Images identitaires et rhétorique : la première de couverture de guides touristiques1
Bibliographic record
Abstract
Nous analysons la première de couverture de guides touristiques de la France, de l’Espagne et du Portugal, dans chaque cas à l’intention d’un public exogène. Chacun de ces territoires doit être capable de transmettre une spécificité et de la faire sienne dans l’ambiance absolument concurrentielle de la prolifération de lieux touristiques. C’est ainsi qu’une identité est bâtie à travers un discours fait de mots et surtout d’icônes servant à profiler le pays en question. La première de couverture des guides fournit alors un accès privilégié à une réalité réduite par la pars pro toto à quelques représentations devenues assez familières. On envisagera donc en quoi ces éléments construisent des emblèmes identitaires.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.016 | 0.021 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".