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Record W2242916885 · doi:10.7202/1033885ar

The Use and Misuse of Information in Securitate’s Files: The Case of Plamadeala

2015· article· en· W2242916885 on OpenAlexaffvenue
Cristina Plămădeală

Bibliographic record

VenueEurostudia · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicHistorical Geopolitical and Social Dynamics
Canadian institutionsConcordia University
Fundersnot available
KeywordsRomanianOrder (exchange)Point (geometry)Computer scienceHistoryPhilosophyLinguisticsBusinessMathematics

Abstract

fetched live from OpenAlex

This short article discusses a series of Securitate documents which contain various inconsistencies, and which were written on or about the Romanian theologian Antonie Plamadeala. Examining these files, I attempt to reconstruct the case Securitate built against Plamadeala in the late 1940s, and point to errors and forgeries, which they may contain. Stated differently, I look at evidence, which may have been fabricated by Securitate in order to prove Plamadeala’s alleged ties to the Legionary Movement. I do this by first laying out the series of accusations the Romanian secret police brought against Plamadeala in 1949 and the way in which it constructed its evidence to support its case against him. I then offer a succinct analysis of ways in which one may derive truth from the plethora of information such files may bring to the attention of the modern investigator, truth which, as this article shows, is often juxtaposed with untruth in Securitate archival records.

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)0.006
metaresearch head score (Gemma)0.022
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 score0.026
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.022
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.005
Science and technology studies0.0260.043
Scholarly communication0.0120.012
Open science0.0020.008
Research integrity0.0070.006
Insufficient payload (model declined to judge)0.0040.001

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 head0.045
GPT teacher head0.297
Teacher spread0.252 · 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
Published2015
Admission routes2
Has abstractyes

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