Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The World Wide Web presents an amazing array of authentic documents in a form called ‘hypertext’ that language learners can use not only to find out about target language cultures but also to develop reading skills. However, as authentic documents, they are more difficult to read than texts traditionally associated with language instruction. This article will analyze such texts in light of reading research and will propose solutions to two potential areas of difficulty. The first is the need to read documents from a computer screen. Since successful reading involves familiarity and habits, activities that add to students' reading experiences are described. The second relates to the varieties of the target language found on Web sites, which teachers can approach through lower-level reading processes including learning basic vocabulary related to the Web, searching native language versions of bilingual sites, using a translation site, pronouncing words aloud, and guessing contextually. These techniques can help students overcome obstacles to reading comprehension. The content of Web sites will be the subject of a future article on higher-level processes.
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.025 | 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 it