MétaCan
Menu
Back to cohort
Record W3103253969 · doi:10.5771/2193-5505-2020-3-395

Corporate Responsibility for Transnational Human Rights Violations under German Criminal Law – Review and Outlook

2020· article· en· W3103253969 on OpenAlexaboutno aff
Petra Wittig

Bibliographic record

VenueEuropean Criminal Law Review · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Law and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsCriminal liabilityGermanPolitical scienceHuman rightsLawPower (physics)Principal (computer security)Criminal lawCriminal responsibilityLiabilityChinaProfit (economics)BusinessLaw and economicsSociologyEconomicsGeography

Abstract

fetched live from OpenAlex

Time and again, cases come to light in which companies in unstable regions have participated in crimes, including human rights violations. However, the economic power over these companies is regularly geographically distant, anchored in the stable regions of the world, e.g. in a corporate headquarters located in Europe, the USA, Canada or Australia, where the economic profit ultimately accrues. Starting from this imbalance, the present essay examines the question of the criminal (co-)responsibility of these power holders using the example of the German legal system. It becomes apparent that the concept of criminal law, which is still based almost exclusively on individual responsibility, leads to deficits in the investigation of the most serious economically driven crimes. Despite this need for reform, however, even de lege lata a top management based in Germany can be held (jointly) liable for distant crimes under the concept of "principal’s criminal liability" (“Geschäftsherrenhaftung”).”

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)0.004
metaresearch head score (Gemma)0.005
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: Review · Consensus signal: Review
Teacher disagreement score0.009
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0050.004
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.170
GPT teacher head0.402
Teacher spread0.233 · 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
GenreReview

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

Citations4
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueEuropean Criminal Law ReviewSame topicCriminal Law and PolicyFrench-language works237,207