A corpus-assisted SFL approach to individuation in the European Parliament: the case of Sánchez Presedo’s original and translated repertoires*
Bibliographic record
Abstract
The present paper proposes a synergic approach between systemic functional linguistics (SFL) and corpus linguistics (CL) in order to explore (original and translated) individuation (and its associated concepts of realisation and instantiation). After a brief introduction (Section 1) and presentation of SFL-related notions (Section 2), the paper discusses the methodological path that is followed in describing the representation of one case of individuation in the European Parliament, that of Spanish Social-Democrat Sánchez Presedo (Section 3). In a largely qualitative use of CL, the paper examines the profile of the speaker’s individuation, stemming from his published/instantiated original interventions in EP proceedings (Section 4). It then identifies the similarities and differences between this published profile and its translated re-instantiation (Section 5), ultimately drawing conclusions after an analytical venture (Section 6).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".