Quantifying word informativeness and its impact on eye-movement reading behavior: Cross-linguistic variability and individual differences
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 importance or centrality of a linguistic unit to a larger unit's meaning is known to affect reading behavior. However, there is an ongoing debate on how to quantify a unit's degree of importance or centrality, with previous quantifications using either subjective ratings or computational solutions with limited interpretability. Here we introduce a novel measure, which we term "informativeness", to assess the significance of a word to the meaning of the sentence in which it appears. Our measure is based on the comparison of vectorial representations of the full sentence with a revised sentence without the target word, resulting in an easily interpretable and objective quantification. We show that our new measure correlates in expected ways with other psycholinguistic variables (e.g., frequency, length, predictability), and, importantly, uniquely predicts eye-movement reading behavior in large-scale datasets of first (L1) and second language (L2) readers (from the Multilingual Eye-tracking Corpus, MECO). We also show that the effects of informativeness generalize to diverse writing systems, and are stronger for poorer than better readers. Together, our work provides new avenues for investigating informativeness effects, towards a deeper understanding of the way it impacts reading behavior.
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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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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