Réflexion méthodologique sur l’usage des logiciels Modalisa et Iramuteq pour l’étude d’un corpus de presse sur l’anorexie mentale
Bibliographic record
Abstract
L’anorexie mentale est une maladie polyfactorielle complexe aujourd’hui considérée comme un problème de santé publique par le corps médical. Toutefois, les discours médiatiques sur ce sujet sont relativement récents. Notre contribution vise à comprendre comment se caractérise la couverture médiatique de cette pathologie et quelles représentations construisent les médias de ce trouble lié à l’adolescence tout en montrant en quoi le recours à des logiciels d’analyse automatisée de discours peut nous être utile. Pour cela, nous menons une analyse quantitative et de contenu d’un corpus de 131 articles, publiés entre 1995 et 2009, dans divers quotidiens nationaux, avec le logiciel Modalisa. Puis, nous utilisons le logiciel Iramuteq pour identifier les mondes lexicaux organisant les discours en nous appuyant sur un second corpus, plus restreint.
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
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 | 0.026 | 0.071 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.014 | 0.012 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.018 | 0.004 |
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".