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Record W2900546581 · doi:10.1515/zrp-2018-0070

Principales rasgos gramaticales del español de Nicaragua

2018· article· en· W2900546581 on OpenAlexaff
Enrique Pato

Bibliographic record

VenueZeitschrift für romanische Philologie (ZrP) · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicSpanish Linguistics and Language Studies
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsAdjectiveAdverbLinguisticsVariety (cybernetics)NounGrammarSubject (documents)HistoryPsychologyComputer scienceArtificial intelligencePhilosophy

Abstract

fetched live from OpenAlex

Abstract This work offers an in-depth description of the main morphosyntactic features found in present Nicaraguan Spanish, a lesser known Central American variety despite being the subject of one of the pioneering dialectological studies on Spanish (Barreto 1893). With the help of text corpora and sociolinguistic surveys, an updated grammatical overview is provided, which takes into account most categories: nouns, adjectives, verbs, adverbs, prepositions and locutions (coordinators, subordinators, among others), and illustrates with examples taken from both formal and informal settings. By comparing these features with previous grammatical descriptions, this study helps in identifying some common American features ―such as the use of medio as an agreeing adjective instead of an adverb particle― as well as some specific patterns ―such as the prominence of ‑udo/‑uda and ‑oso/‑osa suffixes― in present-day Nicaraguan Spanish, some of which remain to be incorporated in the Academy grammar.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.071
Threshold uncertainty score0.140

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.049
GPT teacher head0.309
Teacher spread0.260 · 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 source (direct Gemma or distilled Codex), 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

Citations8
Published2018
Admission routes1
Has abstractyes

Explore more

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