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Record W2019583021 · doi:10.1093/bjc/azl032

Severe and Swift Justice in China

2006· article· en· W2019583021 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueThe British Journal of Criminology · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicCrime Patterns and Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsChinaSwiftCriminal justiceEconomic JusticePolitical scienceQuarter (Canadian coin)Human rightsPopulationLawCriminologySociologyGeography

Abstract

fetched live from OpenAlex

One quarter of the world's population live in China. Chinese law is fast shifting into the global arena. China's response to new and emerging crimes over the last decade is now an important international human rights issue. This paper discusses some key concepts for understanding the criminal justice system of a country that is fast becoming the second most economically and geo-politically powerful nation in the world. Thousands of criminals are executed during China's periodic 'Strike Hard' anti-crime campaigns. This paper examines the Strike Hard policy of 'severity and swiftness', seeking to achieve three complementary objectives: to provide insight into the machinations of criminal justice operations in China's anti-crime campaigns, to explain official justifications for the policy, and to give voice to alternative commentaries and opinions of Chinese criminal justice researchers and practitioners.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.839
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.049
GPT teacher head0.329
Teacher spread0.281 · 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