La Validite D’Equivalence de Versions Multilingues d'un Texte ou d'un Questionnaire (Equivalence Validity of Multilingual Versions of Texts or Questionnaires) (In French)
Bibliographic record
Abstract
Internet, par sa nature globale, apporte de nouvelles opportunites de recherche et d'affaires dans des contextes multiculturels. Or, une situation exolingue accroit le risque d’imprecision ou de confusion linguistiques. Les auteurs de cet article presentent une synthese des methodes utilisees pour traduire et valider les textes. Ils proposent une approche pour traduire et valider des textes et des questionnaires de recherche tout en assurant la validite d'equivalence des versions linguistiques. La methode proposee pourra etre aussi utilisee dans un contexte d’affaires.The global nature of Internet brings new research and business opportunities in multicultural contexts. However, an exolingual setting increases the risk of inaccuracy or linguistic confusion. The authors review methods used to translate and validate texts and questionnaires to another language. They propose a methodology to translate and validate multiple linguistic versions of research questionnaires while ensuring their equivalence validity. The proposed methodology is applicable to a business setting as well.
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 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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| 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".