MétaCan
Menu
Back to cohort
Record W4316143885 · doi:10.30816/iconn5/2019/14

Nicknames from three villages situated on the Mara river

2022· article· en· W4316143885 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueProceedings of the ... International Conference on Onomastics "Name and Naming" · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicLinguistics, Language Diversity, and Identity
Canadian institutionsScience North
FundersUniversity of Glasgow
KeywordsSituatedHuman settlementCraftPopulationGeographyGenealogyHistoryArchaeologySociologyComputer scienceDemographyArtificial intelligence

Abstract

fetched live from OpenAlex

This paper aims to identify and classify the nicknames from three villages (Sat-Şugatag, Giuleşti, Berbeşti), which are situated along the Mara river. The corpus consists of approximately two hundred nicknames which were registered during field research in the aforementioned settlements. The study will analyse the endurance of the nicknames across generations, as well as the reason behind their appearance. It must be noted that a considerable number of nicknames pertain to Roma ethnics, which make up an extended community in Sat-Şugatag, or to the Jewish people, very numerous in Berbesti, where they left a mark on the local population. These names will be grouped into different categories, such as nicknames derived from animal names: Hulpea (‘the fox’), Ursu (‘the bear’); nicknames based on the bearers’ craft: Stolnicul (‘the high steward’) or connected with some physical incapacity: Orbul (‘the blind man’), Schiopul (‘the lame man’).

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.

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)0.001
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.371
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.044
GPT teacher head0.214
Teacher spread0.170 · 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