MétaCan
Menu
Back to cohort
Record W4414773039 · doi:10.1007/978-3-031-98724-3_3

The Maidan Massacre

2025· book-chapter· en· W4414773039 on OpenAlexaff
Ivan Katchanovski

Bibliographic record

VenueRethinking political violence · 2025
Typebook-chapter
Languageen
FieldSocial Sciences
TopicMilitary, Security, and Education Studies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsOpposition (politics)VerdictPrisonGovernment (linguistics)Poison control

Abstract

fetched live from OpenAlex

Abstract This chapter analyzes which party of the conflict was involved in the Maidan massacre in Ukraine on February 20, 2014. Testimonies by the absolute majority of wounded Maidan protesters and nearly 100 prosecution and defense witnesses at the Maidan massacre trial and investigation in Ukraine, testimonies by several hundred witnesses, synchronized videos, and medical and ballistic examinations by Ukrainian government experts confessions by 14 self-admitted members of Maidan sniper groups, bullet hole locations show that both the police and protesters were massacred by Maidan snipers located in Maidan-controlled buildings and areas. Content analysis of synchronized videos revealed that the specific time and direction of shooting by Berkut policemen, who were charged with the massacre, did not coincide with the killing of specific protesters. The Maidan massacre trial verdict confirmed that many protesters and policemen were killed and wounded on February 20 from Maidan-controlled buildings and areas and that there is no evidence of the massacre order by the Yanukovych government or Russian involvement. Because of the cover-up, no one is serving prison sentences for this massacre. The false-flag massacre was organized and carried out with the involvement of oligarchic and far-right elements of the Maidan opposition to overthrow the incumbent government in Ukraine.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.038
GPT teacher head0.331
Teacher spread0.293 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueRethinking political violenceSame topicMilitary, Security, and Education StudiesFrench-language works237,207