La distancia social y su relación con la cortesía lingüística en el español : Un estudio sobre hablantes andaluces
Bibliographic record
Abstract
This thesis examines how social distance in terms of different relationships affects the usage of linguistic resources, with a focus on the Spanish region Andalusia. The aim is to investigate how relationships between different interlocutors affect language, and particularly what different strategies of politeness are being used, and how these differ regarding each interlocutor presented. For the investigation, there are two main types of speech acts used: invitation and request. 30 native and residential Andalusians have participated in the investigation and answered a survey concerning several social situations. The results show that indirect types of politeness strategies are in general more produced when the social distance is extensive. Furthermore, the results of the investigation indicate that politeness strategies can also differ between interlocutors that do not reflect an exceeding social distance. The results presented in this thesis contribute to the research field of sociolinguistics with focus on how social distance affect the usage of politeness in the Andalusian region, which will be useful for making comparisons between different regions in the Spanish speaking world.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| 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".