Assibilated [ř] in Ecuador: Exploring Sociolinguistic Factors among Young Quiteños
Bibliographic record
Abstract
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: 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) 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. 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.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".