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Record W3010063662

Death Be Not Strange. The Montreal Convention’s Mislabeling of Human Remains as Cargo and Its Near Unbreakable Liability Limits

2019· article· en· W3010063662 on OpenAlexaboutno aff
Christopher Ogolla

Bibliographic record

VenueDickinson Law Review · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Law and Aviation
Canadian institutionsnot available
Fundersnot available
KeywordsConventionLawLiabilityPlaintiffHuman rightsBill of ladingSociologyPolitical science
DOInot available

Abstract

fetched live from OpenAlex

This article discusses Article 22 of the Convention for the Unification of Certain Rules for International Carriage by Air (“The Montreal Convention”) and its impact on the transportation of human remains. The Convention limits carrier liability to a sum of 19 Special Drawing Rights (SDRs) per kilogram in the case of destruction, loss, damage or delay of part of the cargo or of any object contained therein. Transportation of human remains falls under Article 22 which forecloses any recovery for pain and suffering unaccompanied by physical injury. This Article finds fault with this liability limit. The Article notes that if a plaintiff were to bring a claim against a carrier for mishandling of human remains, recovery will be limited to the weight of the corpse and the casket in kilograms, multiplied by 19 SDRs. This leads to the absurd result of recovering more for a heavy corpse and/or casket versus a light one. The Article argues that by classifying human remains as ordinary cargo thus applying ordinary cargo rules, The Montreal Convention as generally applied is inhuman and absurd.

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)0.008
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.389
Threshold uncertainty score0.774

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0080.019
Scholarly communication0.0090.006
Open science0.0020.003
Research integrity0.0120.012
Insufficient payload (model declined to judge)0.0080.002

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 head0.042
GPT teacher head0.342
Teacher spread0.300 · 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

Citations1
Published2019
Admission routes1
Has abstractyes

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