Bibliographic record
Abstract
En primer lugar debo agradecer a la excelentisima directora de esta docta casa, Enriqueta Vila Vilar, mi nombramiento como miembro correspondiente de ella y aprovecho esta ocasion para felicitarla por su merecido nombramiento como miembro de la Real Academia de la Historia que tanto la honra y nos honra a todos los sevillanos. Igualmente dar las gracias al los excelentisimos senores academicos D. Rafael Manzano y D. Jose Maria Vaz de Soto que tuvieron la gentileza de unirse a la propuesta. Durante mi carrera academica y profesional he recibido algun que otro reconocimiento tanto en Canada como en Espana; ninguno me ha sido ni sera tan grato como este de Real Academia Sevillana de Buenas Letras en la que se integran o se han integrado mis mejores maestros, colegas y amigos. Cuando recibi la noticia senti que no habia hecho meritos bastantes para recibir tal nombramiento pero como es facil encontrar una explicacion que justifique las cosas que nos benefician personalmente he llegado a la conclusion que si hay algo de lo que me siento orgullosa y que, aunque no aparece en mi curriculo, supone una aportacion a Andalucia. Me refiero a haber ensenado el castellano con acento andaluz a un sin numero de extranjeros; la mayor parte canadienses aunque ahora mismo no puedo pensar en un pais de los que no haya tenido alumnos. En mi facultad compartia la ensenanza de la lengua y la literatura castellana con profesores espanoles, latinoamericanos, canadienses e ingleses y me atrevo a presumir, LA TRANSGRESION EN LAS JARCHAS RomanceS
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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | no category Domain: not available · Genre: Other About the Canadian research system: no · About a Canadian topic: no | Theoretical or conceptual | medium |
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.017 |
| Scholarly communication | 0.014 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.023 | 0.007 |
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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".