User eXperience and Translatability Viewed through the Lens of a Triple Constraint: Time, Cost and Quality
Bibliographic record
Abstract
User eXperience (UX) guidelines make web contentengaging, while controlled language guidelines makeit easily translatable. As organizations seek to servediverse linguistic populations, the question of whetherUX and translatability are compatible or in conflictbecomes increasingly relevant, particularly when itcomes to balancing time, cost and quality. This paperreports on a multilingual recipient evaluation of webcontent.Les lignes directrices venues de l’expérienceutilisateur (UX) rendent les contenus Web invitants,tandis que les directives de langage ciblé les rendentfacilement traduisibles. Du fait que les organisationscherchent à servir des populations linguistiquesdiverses, la question de savoir si l’expérienceutilisateur et la traductibilité sont compatibles ou enconflit devient de plus en plus pertinente, enparticulier quand il s’agit d’équilibrer temps, coût etqualité. Cet article présente une évaluation par undestinataire multilingue de contenus Web.
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 | 0.001 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.010 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 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".