)Computer science

Abstract

fetched live from OpenAlex

Canada's murder sentencing regime has been in effect since 1976, and yet very little data has examined what these sentences actually mean for those convicted. This paper begins to fill this gap by examining the meaning of a life sentence for those convicted of second degree murder in Canada. Using data provided by the Correctional Investigator, we examine both the parole ineligibility periods imposed by sentencing judges, and how long people are serving before a grant of full parole over time from 1977 to 2020. We found statistically significant increases over time in both judicial parole ineligibility periods, and in how long people are serving beyond their first full parole eligibility date. We also found that Indigenous persons are more likely to serve longer periods of time past their parole ineligibility date. We conclude that, at every point in the process, sentencing for murder has become increasingly harsh over time with no obvious public safety rationale for this increase.

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)0.001
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.758
Threshold uncertainty score0.487

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0020.002
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.059
GPT teacher head0.339
Teacher spread0.281 · 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 designObservational
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
Published2023
Admission routes3
Has abstractyes

Explore more

Same topicCriminal Justice and Corrections Analysis→French-language works237,207→