MétaCan
Menu
Back to cohort
Record W3106518534 · doi:10.1075/jial.20014.bow

French-language COVID-19 terminology

2020· article· en· W3106518534 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueThe Journal of Internationalization and Localization · 2020
Typearticle
Languageen
FieldArts and Humanities
Topiclinguistics and terminology studies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)Terminology2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)LinguisticsNatural language processingComputer scienceVirologyMedicinePhilosophyInfectious disease (medical specialty)Pathology

Abstract

fetched live from OpenAlex

Abstract The COVID-19 pandemic situation developed very quickly, driving an urgent and global need to communicate public health information that left relatively little time for traditional and formal language planning activities. This article investigates and compares French-language COVID-19-related terms appearing in linguistic resources developed in Canada and Europe to determine whether this terminology appears to be international or localized. Findings reveal that regional variation exists and that one contributing factor is that de-terminologization is being accelerated by the popular media. Another key factor leading to linguistic differences is the language situation (i.e., majority vs minority situation). Overall, while there is considerable overlap in the terminology used in the two resources, there are enough differences to warrant underlining the importance of localizing terminological content in a situation such as a pandemic in order to ensure that communication of critical information is as effective as possible.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.908
Threshold uncertainty score0.652

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.055
GPT teacher head0.290
Teacher spread0.235 · 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