MétaCan
Menu
Back to cohort
Record W2773958201 · doi:10.29173/invoke29331

Redefining Mandatory Vaccination as Necessary to Life and the Refusal of Vaccination as Criminal Negligence Causing Death

2017· article· en· W2773958201 on OpenAlexvenueaboutno aff
SUSA Submissions, Cody Bondarchuk

Bibliographic record

VenueINvoke · 2017
Typearticle
Languageen
FieldMedicine
TopicEthics and Legal Issues in Pediatric Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsVaccinationNeglectTimelineSkepticismCriminal codeMedicineCriminologyPsychologyPolitical sciencePsychiatryImmunologyCriminal lawHistory

Abstract

fetched live from OpenAlex

This paper argues that childhood vaccination should be considered a necessary of life as defined in Section 215 (1) of the Canadian Criminal Code, and parents who do not vaccinate their children should be considered responsible for death by criminal negligence if their child dies from a preventable disease. It timelines the long history of the vaccine debate from the perspective of both science of skeptics and points to the since-retracted Wakefield paper as the catalyst for the re-emergence of this debate, detailing the science behind why vaccination is safe, effective, and necessary. It then outlines the theory of medical neglect as a form of indirect killing in the same way starvation or lack of shelter is currently considered neglect under the Code, to prove that vaccination is required for all children who can be vaccinated and the dangers of not doing so. It concludes with notes on disease prevention and education to increase the number of vaccinated children, as the goal of defining vaccination as a necessary of life is not meant to punish parents but to encourage higher rates of vaccination and a greater communal knowledge of medical procedures.

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)0.011
metaresearch head score (Gemma)0.028
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.087
Threshold uncertainty score0.174

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.028
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0070.049
Scholarly communication0.0050.006
Open science0.0020.005
Research integrity0.0090.009
Insufficient payload (model declined to judge)0.0020.000

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 head0.074
GPT teacher head0.405
Teacher spread0.331 · 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
GenreCommentary

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
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueINvokeSame topicEthics and Legal Issues in Pediatric HealthcareFrench-language works237,207