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Record W2087742111 · doi:10.1177/0888325411403922

Witch-hunt or Moral Rebirth?

2011· article· en· W2087742111 on OpenAlexaff
Lavinia Stan

Bibliographic record

VenueEast European Politics and Societies and Cultures · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicPost-Communist Economic and Political Transition
Canadian institutionsSt. Francis Xavier University
Fundersnot available
KeywordsPolitical scienceEuropean unionLawParliamentEliteWitchAccessionTransitional justiceIdeologyCommunismEconomic JusticePoliticsEconomics

Abstract

fetched live from OpenAlex

Lustration was not legislated in Romania to date, but it was discussed by deputies and senators of all ideological persuasions, especially from 2005 to 2007. Declarations delivered in front of the house, interventions during debates of lustration-related draft bills and contributions to a parliament-sponsored public discussion reveal that for Romanian legislators lustration can bring about moral cleansing and a break with the past, provide retributive justice for victims of communism, facilitate elite replacement, prevent future violence, and help countries enjoy the benefits of European Union accession, although it punishes valuable individuals, runs against European values, is impractical and unconstitutional.

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)0.007
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: none
Teacher disagreement score0.011
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.049
Scholarly communication0.0060.007
Open science0.0010.005
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0110.001

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 head0.071
GPT teacher head0.275
Teacher spread0.204 · 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

Citations12
Published2011
Admission routes1
Has abstractyes

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