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Record W2438670951 · doi:10.5296/ijl.v8i3.9593

Assibilated [ř] in Ecuador: Exploring Sociolinguistic Factors among Young Quiteños

2016· article· en· W2438670951 on OpenAlexaff
Jesús Toapanta

Bibliographic record

VenueInternational Journal of Linguistics · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicLinguistic Variation and Morphology
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPronunciationLinguisticsClass (philosophy)PsychologyLexisEthnic groupSocial classFirst languageSociologyGrammarPolitical scienceLawComputer science

Abstract

fetched live from OpenAlex

<p class="1">It is extraordinary how extra information such as age, birthplace, education, and social strata is displayed when people talk. Sometimes, it is enough to hear a person to know where that person is from. For instance, the juxtaposition placed on intelligence regarding the southern English dialects in the US:</p><p class="1">Gov. Clinton, you attended Oxford University in England and Yale Law School in the Ivy League, two of the fines institutions of learning in the world. So how come you still talk like a hillbilly? (as quoted in Lippi-Green, 1997: 211)</p><p class="1">Indeed, language aspects such as prosody, syntax, lexis, and/or pronunciation reveal certain characteristics such as birthplace, age, ethnicity, and social strata, to mention some. In Ecuador, one just needs to hear the interlocutor to know where the person is from or is not from. One peculiar characteristic of the speech of Quiteños in Ecuador is the usage of the Spanish trill [ r ] and/or the assibilated [ ř ]; that is, the intervocalic phone in the Spanish word ‘arroz’ can be realized with a trill [ r ] or an assibilated [ ř ] sound. This variation is allophonic and might make people rank individuals on a social scale, judge them as educated or uneducated, and/or link them to a particular speech community. </p><p class="1">This paper explores some possible extra-linguistic factors such as education, social class, and language domains that may be associated with this allophonic variation in the speech of young Quiteños. Data for this paper was collected through a questionnaire at one relatively large university in Quito-Ecuador and mainly reflects participants’ perception on the usage of these two sounds. <strong></strong></p>

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)0.072
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.301
Threshold uncertainty score0.936

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.072
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.072
GPT teacher head0.354
Teacher spread0.282 · 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

Citations3
Published2016
Admission routes1
Has abstractyes

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