Les amis d’en face : petite promenade ironique dans la Base de données lexicographiques panfrancophone
Bibliographic record
Abstract
After drawing a brief panorama of previous analysis of irony and having identified its main relevant features, we analyse lexical units which bear the mark « ironique ou plaisant » within the Base de données lexicographiques panfrancophone, starting by interrogating ourselves on the existence of irony on the level of language or of discourse. \nOur analysis is then carried out on the description of seventeen entries, which are classified according to several criteria: geographical origin (Burundi, Morocco, Quebec, Switzerland), the rhetorical device which is used, the presence or absence of a mocking intention. We thus conclude that lexicalised irony seems to be the mirror of a society’s worries: it is a finger doxa points on the shortcomings that characterise the society it comes from, as well as on its political organization, its functioning rules, its practices. All this seems to be projected by irony against the backcloth of an ideal horizon.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".