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Record W4396717253 · doi:10.29173/mlj1004

Challenging Infanticide: Why Section 233 of Canadas Criminal Code is Unconstitutional

2018· article· en· W4396717253 on OpenAlexaboutno aff
Scott Mair

Bibliographic record

VenueManitoba Law Journal · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Law and Evidence
Canadian institutionsnot available
Fundersnot available
KeywordsSection (typography)Code (set theory)Criminal codePolitical scienceHistoryLawComputer scienceCriminal lawProgramming languageOperating system

Abstract

fetched live from OpenAlex

In the early twentieth century, Canadian juries were reluctant to convict mothers who had murdered their newly born children (children who are under one year of age) and would acquit them despite their obvious guilt.In 1948, Parliament tried to remedy this by adding s. 233 to the Canadian Criminal Code, creating the offence of infanticide.With a maximum penalty of five years imprisonment, juries would be more willing to convict these mothers.As of this writing, s. 233 is still in force.In this article, I will argue that s. 233 is unconstitutional because it violates the equality rights of newly born children under the Canadian Charter of Rights and Freedoms.Specifically, I argue that the punishments a society gives for murder reflects the value it places on human life.Section 233's mandatory lesser punishment for mothers who kill (or even premeditatedly murder) their newly born children communicates that they are less worthy as members of Canadian society than those who are at least one year of age.Furthermore, with its low maximum penalty and a broad definition of disturbed mind, s. 233 trivializes the killing of the newly born children.I then argue that these infringements cannot be justified.Lastly, I will outline how to constitutionally challenge the law.In the section about why s. 233 cannot be justified, I will also discuss a possible replacement for s. 233: a defence of diminished responsibility that applies regardless of the gender of the perpetrator or age of the victim.This would allow flexibility * Scott Mair is a Licensed Paralegal with the Law Society of Ontario and has a minor in law from Carleton University.The views expressed in this article are his own and not those of the Law Society of Ontario.in the sentencing of mentally ill but legally sane defendants without discriminating against a newly born child because of his or her age.

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)0.014
metaresearch head score (Gemma)0.045
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.109
Threshold uncertainty score0.269

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.045
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0200.019
Scholarly communication0.0110.003
Open science0.0040.004
Research integrity0.0140.017
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 head0.062
GPT teacher head0.329
Teacher spread0.267 · 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 designNot applicable
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

Citations2
Published2018
Admission routes1
Has abstractyes

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