The PSR corpus: A Persian sentence reading corpus of eye movements
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 present study introduces the Persian Sentence Reading (PSR) Corpus, aiming to expand empirical data for Persian, an under-investigated language in research on oculomotor control in reading. Reading research has largely focused on Latin script languages with a left-to-right reading direction. However, languages with different reading directions, such as right-to-left and top-to-bottom, and particularly Persian script-based languages like Farsi and Dari, have remained understudied. This study pioneers in providing an eye movement dataset for reading Persian sentences, enabling further exploration of the influences of unique Persian characteristics on eye movement patterns during sentence reading. The core objective of the study is to provide data about how word characteristics impact eye movement patterns. The research also investigates the characteristics of the interplay between neighboring words and eye movements on them. By broadening the scope of reading research beyond commonly studied languages, the study aims to contribute to an interdisciplinary approach to reading research, exemplifying investigations through various theoretical and methodological perspectives.
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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 it