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Record W3084091063 · doi:10.1017/9781108769105.013

Stefan Glaser

2020· book-chapter· en· W3084091063 on OpenAlexaff
Karolina Wierczyńska, Grzegorz Wierczyński

Bibliographic record

VenueCambridge University Press eBooks · 2020
Typebook-chapter
Languageen
FieldSocial Sciences
TopicInternational Law and Human Rights
Canadian institutionsMcGill University
Fundersnot available
KeywordsImpunityLawPolitical scienceOpposition (politics)PoliticsCriminal courtConventionCriminal lawInternational lawSociology

Abstract

fetched live from OpenAlex

For various reasons, Glaser must be understood as a significant scholar of international criminal law. Already in the 1920s, he wrote about the idea of international criminal justice and the creation of an international criminal court. He devoted his main research after World War II to this emerging discipline. He was the first academic who collected various forms of sources and opinio juris to give scholarly support for the development of a new discipline of ICL to be studied at institutions of higher education. At the same time, Glaser was a lawyer involved in some of the political and judicial turmoil of his times especially in Poland. He supported and represented the repressed members of Poland’s political opposition before Polish courts before World War II, he also fought against impunity for grave crimes through his work in the UNWCC during the war, and he provided advice on the draft for the Convention on the Non-Applicability of Statutory Limitations for Grave Crimes.

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)0.002
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.056
Threshold uncertainty score0.188

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0020.003
Scholarly communication0.0050.006
Open science0.0010.003
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0560.053

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 head0.031
GPT teacher head0.227
Teacher spread0.195 · 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
GenreOther

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

Citations16
Published2020
Admission routes1
Has abstractyes

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Same venueCambridge University Press eBooksSame topicInternational Law and Human RightsFrench-language works237,207