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Record W4390771734 · doi:10.48075/odal.v4i1.31665

Romanian first names in America: a synchronic perspective

2023· article· en· W4390771734 on OpenAlexaboutno aff
Oliviu Felecan

Bibliographic record

VenueOnomástica desde América Latina · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicNames, Identity, and Discrimination Research
Canadian institutionsnot available
Fundersnot available
KeywordsPrestigeEthnic groupRomanianImmigrationSociologyPerspective (graphical)Gender studiesEthnologyLinguisticsHistoryAnthropologyPolitical scienceLaw

Abstract

fetched live from OpenAlex

This article deals with a topic which has not been researched extensively. It refers to first names of children born over the last decades in North America and aims to show how Romanian immigrants chose for their children various types of first names: traditional, international, adapted to the language used across the Atlantic, or specific to the adoptive country. A simple, four-question survey was drawn up and applied to 56 Romanians who have settled in Canada, the USA, and Martinique over the last decades. It reveals that the integration into the host country is achieved on the social, professional, and educational levels, as well as on the linguistic and onomastic ones. Thus, we can state that first names chosen for children born across the Atlantic are socio- and psycholinguistic markers not only of the attachment to family, cultural, and religious values, but also of the wish to integrate seamlessly into the adoptive society. The reasons behind the anthroponymic choices are related to the parents’ level of education, the size of the community of immigrants, the connection with certain religious, cultural, and educational institutions which can influence the parents’ onomastic decisions. At the same time, ethnic prestige, on the macrosocial level, and self-esteem, on the microsocial level, determine the choice of first names for newborns.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.904
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.372
Teacher spread0.334 · 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.

Study designTheoretical or conceptual
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
Published2023
Admission routes1
Has abstractyes

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