Semántica del discurso: la variable de género. Una investigación sobre el sexismo semántico
Bibliographic record
Abstract
El presente artículo, siguiendo la corriente investigadora de la Sociolingüística feminista en América del Norte (EE.UU., Québec y Montréal), estudia, desde el lenguaje de género, el sexismo lingüístico, tanto sintáctico como léxico, su caracterización gramatical, y aporta como novedad el estudio del sexismo semántico aplicado a cinco variantes discursivas, con estrechos lazos culturales entre ambas orillas (española; atlántica: argentina, panameña, mexicana; y mediterránea: marroquí), con el fin de ver cuáles son los universales antropológicos que el análisis pragmático y textual ofrece a través de tres principios semánticos: 1. el significado implícito por inferencia; 2. la oposición de antónimos explícitos: sintagmáticos y paradigmáticos; 3. el contraste o antítesis de términos homónimos y polísemos. El procedimiento de reconstrucción de significado que se ha seguido es el siguiente: a. significado implícito inferencial → b. oposición de antónimos explícitos sintagmáticos → c. contraste o antítesis entre diferentes significados de términos homónimos → d. contraste o antítesis entre diferentes acepciones de términos polísemos → e. oposición de antónimos explícitos paradigmáticos.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.021 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".