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Record W37396726 · doi:10.3138/cjh.46.1.97

US-Romanian Relations during the Presidency of Gerald R. Ford

2011· article· en· W37396726 on OpenAlexvenueno aff
Graeme S. Mount

Bibliographic record

VenueJournal of History · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicHistorical Geopolitical and Social Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsPresidencyCommunismRomanianPolitical scienceEconomic historyEmigrationAllegianceLawState (computer science)DemocracyCommunist stateGovernment (linguistics)Political economyPublic administrationPoliticsSociologyHistory

Abstract

fetched live from OpenAlex

Throughout Gerald Ford’s presidency (9 August 1974-20 January 1977), the Romanian government of Nicolae Ceauşescu was one of the most totalitarian governments of Communist Europe. Yet, President Ford and Secretary of State Henry Kissinger had a friendly personal relationship with Ceauşescu, primarily in the hope that he would help to undermine the Soviet Empire. Kissinger had limited interest in democratic practices outside the United States, and Ceauşescu’s Stalinist tendencies were of limited concern to him. Ceauşescu sought to use the United States as a counterweight to the Soviet Union and to gain economic benefits for Romania. Ford and Kissinger were willing to grant Romania most favored nation (MFN) status, but Congress had reservations. Would Romanian Jews have the right to emigrate? Would Ceauşescu’s government respect the language “rights” of Transylvania’s ethnic Hungarians and Germans? Would Romania’s Protestants and Roman Catholics enjoy freedom of worship?

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)0.003
metaresearch head score (Gemma)0.004
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.048
Threshold uncertainty score0.099

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0130.006
Scholarly communication0.0060.002
Open science0.0010.003
Research integrity0.0040.009
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 head0.032
GPT teacher head0.250
Teacher spread0.218 · 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

Citations2
Published2011
Admission routes1
Has abstractyes

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