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Record W6996313538

"On the Road to Religious Freedom": a Study of the Nazarene Emigration from Southeastern Europe to the United States

2017· article· en· W6996313538 on OpenAlexaboutno aff

Bibliographic record

VenueDigital Archive of SASA (Serbian Academy of Sciences and Arts) · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicEarly Modern Women Writers
Canadian institutionsnot available
Fundersnot available
KeywordsEmigrationPersecutionReligious persecutionImmigrationPoliticsPrisonOathIdentity (music)
DOInot available

Abstract

fetched live from OpenAlex

Different historical and socio-political circumstances often were the cause of migration, especially in the countries of Southeastern Europe. Migration was also triggered by religious persecution of particular religious minorities by different political systems, one of them being the Nazarenes. The Nazarenes were founded by a former Reformed minister Samuel Fröhlich around 1830 in Switzerland, but they soon expanded to Central and Eastern Europe. Because of their pacifist beliefs and refusal to swear and to take an oath a large number of the Nazarenes were condemned to severe prison sentences. Defending their religious identity and escaping religious persecution, thousands of Nazarenes started to emigrate especially during the First World War and in the interwar period to North America. In North America they joined the Apostolic Christian Church (Nazarene), which was the official name of the Nazarene community in the United States and Canada. The material presented in this paper results from empirical research, conducted in Serbia and the United States, on the history of the Nazarene emigration to North America. The aim of this paper is twofold: to analyze how early migration is remembered by the Nazarenes today and how the Nazarenes, as a religious minority from Southeastern Europe, became a trans-national religious community that developed in several branches. The paper shows how religion could be a ‘channel for migration’ and how immigrants used religion in processes of migration.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.545
Threshold uncertainty score0.624

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.050
GPT teacher head0.260
Teacher spread0.210 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueDigital Archive of SASA (Serbian Academy of Sciences and Arts)Same topicEarly Modern Women WritersFrench-language works237,207