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Record W4406965241 · doi:10.1387/asju.25950

Revisiting Argentine Spanish intonation: Córdoba and San Luis

2025· article· en· W4406965241 on OpenAlexaff
Laura Colantoni

Bibliographic record

VenueAnuario del Seminario de Filología Vasca Julio de Urquijo · 2025
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsIntonation (linguistics)GeographyHumanitiesLinguisticsArtPhilosophy

Abstract

fetched live from OpenAlex

Pretonic lengthening has been reported as the most salient characteristic of Córdoba Spanish (Lang-Rigal 2014; Lenardón 2017). If the relative duration of the pretonic to the tonic is a cue to stress in Spanish (Ortega & Prieto 2011; Hualde 2015), it is worth exploring what the cues are in a variety in which pretonic syllables are longer than tonic ones. I analyze the production of oxytones, bi- and trisyllabic paroxytones and proparoxytones by six speakers from Córdoba and three from the neighbouring province of San Luis. An analysis of relative duration and intensity, as well as pitch accent types, revealed that pretonic lengthening was more prominent in and near the capital of Córdoba than in the rest of the province but was also attested in San Luis. Consistent with previous studies (Requena et al. 2013; Lang-Rigal 2014), participants from Córdoba showed a tendency to align the f0 peak within the stressed syllable but varied in the alignment of the peak depending on the type of word and the location. Overall results support the existence of a geographical continuum in the use of relative duration of tonic, pretonic and posttonic syllables (Vidal de Battini 1964) and reveal the need of more systematic explorations of the correlate of stress in different word types and across Argentine varieties.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.241
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.016
GPT teacher head0.325
Teacher spread0.309 · 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 designObservational
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
Published2025
Admission routes1
Has abstractyes

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