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Record W4245652129 · doi:10.1017/9781107323728

June Fourth

2021· book· en· W4245652129 on OpenAlexaff
Jeremy Brown

Bibliographic record

VenueCambridge University Press eBooks · 2021
Typebook
Languageen
FieldSocial Sciences
TopicChinese history and philosophy
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsBeijingChinaTurning pointScope (computer science)DemocracyPolitical scienceHistoryMedia studiesCriminologySociologyLawAestheticsArtPeriod (music)Politics

Abstract

fetched live from OpenAlex

The Tiananmen protests and Beijing massacre of 1989 were a major turning point in recent Chinese history. In this new analysis of 1989, Jeremy Brown tells the vivid stories of participants and victims, exploring the nationwide scope of the democracy movement and the brutal crackdown that crushed it. At each critical juncture in the spring of 1989, demonstrators and decision makers agonized over difficult choices and saw how events could have unfolded differently. The alternative paths that participants imagined confirm that bloodshed was neither inevitable nor necessary. Using a wide range of previously untapped sources and examining how ordinary citizens throughout China experienced the crackdown after the massacre, this ambitious social history sheds fresh light on events that continue to reverberate in China to this day.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.591
Threshold uncertainty score0.583

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0050.002
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.5910.327

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 head0.030
GPT teacher head0.229
Teacher spread0.199 · 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.

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

Citations19
Published2021
Admission routes1
Has abstractyes

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